Eindhoven University of Technology
MASTER
Making smart use of the maritime heavy lift shipping industry
Smits, L.L.
Award date: 2016
Link to publication
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• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain Eindhoven, September 2016
Making smart use of
the Maritime Heavy Lift Shipping Industry
By
L.L. (Lars) Smits
Student identity number 0650460
In partial fulfilment of the requirements for the degree of
Master of Science In Operations Management and Logistics
Supervisors: Dr. M. Slikker, TU/E, OPAC Dr. E. Demir, TU/E, OPAC
Company supervisors: John Slijkoord, Damen Shipyards Paul van Leeuwen, Damen Shipyards
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TUE. School of Industrial Engineering. Series Master Theses Operations Management and Logistics
Subject headings: Logistics, Maritime Shipping, Heavy Lift Shipping, Maritime Transportation.
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Abstract This master thesis describes a research conducted at Damen Shipyards. Damen Shipyards is Netherlands biggest shipbuilding company with customers located worldwide and different shipyards in Europa and the South East of Asia. One of the many challenges Damen is facing with their worldwide activities is about shipping the vessels to the customers. The shipping prices can vary greatly for different ships, for different routes and over time. When Damen can transport several ships at once usually the price per ship goes down. We investigate where these variations come from and how Damen can combine more transports in a cost effective manner. Furthermore there is the idea that a longer term planning will decrease the transportation prices received by shipping companies. Whether or not this idea is correct is investigated. This is done by a literature research about maritime shipping costs and heavy lift shipping costs, by interviewing some of the largest heavy lift shipping companies to see if the current way of working leads to optimal shipping costs.
The most important conclusions are that currently there is no synchronized way of working between different product groups with regard to stock transportations. Some product groups are reactive in regard to stock transportations where others are proactive. A proactive approach increases the opportunities for stock transportations and lowers the overall logistic costs. Better internal information sharing between different Product Groups and the Deliveries department is needed that will also improve the chances of finding more cost efficient combination transportations.
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Preface This report shows the result of my Master Thesis performed at Damen Shipyards. This is the last requirement in the fulfillment of the Master Operations Management and Logistics in the direction of Operations Planning & Accounting. I have had much pleasure in the time I did this research at Damen and met a lot of great people. Furthermore I was introduced to the maritime industry and got hooked instantly. Therefore I am proud to say that I will be working for Damen soon!
I would like to thank Paul van Leeuwen and John Slijkoord who were supervising me throughout this study. I have learned a lot from your experiences on all kinds of interesting topics. Although I sometimes had the idea that you were not convinced of the direction I was heading or you would already know the answers you gave me time and room to develop these insights myself. If I had questions you always tried to help me or showed me where I could find the answers. Furthermore I would like to thank all direct colleagues for the help and the fruitful and pleasant collaboration.
I also would like to thank dr. M. Slikker and E. Demir. You have always provided me with honest and constructive feedback. You gave me a lot of freedom to think of creative solutions and gave me good guidance to deliver a nice end product.
This Master Thesis is the end of my three year master program at the Technical University of Eindhoven. From the moment I started I had a lot of fun with my classmates. We had a lot of fun in trying to find answers to questions in class as well as outside of class.
This is a nice opportunity to thank my family. My parents and brother. Without them I would not have been able to pull this off.
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List of Abbreviations AST: Area Service Team BOF: Basic Ocean Freight BR: Berth Rate CC: Capital Costs CDF: Cumulative Distribution Function DPC: Daily Port Costs DWT: Deadweight FC: Fuel Consumption FCB: Fuel Consumption at Berth FCS: Fuel Costs Sea GRT: Gross Registered Tonnage I: Initial Investment Costs IC: Interest Costs L/C: Letter of Credit LC: Loading Costs MC: Maintenance Costs MEC: Main Engine Capacity MT: Metric Ton MTO: Make To Order MTS: Make To Stock MWS: Marine Warranty Surveyor nm: Nautical mile OC: Operating Costs OOPC: One-off Port Costs PC/UMS: Panama Canal Universal Measurement System PG: Product Group POD: Port/Place of Discharge POL: Port/Place Of Loading PTCC: Percentage Total Charged costs to Customer RSM: Regional Service Manager SCNT: Suez Canal Net Tonnage SR: Sea Rate SUBC: Ship Utilization by Customer cargo SWL: Safe Weight Load TEU: Twenty feet Equivalent Unit TU: Trip Utilization UNCTAD: United Nations Conference on Trade and Development w/m: Weight or Measurement WACC: Weighted Average Cost of Capital
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Management summary Very fluctuating costs for heavy lift shipping in a worldwide maritime environment is what Netherlands’ biggest shipbuilding company Damen Shipyards has to deal with on a daily bases. There are concerns that current mid- to short term planning of heavy lift is not optimal in receiving the best possible offers from shipping companies. Furthermore Damen is trying to find a way how to optimally make use of their size to make more cost efficient stock transportations. Last but not least this study quantifies the value of offering more flexibility towards shipping companies.
Research questions The following research questions were developed. The main question is: How can maritime heavy lift transportations for complete vessels be designed in an efficient way and what are the impacts on costs and delivery performance?
In order to be able to answer this research question three sub-research questions are formulated that need to be answered in advance:
1. What are the current processes in the delivery of complete vessels, what types of activities and factors influence cost and delivery performance and how is current performance measured?
2. What is the value of offered flexibility by customers and what factors influence this value?
3. What processes need to be redesigned to go to a longer-term planning and what would be the consequences on the flexibility towards the customer?
Method By describing the internal processes at sub question 1 insights are provided about the internal structure for the heavy lift deliveries. Where the first sub question is more internal oriented, answering the second sub question gives information about external factors such as market structure and the associated costing structure. This is answered with use of literature research (Smits, 2016) and by discussing with heavy lift shipping companies. The information provided by answering sub research question 1 and 2 is used as input for a simulation tool to assess the costs in maritime shipping for a shipping company. After these two questions are answered an answer can be provided for the last sub research question. Possible gaps between the internal way of working and the external market structure can be evaluated.
Results Most factors that influence cost and delivery performance are outside of the organization. These factors are among others the position within a trade network, trade imbalances, complementarity of trade, competition, liner services, connectivity, distance but also the volume or weight of the shipped product are all influencers of costs for maritime shipping. There are some internal factors as well. The amount of offered flexibility for instance can lower the shipping prices.
Figure 1 shows the cost structure for one simulation run of the ASD3412ICE for the route Ha Long – Vera Cruz with 28 days of flexibility. The x-axis shows the number of heavy lift ships that are able to lift the
vi cargo based on the Safe Weigh Load of the cranes on board, in this case there are 32 ships. The y-axis shows the costs in Euro. The costs are already sorted from low to high. The dark blue bars show the mobilization costs, the blue bars show the loading costs, the aqua colored bars show the sea voyage costs, the green bars show the canal passage costs, the orange bars show the unloading costs and the yellow bars show the demobilization costs. The red crosses show the utilization rates for each specific ship which can be read in the y-axis on the right.
Figure 1: Cost structure of shipment of ASD3212ICE.
Also combining the transportation of multiple ships can have a significant impact on the price per ship received from shipping companies. Since this price is by far the largest proportion of heavy lift shipping costs one would assume everything is organized in a manner that supports this. After conducting in depth research in the way revenues are distributed between different shareholders within the Damen organization we can conclude that these are all in line what should be expected. If product groups make smart choices with regard to stock transportations they are rewarded with a higher share of the revenue gained by selling ships. However, the way that each product group handles stock transportations is very different. Some product groups are proactively searching to make combinations possible where others are most of the time in a reactive state. Product Groups as well as Sales will not know of planned transportations and booked transportations for other Product Groups or Sales Areas. Although the bookings are for other areas the route could still be through another Sales area. In this case it could be beneficial to use this information in negotiations with customers where customers can be steered towards a planning where a combination is possible which would lower the transportation costs. Product Groups only know their own stock levels and own wishes for stock transportations. These wishes do not always reach the Deliveries department. Improvements can be made here. A structural information sharing process between Sales, Product Groups and the Deliveries department is not present at this moment. Having such a process could greatly improve the possibilities to combine transportations within the Damen Group. Section 9.2 describes this into more detail.
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Offering more flexibility is definitely of great value to receive low prices from the shipping companies due to a couple of reasons that are listed below.
- More chance finding a ship close by the port of loading. - More chance finding a more cost efficient ship close by the port of loading. - More chance for the shipping company to find additional cargo - More competition for shipping companies
Besides the external advantages having more flexibility to execute a shipment also increases the possibility to find combinations internally. Offering more flexibility does not always mean that shipments will be performed later. It does mean that shipping companies will understand there is more competition for the cargo and will most likely use a pricing strategy accordingly. The Deliveries department usually offers a wide indication for a time of shipment to the shipping companies. This is most of the time a combination of the factors above but also due to uncertainties in the completion date of the ship and uncertainties in receiving a green light from Sales due to payment issues from customers. Determining the exact value of offered flexibility is difficult since estimations have to be made about the increase in cargo room utilization values for each ship with each increase in flexibility. Data analysis of earlier transportations could help improve the estimations. Unfortunately due to the way data about costs and all other relevant information such as offered flexibility, date of shipment, fuel prices and route data analyses cannot be performed accurately.
The third research question was formulated with the underlying assumption that current short to mid- term planning is not cost efficient. After discussing this with the two biggest Dutch heavy lift shipping companies BigLift and Jumbo Maritime and studying the prices received from shipping companies the conclusion can be made that going to a longer term planning is not to be recommended. This is due to the following reasons. Shipping companies usually do not know themselves where their ships will be in a period further away than approximately three months from now. Also the amount of other cargo that can be found for a similar route is difficult to estimate. This makes that shipping companies indicate prices with a lot of safety margin. Jumbo Maritime and BigLift also explained that there have been efforts in the past with other customers to set up such a longer term commitment for multiple shipments but these efforts stranded quite soon due to practical and cost issues. Figure 1 shows the minimum costs for shipments and how much variation there is with other ships. Therefore it is very unlikely that having a long term relationship with only one shipping company is cost efficient. When shipping companies are booked first the cargo of the shipper becomes base cargo. Cargo that is booked later becomes additional cargo or spot cargo. These spot cargo is cargo that is going with a ship that already covered all or most of its costs for a journey. This makes that spot cargo usually does not account for much more costs for the shipping company which can make the price offered to the shipper a low one. The downside is that it can be risky to always wait for the spot market option. Ships can be fully booked or be booked for other destinations which makes this option disappear. It is always a trade- off between waiting longer for booking the best spot option price and taking a lot of risk or booking earlier with less risk.
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Conclusion Although most cost factors are external Damen can still improve the way they have organized transportations. The concerns that current mid- to short term planning of heavy lift is not optimal in receiving the best possible offers from shipping companies are most likely raised due to the high fluctuations in prices received from different shipping. Although the prices can vary significantly this research concludes that current mid- to short term planning is contributing to receiving low prices from shipping companies. However, Damen can improve by switching from a reactive state to a proactive one and continually search for possibilities to make combinations of transportations possible. To achieve this the information sharing between Sales, Product Groups and the Deliveries department must be made easy and understandable. An information sharing system can help with that. Finally the value of the amount of offered flexibility towards the shipping companies is definitely underestimated by the decision makers. Although it is hard to determine the cost savings accurately this study showed that by offering more flexibility the average costs for the shipping companies decrease significantly. The results are shown in Table 1, Table 2, Figure 2 and Figure 3.
Table 1: Cost savings compared to one offered flexibility day
Flexibility days 28 56 84 112 Rotterdam € 143.250 € 234.180 € 293.670 € 314.180 Vera Cruz € 113.330 € 191.143 € 253.010 € 297.390 Lagos € 86.300 € 143.417 € 188.897 € 202.600 Sharjah € 94.153 € 131.003 € 133.843 € 135.453
Table 2: Relative costs compared to one offered flexibility day
Flexibility days 28 56 84 112 Rotterdam 79% 66% 57% 54% Vera Cruz 85% 74% 66% 60% Lagos 86% 77% 69% 67% Sharjah 75% 65% 64% 64%
Figure 2: Boxplot for different flexibility days ASD3212 Figure 3: Boxplot for different flexibility days ASD3212ICE Vietnam-Rotterdam Vietnam - Sharjah
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Table of Contents Abstract ...... iii Preface ...... iv List of Abbreviations ...... v Management summary ...... vi Research questions ...... vi Method ...... vi Results ...... vi Conclusion ...... ix 1. Introduction ...... 1 2. Company description ...... 2 2.1. The history of Damen ...... 2 2.2. The current situation of Damen ...... 2 2.3. The Deliveries department ...... 3 3. Problem definition and research questions ...... 5 3.1. Research questions ...... 5 3.2. Method ...... 5 3.3. Scope ...... 6 4. Current processes ...... 7 4.1. Responsibilities ...... 7 4.2. Information flow ...... 8 4.3. Financial flows ...... 11 4.4. Delivery operational activities ...... 11 5. Costs determinants for maritime shipping ...... 13 5.1. Determinants for international maritime transport costs ...... 13 5.1.1. Ports ...... 16 5.1.2. Trade flows ...... 17 5.1.3. Structure of the maritime industry ...... 17 5.1.4. Position within the global shipping network ...... 17 5.1.5. Ship operating costs ...... 17 5.1.6. Facilitation ...... 17 5.1.7. Shipped product ...... 17
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5.1.8. Discussion liner shipping ...... 18 5.2. Non containerized cargo ...... 18 5.2.1. Flat rack containers ...... 18 5.2.2. Breakbulk/General cargo ...... 20 5.2.3. Semi-submersible ...... 20 6. Heavy lift ...... 21 6.1. Heavy lift fleet ...... 21 6.2. Heavy lift crane capacity ...... 22 6.3. Heavy lift costing method ...... 22 7. Design to quantify the costs for heavy lift transportation ...... 23 7.1. Mobilizing costs...... 24 7.1.1. Mobilizing time ...... 24 7.1.2. Sea Rate...... 29 7.2. Loading costs ...... 33 7.2.1. Berth Rate ...... 33 7.2.2. Port Costs ...... 34 7.3. Sailing Costs ...... 36 7.3.1. Travelling costs ...... 36 7.3.2. Ship utilization ...... 36 7.3.3. Canal costs ship ...... 38 7.3.4. Canal costs cargo ...... 40 7.4. Unloading costs ...... 40 7.5. Demobilization costs ...... 40 7.6. Summary of the heavy lift cost model...... 41 8. Simulation ...... 42 8.1. Input Parameters ...... 42 8.2. Validation and verification ...... 43 8.3. Results and analysis of simulation ...... 45 9. Conclusion ...... 50 9.1. Research conclusion ...... 50 9.2. Recommendations ...... 53 9.3. Limitations and further research ...... 55
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10. Bibliography ...... 56 11. Appendix ...... 59 Appendix A: Damen ship types ...... 59 Appendix B: Damen worldwide ...... 60 Appendix C: Organogram Damen ...... 61 Appendix D: Swimlane diagram ...... 62 Appendix E: Container freight markets and rates...... 63 Appendix F: Port tariff structures Asian ports ...... 65 Appendix G: Heavy lift fleet overview ...... 66 Appendix H: Stopford model for revenue and costs of operating a ship ...... 69 Appendix I: Distances per location baseline route ...... 70 Appendix J: Regression results distance round voyage ...... 71 Appendix K: Sample for fuel consumption analysis ...... 72 Appendix L: Regression tests results energy usage ...... 73 Appendix M: Example of Port costs calculation ...... 74 Appendix N: Deck length regression analysis...... 77 Appendix O: Canal Net Tonnage regression analyses...... 78 Appendix P: Top Heavy Lift ships characteristics and costs...... 79 Appendix Q: MATLAB functions and calculations...... 82 Appendix R: Poster thesis ...... 85
Figure 1: Cost structure of shipment of ASD3212ICE...... vii Figure 2: Boxplot for different flexibility days ASD3212 Vietnam-Rotterdam...... ix Figure 3: Boxplot for different flexibility days ASD3212ICE Vietnam - Sharjah ...... ix Figure 4: The structure of the thesis ...... 1 Figure 5: Overview of number of shipments per year as derived by data analysis performed at Damen ... 3 Figure 6: Locations of heavy lift deliveries ...... 4 Figure 7: Research model by Mitroff et al. (1974) ...... 6 Figure 8: Schematic overview of information flow ...... 9 Figure 9: Example of information flow between departments ...... 10 Figure 10: Summary activities for shipment ...... 12 Figure 11: Cost components for arranging heavy lift shipment ...... 13 Figure 12: The "no-relationship" between distance and maritime transport costs (United Nations Conference on Trade and Development, 2015) ...... 14
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Figure 13: The relationship between transport costs and port connectivity (United Nations Conference on Trade and Development, 2015) ...... 14 Figure 14: Seven determinants for maritime transport costs (Wilmsmeier, 2014) ...... 16 Figure 15: Interceptor 1102 ...... 18 Figure 16: Overview semi-submersible ships (National University of Singapore, 2008) ...... 21 Figure 17: Heavy lift fleet in lifting capacity >250 metric ton SWL ...... 21 Figure 18: Top down view of heavy lift vessel with two 350 tons cranes (BBC-Chartering, 2016) ...... 22 Figure 19: Cost determinants for heavy lift shipping ...... 24 Figure 20: Density in world shipping (Energeo Politics, 2015)...... 25 Figure 21: Geographic round voyage of baseline ...... 25 Figure 22: Distance to Singapore for baseline route ...... 26 Figure 23: Distribution of ships for certain flexibility days ...... 27 Figure 24: Mobilization distance ships close to maximum ...... 27 Figure 25: Cumulative Distribution Function with different flexibility days ...... 29 Figure 26: Fuel consumption container ships ...... 31 Figure 27: Energy usage ship against DWT ...... 32 Figure 28: Residuals of regression line ...... 32 Figure 29: Overview of Loading costs ...... 33 Figure 30: One-off Port costs for different ship sizes and ports ...... 35 Figure 31: Average daily port costs for different ships ...... 35 Figure 32: Overview of sailing costs ...... 36 Figure 33: Deck length of heavy lift ships ...... 38 Figure 34: Visualization of simulation model ...... 43 Figure 35: Cost structure of shipment of ASD3412ICE ...... 46 Figure 36: Cost structure of shipment ASD2411 ...... 46 Figure 37: Minimum costs per simulation run ASD2411 ...... 47 Figure 38: Minimum costs per simulation run ASD3412ICE ...... 47 Figure 39: Boxplot of minimum costs for 100 simulation runs ASD3212ICE ...... 48 Figure 40: Boxplot for different flexibility days ASD3212 Vietnam-Rotterdam ...... 49 Figure 41: Boxplot for different flexibility days ASD3212ICE Vietnam - Sharjah ...... 49 Figure 42: Boxplot for different flexibility days ASD3212 Vietnam-Rotterdam ...... 52 Figure 43: Boxplot for different flexibility days ASD3212ICE Vietnam - Sharjah ...... 52 Figure 44: Graphical overview of information sharing system ...... 54 Figure 45: Global activities Damen Shipyards Group...... 60 Figure 46: Organogram Damen ...... 61 Figure 47: Swimlane diagram at the Delivery process ...... 62 Figure 48: Container freight rates ...... 64 Figure 49: Container freight rates per nautical mile ...... 64 Figure 50: Market share of top 15 multipurpose shipping companies by deadweight with a combined lifting capacity above 100 tons (Toepfers, 2016) ...... 66 Figure 51: Revenue and cost summary (Stopford, 2009) ...... 69 Figure 52: Residual plot baseline against CDF uniform distribution ...... 71
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Figure 53: Deadweight distribution of sample size ...... 72 Figure 54: Residuals deck length ...... 77 Figure 55: Suez Canal Net Tonnage regression analyses ...... 78
Table 1: Cost savings compared to one offered flexibility day ...... ix Table 2: Relative costs compared to one offered flexibility day ...... ix Table 3: Dimensions flat rack container ...... 19 Table 4: Number of lost slots on container vessels for small ships ...... 19 Table 5: Mobilization distance for ships close to the maximum ...... 28 Table 6: Engine power heavy lift ships ...... 31 Table 7: Port costs for different ship sizes ...... 34 Table 8: Suez Canal toll charges ...... 39 Table 9: Panama Canal toll charges ...... 40 Table 10: Route characteristics ...... 42 Table 11: Cargo characteristics ...... 42 Table 12: Scenarios with different flexibility days ...... 42 Table 13: Real life route costs ASD2411 Vietnam – Mexico ...... 44 Table 14: Simulation results with only ASD2411 Vietnam - Mexico ...... 44 Table 15: Real life route costs ASD 2411 Vietnam - Rotterdam ...... 45 Table 16: Simulation results with only ASD2411 Vietnam - Rotterdam ...... 45 Table 17: Average minimum costs for ASD2411 for different destinations and flexibility days ...... 48 Table 18: Average minimum costs for ASD3212 for different destinations and flexibility days ...... 48 Table 19: Average minimum costs for ASD3412ICE for different destinations and flexibility days ...... 48 Table 20: Cost savings compared to one offered flexibility day ...... 50 Table 21: Relative costs compared to one offered flexibility day ...... 50 Table 22: Cost savings compared to one offered flexibility day ...... 51 Table 23: Relative costs compared to one offered flexibility day ...... 51 Table 24: Container freight markets and rates ...... 63 Table 25: Port tariff structure Asian ports overview ...... 65 Table 26: Top of Heavy lift fleet ...... 66 Table 27: Baseline ship route ...... 70 Table 28: Model summary regression baseline against CDF uniform distribution ...... 71 Table 29: Statistical tests regression analysis baseline against CDF uniform distribution ...... 71 Table 30: Model summary regression analysis energy usage against DWT ...... 73 Table 31: Statistical tests regression analysis energy usage against DWT ...... 73 Table 32: Port costs Valparaiso, Chili ...... 75 Table 33: Port costs Anchorage of Ha Long, Vietnam ...... 76 Table 34: Model summary regression analysis deck length against DWT ...... 77 Table 35: Statistical tests regression analysis deck length against DWT ...... 77 Table 36: Model summary regression analysis SCNT against DWT ...... 78 Table 37: Model summary regression analysis PC/UMS against DWT...... 78
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1. Introduction This chapter will serve as a guideline how the structure of this thesis is set up. It will also give an introduction to the research topic. This research is performed in partial fulfillment of the Master Operations Management and Logistics at the Technical University of Eindhoven. The research is performed at the headquarters of the biggest shipbuilding company of The Netherlands Damen Shipyards for a period of five months.
Although Damen has still been growing the last few years the current market conditions are worrisome. This puts a lot of pressure on shipping prices. The shipping prices can even make the difference between selling or net selling a ship. Luckily, due to the volume of ships that are produced there are possibilities to combine transportations for stock purposes and for different customers between the different Damen product groups and production locations. Damen produces a wide variety of ships for different markets with different ship sizes. Although we do elaborate on shipping prices for lighter ships the main focus is on the heavy lift shipping markets where price fluctuations are higher. The organization of these transportations is in control of the Deliveries department of Damen. The actual transportation from loading to unloading harbor is executed by heavy lift shipping companies.
First the company Damen and the Deliveries department are introduced in Chapter 2. The Deliveries department is in control of the coordination of the transportations. The problem definition and the research questions are stated in Chapter 3. After the company is introduced and the problem is formulated the current way of working will be described extensively with responsibilities, workflows and financial flows in Chapter 0. Chapter 5 discusses the shipping industry and Chapter 6 the heavy lift shipping market and associated costs. This information is used as input to develop a model to determine the costs for heavy lift ships for different routes and ships which is discussed in Chapter 7. Chapter 8 discusses the simulation method and the validation and verification of the results. Also the outcomes of the simulation are discussed and the results are given. Finally the conclusion and recommendations are stated in Chapter 9. Figure 4 illustrates the structure of this thesis.
Internal activities
Chapter 4
Designed Company Problem Maritime Conclusion and Introduction model shipping Simulation description definition shipping costs recommendations costs Chapter 1 Chapter 2 Chapter 3 Chapter 5 Chapter 7 Chapter 8 Chapter 9
Heavy lift shipping costs Chapter 6
Figure 4: The structure of the thesis
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2. Company description The Damen company is introduced next. The history of Damen is shown as well as the current activities. Furthermore the Deliveries department is introduced together with the amount of shipments per year and the variety of locations where the shipments are send.
2.1. The history of Damen Damen was established by two brothers back in 1927. Today, with more than 9,000 employees, Damen Shipyards Group has earned a leading position in the shipbuilding world. Damen is an international company, but, at heart, they are still a family company with family values and a deep respect for their maritime heritage. (Damen, 2015)
In 1922, the two Damen brothers, Jan and Rien, started building boats in a shed next to the family home. Five years later they formalized the company as Damen Brothers. It remained a small, yet prominent, company for more than 40 years. In 1969 Kommer Damen bought the company from his father and introduced the concept of modular construction to build small boats and launches. This concept of standardization (known today as The Damen Standard) generated clear advantages: fast delivery times, reduced costs and proven designs. The concept was an immediate success and in 1973 the company expanded to larger facilities in Gorinchem, the Netherlands. Due to Gorinchem’s strategic position for the dredging industry, Damen built workboats and auxiliary equipment. These workboats soon gained an excellent reputation in many foreign markets and Kommer Damen saw the potential for export. The steady growth continued as Damen took over numerous yards specializing in niche markets. This led to the establishment of partnerships and business cooperations with yards all over the world. Since the introduction of the modular shipbuilding concept, Damen has delivered more than 5,000 vessels.
2.2. The current situation of Damen Today, Damen Shipyards Group operates in many shipbuilding sectors and has gained a prominent and trusted standing throughout the world. With a global workforce numbering more than 9,000, Damen builds a wide variety of standard hulls for stock at dedicated shipyards in strategic locations. An overview of the different types of ships that are produced by Damen is shown in Appendix A. Production capacity is up to 160 vessels per year. Most ships are built in China, Vietnam, Singapore, Romania, Poland and The Netherlands. An overview of the worldwide activities executed by Damen is shown in Appendix B.
Damen does more than building ships – it also has an international network of lifecycle support services that includes maintenance and repair & conversion facilities. (www.damen.com, 2015) Nowadays Damen is still a sales driven organization. The headquarter of Damen is located in Gorinchem. From here the worldwide activities are managed. The locations of Damen shipbuilding and services activities is shown in the overview below. Most shipbuilding activities occur in China, Vietnam, Singapore, Romania, Poland and the Netherlands. The ships that are built are for a wide variety of markets and come in all weights and sizes. Damen is active in the Tugs, High Speed vessels, Pontoons, Offshore, Dredgers, Ferries, Naval Defense vessels, Transportation ships and Fishing ships markets. Damen has organized its structure by making seven Product Groups (PG’s, a list of abbreviations can be found on page v) that
2 each focusses on its own market. These PG’s are responsible for the supply chain from the Design and Proposal to completion on site. The organogram that shows this structure is in Appendix C. Here the Deliveries department is also shown. Hierarchy wise the Deliveries department; “Ship Deliveries & Trials” is located below the CPO, Damen Services, Services Operations and Training & Deliveries Services. The following section introduces the Deliveries department.
2.3. The Deliveries department The Deliveries department of Damen is responsible for coordinating and managing all activities regarding the transportation of hulls, stock and sold ships. The department is split into two groups. There is the heavy lift group consisting of four employees. The other group also consists of four employees and is responsible for coordinating and managing the activities required for own keel transportation.
By conducting internal data analysis the transportation costs and numbers are determined. In 2014, 67 ships were transported with use of heavy lift and 59 by own keel transportation. This is a total of 126 ships. In 2014 the costs for these activities were respectively €8.200.000 and €14.400.000. The costs involved in own keel transportation are among others crewing costs, fuel and lubricants costs, project costs, administration and legislation costs such as St. Vincent registration and insurance costs, parts and provisions costs and harbor costs. Also canal passage costs and anti-piracy costs can be involved.
For heavy lift transport there can be several options. If the cargo has lifting lugs they can be used to lift the ship. Otherwise the ship has to be lifted with the use of belly sling or by using a semi-submersible carrier. This is a carrier that can lower their deck below the surface of the water. Costs for heavy lift transportations include mobilization costs of the ship from shipyard to loading location and mobilization costs for the shipping cradle from the manufacturer to the loading location. Also loading charges such as agency fees, port charges and tugboats need to be accounted for. Depending on the value of the cargo a Marine Warranty Surveyor is obligatory and for below surface activities divers need to be hired. The last five years the numbers of transported ships and shipments have been tripled from 50 ships in 2011 to more than 140 transported ships in 2015 as shown in Figure 5.
Shipments Transported ships 150 150
100 Own keel 100 Own keel Heavy Lift Heavy Lift 50 50 Total Total 0 0 2011 2012 2013 2014 2015 2011 2012 2013 2014 2015
Figure 5: Overview of number of shipments per year as derived by data analysis performed at Damen
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Heavy Lift shipments in these five years were to locations worldwide. Figure 6 shows the locations of deliveries of the last five years. These deliveries are from all Damen yards and illustrates the diversity of customer locations.
Figure 6: Locations of heavy lift deliveries
Currently the booking of these shipping companies is done on a short-term basis, i.e. 2 months in advance or less. This is due to a couple of reasons. In maritime shipping, after a transport is booked the shipper is obliged to pay the transportation price agreed with the shipping company. So the shipper would want to be certain that the shipment is not delayed or cancelled. Both internally and externally there are uncertainties. Internally there is the uncertainty of the availability of the ship with regard to building times and testing. Externally there are the uncertainties about customers’ payments. In general, customers would like to receive their ships as fast as possible and within a reasonable time frame. This short-term planning in combination with a short delivery time is one of the reasons the deliveries employees feel they depend significantly on the capricious prices received from the shipping companies. This research investigates further how the current tactical (mid-term) and operational planning (short- term) limit the efficiency of the transport deliveries.
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3. Problem definition and research questions This section introduces the problem statement. The problem concerns the transportation of ships from their shipyard or stock location to stock locations or customers’ desired destination located all over the world. These shipments are performed by specialized shipping companies that travel the seas in order to fulfill these demands. The coordination and project management is executed by the deliveries department of Damen services. They approach the market and return the costs and planning to the Sales department. Sales is not convinced that the current way of working is optimal. The problem can be stated as follows:
Sales is not convinced that current way of working is optimal in receiving low logistic costs for the delivery of ships from yards to customers.
Research questions are developed to tackle this problem and are discussed in the next section.
3.1. Research questions The following research questions are formulated to give more insight into the problem. The main question is formulated as follows:
How can maritime heavy lift transportations for complete vessels be designed in an efficient way and what are the impacts on costs and delivery performance?
In order to be able to answer this research question three sub-research questions are formulated that need to be answered in advance:
1. What are the current processes in the delivery of complete vessels, what types of activities and factors influence cost and delivery performance and how is current performance measured?
2. What is the value of offered flexibility by customers and what factors influence this value?
3. What processes need to be redesigned to go to a longer-term planning and what would be the consequences on the flexibility towards the customer?
By describing the internal processes at sub question 1 insights are provided about the internal structure for the heavy lift deliveries. Where the first sub question is more internal oriented, answering the second sub question gives information about external factors such as market structure and the associated costing structure. After these two questions are answered an answer can be provided for the last sub research question. Possible gaps between the internal way of working and the external market structure can be evaluated. One such gap could be the current short term planning for shipments. In this study the operational research model as described by Mitroff et al. as shown in Figure 7 is used. Mitroff et al. research model is described in the next section.
3.2. Method The operational research approach consists of four phases. These are conceptualization, modeling, model solving and implementation. In the conceptualization phase, a conceptual model is developed of the problem. Here the decisions on which variables need to be included in the model are made and the
5 scope of the model and problem is defined. In the modeling phase the quantitative model is actually build, this the relationships between variables are defined. In the third phase the model solving process takes place. In this phase the mathematics usually play a dominant role. In the fourth and final phase the results of the model are implemented. After this a new cycle can start. Mitroff et al. argue that the research cycle can begin and end at any phase, as long as the researcher is aware of the parts of the solution process that is addressed in order for the researcher to make claims based on the results of the research. This report as build up similar to this research model. There is some overlap between Different chapters of this report and the phases as described by Mitroff et al. but in general this report is set up as follows: Chapters 4, 5 and 6 are about the conceptualization of the model. Chapter 7 is the modeling phase, Chapter 8 is the model solving phase and Chapter 9 is about the implementation of the results.
Figure 7: Research model by Mitroff et al. (1974)
3.3. Scope In this research the focus is placed on the transportation of sold ships as well as stock transportations from the major producing locations in China, Vietnam and Singapore to locations worldwide. The loading harbors are Shanghai, Ha Long Bay and Singapore. Furthermore shipments for all non-stackable ships will be taken into account where the focus is on heavy lift ships. Stackable or dismantled ships such as pontoons, barges and dismantled dredgers will not be taken into account
Although Damen has performed these kind of operations for over 25 years data analysis about costs is difficult to perform. This is because internally no universal method exists to store costs for different shipments over time. Therefore one cannot interpret the stored data in a valid way which limits this study. Besides the limited stored data the heavy lift literature is limited as well. This could be because heavy lift is only a very small portion of total maritime transportations.
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4. Current processes Now that the company and the scope of this project are described we can go further into detail on processes. First the responsibilities within the organization for preparing, booking and executing transportations is discussed. After that the information sharing processes are discussed as well as financial flows. Finally the operational activities are described.
4.1. Responsibilities The way of working for Deliveries is captured in a swimlane diagram as shown in Appendix D. This diagram shows the different responsibilities for the departments within Damen and shows the third parties involved in the delivery process. Ships are made to stock and made to order. The important elements in the process for make to order are described first.
When Sales has sold a ship and the customer wants to have the ship delivered by Damen activities regarding the coordination of transportation can begin. A kick-off meeting is initiated by an employee of the Area Service Team (AST) and a budget is created in the Enterprise Resource Planning system IFS. The Deliveries department creates a project in IFS and checks the planning of construction with the responsible Product Group (PG). They also ask for quotes of the shipping companies. What usually happens is that several different prices are received from different shipping companies. The Deliveries department makes a tradeoff between the options received on planning and price. When the selection is made on planning and price the Deliveries department determines what would be a good price for the shipment, this is usually done by taking some sort of weighted average of the lowest three. This is done to ensure that the price in the internal quotation that is send to Sales is reliable. The lowest option could disappear due to planning reasons of the shipping company or planning changes by Damen.
The Delivery departments makes sure all stowing plans are received by the PG. The shipping company proposes a lifting idea based on these stowing plans. This is checked by the PG’s engineer and the Marine Warranty Surveyor (MWS). A MWS is required for shipping an object with a value greater than 5,000,000 USD or for shipping multiple objects with a value greater than 7,500,000 USD. Before the shipping contract with the shipping company can be signed the Booking Permission Memo needs to be signed by Sales and the responsible Project Manager and the shipping contract is checked by Legal. Before the Deliveries department signs the contract with the shipping company they renegotiate with the shipping companies that offered a good price before. If a shipping company has found more cargo for similar routes the costs for taking the Damen cargo are lower for the shipping company. It does happen that these lower costs are reflected in a new lower price for Damen. Other subjects of negotiating are the amount of demurrage rates and days. How often or how much the prices received from shipping company lower due to renegotiating or waiting longer before booking is unclear due to the way the information is stored. When performing data analysis it is not possible to compare the initial price received from a shipping company and the final price at booking. This needs to be made possible if one would like to investigate this further.
After signing the contract with the shipping company Damen is obliged to pay the shipping company even if Damen does not want to ship its goods anymore. The Delivery department arranges crew of the local shipyard to transport the ship from the construction yard to the loading port at sea. The Deliveries
7 department makes sure insurance papers are in order. The Chief Products Officer approves the physical loading on the carrier by signing a Release Memo. This is among others to secure that customer payments are according to payment schedule. A local shipping agent is hired to deal with local export activities and to fine tune the loading place with the carrier. If required, an employee of the Deliveries department supervises the loading of the vessel to deal with any unforeseen circumstances.
The ship is loaded on deck of the carrier and secured for transport. In the heavy lift shipping market the carrier expects payment no later than one week after loading but always before unloading of the cargo. The shipping company releases a Bill of Lading after loading. This document must be presented at the unloading location to receive the goods. The Deliveries department arranges for a Letter of Credit (L/C). This is to ensure payments are received according to the agreements made with the customer. The most common way is that Damen is responsible for the loading, transportation and the unloading of the ship. After the unloading the customer is responsible to further discharge the ship and accountable for other local costs such as compulsory stevedoring and port clearance. A lot of variations are possible for when the ownership, risks and responsibilities shift from manufacturer to customer. This is captured by the sales contract and shipping terms. After the payment of all invoices the project is closed and a subsequent calculation is performed by the AST.
The build time for ships made to order varies per type of ship. Smaller ships are constructed in 3 months’ time and larger ships can take up to 2 years to build. For example; The Damen smaller Tugs such as the STU1004 takes about 8 months to build and for the larger Tugs such as the ASD2810 a build time of 14 months need to be accounted for.
The activities described above are for build to order ships. For build to stock ship transportations the activities are quite similar. However there are now two options. Either ships are transported for stock keeping purposes or a ship that is already on stock is sold to a customer. In the case of sold ships shipments need to be executed in a short notice. Stock transportation has lower time urgencies and can only be executed to areas where the stock can be maintained and where customer specific demands can be applied. Here again transports can be booked after the Booking Permission Memo is signed by Sales and the PG.
4.2. Information flow The information exchange between internal departments and the Deliveries department with the carriers is discussed in this section. Sales is in the lead for sold ships whereas the Product Group decides when ships are transported for stock keeping purposes.
Information exchange between Sales and the Deliveries department only occurs when there is an opportunity to sell a ship. Sales contacts the Regional Service Manager (RSM) with information on ship type and planning. The RSM contacts the Deliveries department. The Deliveries department contacts different shipping companies to receive quotations for different shipments regarding price and planning. The deliveries department sets the Internal Damen Cost price (IDC) and communicates this with the RSM. The RSM sets a margin and communicates this with Sales. There is no rule for how the margin is determined. Sales communicates this with the customer.
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For stock transportations the Product Group communicates directly with the Deliveries department. Each Product Group determines his own stock levels and locations. Some PG’s are very active in finding good opportunities to transport ships for a low shipping price while others are less active or prefer not to ship for stock keeping purposes. Stock transportation only take place between Damen shipyards and are usually the result of multiple high ship selling probabilities in the same region. Another option that triggers a Product Group to make stock transportation is when multiple similar ships are located in the same region. In that case shipments take place only if combinations can be made within a Product Group. There are no rules or guidelines in how the Product Groups should operate in regard to stock transportations. Figure 8 shows a schematic overview of the information process.
Customer
RFQ Quotation Forecasts Product Sales Quotation RFQ Group
RFQ RSM IDC IDC
RFQ Deliveries
RFQ Quotation
Shipping company
Figure 8: Schematic overview of information flow
The lack in rules for stock transportations is worrisome due to a couple of reasons. This is illustrated with the use of an example. Figure 9 shows this example for a possible transportation for a sold ship. The seven different Product Groups and the seven different Sales Areas are shown. In the middle the heavy lift department is located. Consider the possible transport is set up for Sales Area 2 for a product which is in the portfolio of Product Group 7. The dark blue boxes are the boxes of Damen that will know about this transport since they are directly involved or informed by others.
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Customer
RFQ Interaction on stock and production planning
Product Sales Services Group
Sales Regional RFQ Service Product Booking Permission Memo Area 1 Area 1 Group 1
Sales Regional RFQ Service Product Area 2 Area 2 Group 2 Status IDC updates Sales Regional Service Deliveries Product Area ... Area ... Group ..
Regional Stowage plans Sales Product Service RFQ Area 7 Area 7 Group 7
Shipping Company
Figure 9: Example of information flow between departments
Only Sales Area 2, the Regional Service Area 2, the Deliveries department and PG7 will be informed by following the processes. It could well be possible that Product Group 1 would like to have a ship transported for stock keeping purposes. Since there is no structural information sharing process between Services Deliveries and the different Product Groups for planned transportations the Deliveries department is unaware of this possible wish for a stock transportation and the Product Groups are unaware of any possible transportation for Sales Area 2. All Sales Areas except Sales Area 2 are also unaware of this transport which blocks the possibility for them to take this information into account when negotiating with the customers. This information could be used to convince customers that the shipping costs are more cost efficient at Damen then under normal conditions because Damen can leverage economies of scale.
Combining the above means that Damen as a group does not reach their full potential for combining transports. Although no structural information sharing process exists there are multiple combined transports per year. This is sometimes initiated by the Product Groups, by customers that place an order for multiple ships or by the Deliveries department that see multiple orders for different customers come together. Before describing how this information sharing could be improved the financial flows, other delivery activities and the heavy lift shipping market and costs factors are discussed.
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4.3. Financial flows Although there is a wide variety when it comes to financing ships. In general ships are purchased by customers and a payment schedule is developed with Sales. This payment schedule normally shows a phased payment for different milestones during the building process. Payment schedules for customers can vary greatly between customers’ wishes and possibilities offered by Damen. In general the payment schedule for Make To Order (MTO) looks as follows.
- 30% is paid as down payment - 30% is paid after the hull is finished - 30% is paid after the engines are installed and outfitting is completed - 10% is paid after ex-yard delivery
When looking from a financial perspective transports are booked as late as possible. This is due to a combination of factors. First the completion date of each ship can vary greatly during the production phase. Second, due to a variety of reasons, the payment schedule is sometimes not complied with by customers. Booking as late as possible decreases the risk for an empty transport. The lack of uncertainty about payments limits the transportation department in booking the most cost efficient option. The transportation department cannot make an agreement with a shipping company when low prices are received and the option could be lost in a later stage. The next section describes the operational activities for heavy lift transportations.
4.4. Delivery operational activities To transport a ship from an inland (building) location to a customer located somewhere around the world all kinds of different activities need to take place. With these activities costs are involved. The activities are mentioned in a chronological order. First the activities performed by Damen are mentioned. Afterwards the activities are explained for the carrier as summarized in Figure 10. These lists are derived from information provided by experienced Damen Deliveries employees.
The activities of Damen are:
- Arrange shipping cradles - Arrange lifting gear - Preparing ship for sea voyage - Mobilization of cradle from building location to loading location - Mobilization of vessel from building location to loading location, either complete or dismounted by towage, truck, pontoon or own keel - Arranging for necessary formalities such as customs/export- and transport documents and port permits - Hiring of a Marine Warranty Surveyor - Coordinate lifting, loading and lashing
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The activities for the carrier are as follows.
- Mobilization nominated vessel of carrier - Arranging necessary formalities to enter port of loading - Entering port of loading and paying associated port dues - Performing loading preparations - Executing lifting, loading and lashing - Leaving port by pilots and assisting tugs - Executing sea voyage - Sailing through canal and paying canal costs - Arranging necessary formalities to enter port of unloading - Entering port of unloading and paying associated port dues - Performing unloading preparations - Executing unlashing and unloading - Leaving port by pilots and assisting tugs - Demobilization of nominated vessel of carrier
Activities overview
Preparing ship Mobilization to port Loading at port Sea voyage Unloading at destination
- Arrange shipping cradles - Mobilizing ship and - Hiring of MWS - Executing sea voyage - Entering port and paying - Arrange lifting gear cradles to port - Coordinate lifting, - Performing canal port dues - Prepare ship for sea - Arranging all necessary loading and lashing passage and paying canal - Executing unloading voyage formalities at port costs - Entering port and paying - Ship delivery to - Arranging necessary port dues customer - Mobilizing vessel formalities at unloading - Leaving port - Preparing for loading - Arranging all necessary port - Demobilizing of vessel formalities at port - Execute lifting, loading and lashing Legend: Activities by Carrier - Leaving port Activities coordinated by Damen
Figure 10: Summary activities for shipment
The main cost components that are necessary in order to be able to make a heavy lift shipment possible are shown in Figure 11.
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Internal Damen Nominated transportation vessel Cost price price
Subject Calculation method
Ship cradles Price per ton
Preparation Fixed per ship ship
Mobilization Price per ship ship per location
Local port costs Price per ship and formalities per location
Figure 11: Cost components for arranging heavy lift shipment
Now that the internal way of working is discussed more information about the shipping industry will be provided next in Chapters 5 and 6. After the shipping industry is discussed we will elaborate on how Damen can better fit their internal processes with the shipping market in Chapter 5.
5. Costs determinants for maritime shipping This chapter will elaborate on the costs from port to port that are involved in the delivery of Damen vessels to locations all over the world. It is based on publications from experts in the field of maritime shipping, interviews with experienced Damen employees and from information gained by talking with major heavy lift shipping companies. First results of studies will be discussed considering containerized liner shipments. This will give insights in the different aspects that are involved in maritime transportation costs. These insights are useful to understand the shipping market and can be of guidance for heavy lift transportation costs. These heavy lift costs will be discussed in the Chapter 6.
5.1. Determinants for international maritime transport costs There is a variety of factors that can influence maritime transportation costs. What first may come to mind is travel distance. The United Nations Conference on Trade and Development (2015) published their yearly review of maritime transport in which they discuss all kinds of maritime transport subjects. They showed the “no-relationship” between distance and maritime transport costs for liner shipping which is based on 12.595 observations of maritime transport costs in international trade in the year 2013 at the Standard International Trade Classification. The scatter dot diagram is shown in Figure 12. Their study showed that less than 2% of the transportation costs is explained by the travel distance.
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They argue that more than geographical distance, it maybe the economical distance, as for example captured by shipping connectivity and a countries position within global shipping networks that emerges as the relevant factor for international transport costs.
Figure 12: The "no-relationship" between distance and maritime transport costs (United Nations Conference on Trade and Development, 2015)
Other research on liner shipping connectivity such as Kumar & Hoffmann (2002), Marquez-Ramos, et al. (2005), McCalla, et al. (2005), Wilmsmeier, et al. (2006), Angeloudis, et al. (2006) and Wilmsmeier (2014) also concludes frequently that the position within a network has a more significant impact then geographical distance. This is also due to the influencing variables of liner network connectivity such as frequency and ship size. These are determined by the overall level of trade, port infrastructure, development options and geographic position.
The network of maritime and port industry and the countries and international organizations that act as governing and regulating bodies have complex interaction to function properly. Decisions made by these actors will also influence the cost of transportation for the region of country in trade with its counterparts. Figure 13 shows the reduction in freight rates with increasing connectivity. Connectivity is an expression of shipping possibilities, port infrastructure and industry structure. This study, based on 7.868 observations of maritime transport costs in international trade for the years 2012 and 2013 at the Standard International Trade Classification, shows that over 5% is explained by a ports connectivity as captures by its Bilateral Liner Shipping Connectivity.
Figure 13: The relationship between transport costs and port connectivity (United Nations Conference on Trade and Development, 2015)
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Port connectivity is an important factor for transportation costs. Also economies of scale can be one. According to the report of UNCTAD (2015) economies of scale occur at two different levels. First, system internal economies of scale, which reflect the decrease in transport costs per ton, as the size of the individual shipment increases. Second, system external economies of scale, which reflect the decrease in transport costs as the volume of trade between two countries increases. The latter is also linked to other determinants of transport costs, such as levels of competition, vessel operation costs and port infrastructure.
Remember that UNCTAD (2015) research is about liner container services and not heavy lift services. Similar scientific research about the heavy lift market is limited. Even though this is not about the heavy lift market it still provides some insights in the industry. For heavy lift transport it could also hold that the more connected a port is and the better it is located geographically the more likely it is to find ships that can combine cargo from other customers that share a similar route. In that case shipping companies can divide the shipping costs between the two, or more customers which makes the average price go down.
The freight rates in the container shipping industry is studied by UNCTAD (2015). The table that shows the container freight markets and rates generated by them is listed in Appendix E. It shows that the freight rates per market can change significantly within a year, i.e. up to 50%.
The tanker market, which incorporates the transportation of crude oil, refined petroleum products and chemicals shows that the freight rate is also very volatile and subjected to change. Very large crude carrier average spot earnings stood at $43.948 per day in the last quarter of 2014 and $27.315 per day for the entire year of 2014. This was in 68% increase from 2013 (Baltic Dirty Tanker Index, 2015).
For dry bulk the freight rate are also under pressure (Clarksons Research, 2015a). There is still a surplus of capacity and uncertainty in demand projections. In 2014 the average earnings were $9.881 per day. The low overall earnings put financial pressure on companies and some filed for bankruptcy (Clarksons Research, 2015b). For more detailed information on prices of these kinds of transportation you are reverted to Clarksons Research (2015b).
The three largest maritime types of transportation all show very fluctuating prices that depend on geographical location, trade imbalances between these locations, oil prices and port infrastructure. During the last decade more and more studies showed similar results what determinants for maritime transports costs are. A study from Kumar & Hoffmann (2002) was confirmed by subsequent studies. Based on results from Sanchez et al. (2003), Wilmsmeier et al. (2006), Wilmsmeier & Hoffmann (2008), Kumar (2010) as well as a literature review provided by OECD (2008), Wilmsmeier (2014) found seven different determinants for international maritime transport costs as shown in Figure 14.
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Figure 14: Seven determinants for maritime transport costs (Wilmsmeier, 2014)
These are ports that include infra and superstructure, port productivity, port operator model and port tariffs. The second determinant is trade flows which incorporates trade imbalances, volumes of trade and complementarity of trade. The third is the structure of the maritime industry. This is about competition, liner services supply and regulation. The next one is the position within the global shipping network, the connectivity, centrality and distance play a role here. The fifth determinant are the ship operating costs such as crewing, bunkering and registration. The sixth determinant Wilmsmeier found is facilitation for trade and facilitation for transport. The last determinant is about the shipped product such as the volume of the shipment, the value and the type of produce. The following sections will elaborate on each of the seven determinants for maritime transports as generated by Wilmsmeier (2014).
5.1.1. Ports In this section the characteristics of the different pricing mechanism of ports are elaborated. First of all, it is good to know that comparing port tariffs accurately is difficult due to the diversity in regulations and systems that are used by ports and due to variating currency exchange rates. Furthermore, there are ports where the tariff structure is difficult to obtain or confidential. The United Nations Economic and Social Commission for Asia and the Pacific (ESCAP, 2016) developed an overview that shows the most common structure for pricing structures in Asian ports as shown in Appendix F.
The following calculation is to show the port costs price strategy for heavy lift ships in the Port of Rotterdam. The Port of Rotterdam uses a pilotage base fee based on the draft of the ship plus an additional fee based on the route from sea to the quay location. Port dues are paid over the Gross Tonnage of the ship based on the type of ship/cargo. This means that for instance oil tankers have a
16 different price per GT then general cargo ships. Cargo dues are based on the shipped type of cargo multiplied with the weight of the cargo and there is a waste fee per day based on the main engine capacity. The birth hire is based on a fixed price multiplied with the length of the ship (Port of Rotterdam Authority, 2016). Specific port costs for several ports and several different heavy lift ships will be discussed in Section 7.2.2.
5.1.2. Trade flows Trade flows such as trade imbalances, volumes of trade and the complementarity of trade are incorporated in the determinants for transport costs since they are of influence for the liner routes set- up by shipping companies. Liner companies that ship goods between locations with balances trade flows and higher volumes of trade can achieve higher economies of scale which will lower the costs for shipping goods.
5.1.3. Structure of the maritime industry Besides ports and trade flows the structure of the maritime industry is also classified by Wilmsmeier as an important factor for maritime transportation costs. The amount of competition, the supply for liner services and local regulations are of impact for sea freight prices.
5.1.4. Position within the global shipping network The position within the global shipping network is a determinant that seems more obvious. Connectivity, centrality and distance are three important factors for transportation prices. When cargo needs to be transported between two locations which both have a good position in the network there are a lot of possibilities to ship the cargo. Cargo can be transported via a direct liner service or there can be made use of a network of liner routes.
5.1.5. Ship operating costs The fifth determinant is the operating costs of the ship. Crewing, bunkering and registration costs of the ship all impact the operations cost of the transportation ship and therefore impact the costs for shipping. Transportation ships have daily costs when at berth in a port and daily costs when sailing. Depending on the expectation of the amount of the utilization of the cargo room a price is set per container or per weight/measurement.
5.1.6. Facilitation The next determinant identified by Wilmsmeier is Facilitation. This can be divided in trade facilitation and transport facilitation. These subsections are about the set of policies aiming at reducing trade costs. These policies can range from the simplification and standardization of customs procedures, to investment in physical infrastructure projects such as deepening port waters and investing in shore cranes.
5.1.7. Shipped product The seventh and last determinant is about the volume, value and type of shipped product. Traditional pricing strategies were based on the value of the cargo. Nowadays trends are towards pricing strategies based on volume or weight of cargo but traditional pricing strategies still exists.
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5.1.8. Discussion liner shipping All these determinants are intertwined with each other. High volumes of trade, trade balances, high port productivity, good trade facilitation and easy to handle products work towards transportation ships getting bigger and bigger. This is because ships can achieve economies of scale. These reduction in the per unit costs consists of port costs, bunker costs, employees’ wages, canal costs and capital costs that are distributed over more cargo which contribute to an average lower freight rate compared to smaller ships.
Most Damen ships do not meet the requirements needed to ship with conventional container liner services. This is due to the ship sizes and weights of the Damen vessels. Only one ship type, the Interceptor 1102, Figure 15, can fit in a standard container. The costs and activities needed to transport oversized cargo will be discussed next.
Figure 15: Interceptor 1102 5.2. Non containerized cargo Cargo that does not fit within a container but that can be transported on the base of one container is classified as out of gauge cargo. Cargo that needs to be transported on more than one container is called breakbulk, oversized, heavy lift or project cargo. For out of gauge cargo flat rack containers exists.
5.2.1. Flat rack containers To transport out of gauge cargo a bed of flat racks is laid. On top of that the shipping cradles and the ship have to be lifted and sea tightened. Container ships prices are based on a price per container. Oversized cargo is charged for the number of lost container slots due to the size of the cargo. This means that for cargo that is only one meter longer it will be charged two containers. Cargo that is one meter longer and one meter wider is charged for four containers. If cargo is higher than a high-cube flat rack and lower than two high cube flat racks containers can still be loaded on top if the shipping company is willing to do that. If the cargo is higher than the height of two high cube containers no containers can be lifted on top due to strength issues. This means the shipper is charged for the base of flat racks plus all the containers that normally would go on top. This pricing method per container size is not ideal for cargo sizes that are not boxed shaped. To illustrate this the following calculation is for shipping small Damen vessels on a bed of flat racks on a container ship. This is an very simple representation of reality. Container ships are designed for containers to be loaded in the length of the ship. Sideways walls, athwart ship, are in the ships’ structure for strength and stability purposes. Therefore breakbulk size load needs to be placed sideways when stored below deck which increases the
18 number of lost slots. Above deck this problem does not occur. But here the stowing plan can bring up issues since containers placed below need to be loaded first and unloaded later. The dimensions for a 40 feet flat rack is stated in Table 3.
Table 3: Dimensions flat rack container
40’ feet Flat Rack Length (in m) Width (in m) Height (in m) Exterior 12.192 2.438 2.896 Interior 11.652 2.374 2.264
Table 4 shows the number of lost slots for the smaller Damen ships with or without mast. These are for the dimensions of the ship. The necessary room for shipping cradles and lashing lines is not taken into account. Also the number of containers that cannot be stacked on top anymore is not shown since this number is dependent on the shipping companies stow plan.
Table 4: Number of lost slots on container vessels for small ships
Type of ship Dimensions Dimensions Light Lost 20 ft Lost 20 ft Lost 20 ft Lost 20 ft in m (length x without ship slots slots slots with slots weight x mast in m weight with without mast without height) (length x (ton) mast mast longitudinal mast weight x athwart athwart longitudinal height) ship ship HSC, SPa 12.56x3.85x 11.85x3.70x 11 36 24 24 16 1204 5.51 3.72 HSC, FCS 16.15x5.40x 16.15x5.40x 20 42 28 36 24 1605 7.65 4.07 HSC, FCS 21.10x5.45x 21.10x5.45x 38 72 54 48 36 2206 8.79 6.11 HSC, FCS 19.70x8.20x 19.70x8.20x 44 90 72 80 64 2008 12.13 8.56
With above numbers of lost slots and an average basic ocean freight (BOF) price per TEU in 2014 from Shanghai to Rotterdam of $1,161 and Shanghai to West-Africa of $1,838 (United Nations Conference on Trade and Development, 2015). Smaller ships such as the Spa 1204 would cost around 16*$1,838= $29,408 BOF. For the FCS1605 the BOF price would be $44,112. With mandatory surcharges and Value Added Services for handling this non standardized cargo these prices would become higher.
The Deliveries department always considers shipping smaller ships with these kind of transportation services. A tradeoff is made between the costs for shipping with mast, shipping without mast and shipping on other types of transportation vessels. These other types of transportation vessels are described in the following sections.
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5.2.2. Breakbulk/General cargo Breakbulk ships, also referred to as multi-purpose or general cargo ships, is another option to transport oversized cargo such as steel pipes and coils, bagged cement and light ships. According to the yearly review of maritime transport of UNCTAD of 2015 there was a total of 77,000,000 DWT of breakbulk ships. With an average of 15,000 DWT per ship there are around 5,100 ships.
The pricing systems for breakbulk ships differ per shipping company. Companies work with port charges for the port of loading and unloading and with ocean freight rates per weight/measurement (w/m). Breakbulk ships sail on liner services, semi liner services and there are transportation ships that provide tramping services. Liner services shipping companies usually wield the w/m rates which is based on several aspects. The shipping company determines the daily rate of the ship, the port costs at loading and unloading and any possible canal costs and piracy protection costs. They set an expected utilization level for the vessel for the coming period. Based on the aspects above and the competition level a rate per w/m is set. Therefore routes that have high volumes of trade have a higher expected utilization level with less variation per voyage. Also there is more competition which lowers the w/m rate. Vice versa this works similar. Ships that sail on routes with lower volumes of trade expect to have a lower utilization which leads to higher w/m rates. Usually, but not always, customers can deviate from the dedicated ports of the transportation ship. The extra costs for sailing and the incurred port costs are charged directly to the customer.
For Damen ships the measurement is usually decisive for the transportation costs. The shipping companies also use an addition to the w/m rate based on the weight of the cargo. This means the rate for heavy cargo is higher per measurement then the rate for light cargo. The calculation method for the measurement used by the breakbulk companies is quite straightforward. The dimensions of the cargo in cubic meters is multiplied with the w/m rate. W/m rates vary from 65 USD w/m for light cargo up to 40 tons for highly utilized routes such as Antwerp-Singapore and Antwerp-Jeddah. For cargo of 90 tons the rates are around 90 w/m in USD. For cargo with a weight of 120 tons w/m rates are around 125 USD.
Cargo that weighs more than 120 tons usually cannot be lifted by the cranes of the breakbulk ships. The next logical step when arranging shipping possibilities from light cargo to heavy cargo after container shipment and breakbulk shipment is heavy lift shipment. Since heavy lift is the main subject of this thesis first the last option which is semi-submersible transportation will be discussed. After that chapter 6 is devoted to discuss heavy lift transportations.
5.2.3. Semi-submersible Semi-submersible transportation is usually the most expensive option for shipping heavy cargo. Semi- subs can lower their deck under the surface of the water by adding ballast. Then cargo can be maneuvered over the deck. Afterwards the deck is lifted by dropping the ballast and the ship is ready to sail. The overview in Figure 16 shows the semi-submersible fleet increase from year 2000 to 2012. Currently the largest ship-owner Dockwise has 22 semi-submersible ships in operation.
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Figure 16: Overview semi-submersible ships (National University of Singapore, 2008)
Semi sub transportations are very costly in nature and are normally only used for cargo that cannot be lifted by means of cheaper options such as heavy lift. The main subject of this thesis is about heavy lift therefore the costs for these kind of services are not discussed.
6. Heavy lift After the other types of maritime transportation have been discussed. The following will give information on heavy lift transportation. Cargo weighing between 120 metric tons to a maximum of 3,000 metric tons are usually lifted with use of heavy lift. The following sections will discuss the fleet, the cranes and the costing method for heavy lift ships.
6.1. Heavy lift fleet Heavy lift ships work in a niche market. The amount of ships that can carry these huge loads drops significant with each increase in lifting capacity. At the start of 2016 there are around 970 vessels that can lift over 100 metric tons and 325 vessels that can lift cargo of over 250 metric tons as shown in Figure 17 (Toepfers, 2016).
3500
3000 2500 2000 1500 1000
500 Totalmax SWL mt. in
0
1
51 11 21 31 41 61 71 81 91
101 111 121 131 141 151 161 171 181 191 201 211 221 231 Number of ships
Figure 17: Heavy lift fleet in lifting capacity >250 metric ton SWL
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There are only 32 ships that have a Safe Working Load of 900 tons, 22 ships that can lift 1,400 tons and 10 ships that can lift 1,800 tons. These ships are from companies such as Jumbo Maritime, BigLift Shipping, Sal Heavy Lift, Hansa Heavy Lift and Intermarine. A complete overview about market shares and the ships at the top of the heavy lift industry can be found in Appendix G.
6.2. Heavy lift crane capacity The Safe Working Load (SWL) is the maximum the ship is able to lift expressed in tons, this requires a simultaneous use of two or more cranes of the ship. Because of the decrease of SWL based on the outreach of the cranes only a small portion of the cranes maximum capacity can be used. Figure 18 shows a top down view of a schematic representation of a heavy lift vessel with 2x 350 SWL. Although this ship is listed as a SWL of maximum 700 metric tons she cannot lift Damen vessels of 700 tons. To lift vessels slings and spreaders are needed that can weigh up to around 30 metric tons each. Besides that required lifting maneuvers may transcend the SWL of a crane on any time during the lifting operation.
Figure 18: Top down view of heavy lift vessel with two 350 tons cranes (BBC-Chartering, 2016) 6.3. Heavy lift costing method The heavy lift shipping companies determine the cost for a shipment on several factors. These factors are quite similar to the factors for breakbulk ships as well as the seven determinants provided by Wilmsmeier (2014) but there is much more uncertainty within the heavy lift shipping industry. The higher uncertainty comes from the fact that there is less cargo for a fewer amount of transportation vessels and cargo destinations are more distributed. This means that the chance for these shipping companies to operate on highly efficient routes are lower.
Heavy lift ships have a much higher percentage of costs for mobilizing and demobilizing the ship. Also, compared to container- and breakbulk transportation, the expected utilization levels for the port of loading, port of unloading and the utilization during transportation are much lower. Besides that, the cranes of heavy lift ships are costly. Because of this these heavy lift ships are smaller than other transportation vessels so less economies of scale can be achieved. The next chapter will discuss all costs involved for the shipping company in heavy lift transportation.
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7. Design to quantify the costs for heavy lift transportation This chapter presents a model that incorporates all costs from the point of view of a heavy lift shipping company. The model shows a general representation for involved costs for a shipment for heavy lift cargo from a POL to the POD. It is used to determine the value of offered flexibility by shippers to shipping companies. The model is set up in such a way that the shipping costs for different routes and different cargos can be assessed for different amounts of offered flexibility. The value of flexibility is assessed with use of simulation in the software tool MATLAB. This will be discussed after the model is explained.
The representation for costs for the shipping company is set up based on a combination of the findings above as well as findings of Stopford (2009), outcomes of interviews conducted at the Dutch heavy lift shipping companies Jumbo Maritime and BigLift, the experiences of the employees of the heavy lift department at Damen and the information provided by the product director of cargo vessels of Damen. The findings of Stopford are shown in Appendix H.
Figure 19 illustrates the model. In essence, the Cost determinants for heavy lift shipping are quite similar to the seven cost determinants provided by Wilmsmeier (2014). Ports and port tariffs are addressed by the loading and unloading costs components. Trade flows are captured by the Mobilizing costs and the Ship utilization at the Sailing costs. The structure of the maritime industry and the amount of competition is captured by selecting only the ships that can possible load the specified cargo. Ship operating costs are addressed by the Sea and Berth rates. Facilitation is the only subject that is not captured in one way or another by the Cost determinants for heavy lift shipping model. This is because heavy lift ships are not dependent on trade and transport facilitations offered by third parties. The Shipped product determinant is captured in Cargo specs at the Loading and Unloading cost components and is of influence on the ship utilization.
The annual costs components of operating fleet overview of Stopford (2009) as represented in Appendix H are also captured by the model. The capital, interest, maintenance and operating costs are captured by the Sea Rate and Berth Rate. The voyage costs are captured by the Sailing costs and Cargo handling is captured by the Loading and Unloading cost components. This is explained in more detail in the following chapters.
As shown in Figure 19 there are five major cost determinants for shipping heavy lift. The nominated transportation vessel costs consist of the sum of each of these five components. Each major Cost Component has one or more Sub Cost Components. A Sub Cost Component is either a one-off cost component or a cost component that grows when more time is needed for the specific component. Both can be influenced by a factor which is in the third column. If the Sub Cost Component grows when more time is needed the growth rate is dependent on the Rates shown in the fourth column. The blue boxes Flexibility and Ship Utilization are factors that are highly stochastic. Each major Cost Component with its Sub Cost Components, Cost Drivers and Relevant Rates will be discussed next.
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Perceived market Nominated position transportation vessel price Total transportation vessel cost
Cost Components Sub Costs Components Cost Drivers Relevant Rates
Mobilizing Mobilizing time Flexibility Sea rate
Loading time Cargo specs Berth rate Loading Daily port costs One-off Port costs Ship size
Travelling time Ship Utilization Sea rate Sailing Canal costs ship Ship size Canal costs cargo Cargo size on deck
Unloading costs Cargo specs Berth rate Unloading Daily Port costs One-off Port costs Ship size
Demobilizing Demobilization costs Discharge location Sea rate
Not stochastic Legend: Highly stochastic
Figure 19: Cost determinants for heavy lift shipping 7.1. Mobilizing costs Mobilizing costs are incurred for sailing the transportation ship for the deviation needed to arrive at the Port of Loading. This deviation will be described as the mobilization distance. The mobilization distance is multiplied with the Sea Rate (SR) to calculate the mobilization costs. The mobilization time will be described first and the Sea Rate second.
7.1.1. Mobilizing time The heavy lift tramp ships sail to wherever there is cargo. At the moment of the first offer, which is an offer for indication purposes, the shipping company usually knows their gross route for up to one or two months ahead in time. For the remaining months the route is uncertain or unknown. The mobilization time stands for the extra distance the shipping company has to sail in order to arrive at the port of loading divided by the travel speed. The shipping company uses an expected value for this mobilization time. This expected value is dependent on the place of the port of loading as well as the flexibility offered as learned from the interviews at Jumbo Maritime and BigLift Shipping. Ports on major trade lanes are more likely to sail by then those on more exotic places. The following example will illustrate how this can be determined. The example starts with a flexibility of zero days. This means that the shipping company needs to be at the POL at an exact date. When the method to determine the
24 mobilization distance for zero days of flexibility is clear it will be shown how the mobilization distance for more days of flexibility can be determined.
Heavy lift ships on tramping services sail all around the world. Consider a round the world voyage, the distance towards a POL for a certain time is shown by plotting the distance towards the POL for each moment in time. The POL in this case is Singapore. The following route is used as a baseline. This route is based on the density of world shipping and follows the major trade lanes. The density in world shipping is shown in Figure 20. A geographic representation of the round voyage is shown in Figure 21. The red line in this figure is the route of a heavy lift ship.
Figure 20: Density in world shipping (Energeo Politics, 2015)
Figure 21: Geographic round voyage of baseline
The distance towards Singapore is shown for a certain route per location in Appendix I. Plotting the distance towards Singapore shows the graph as in Figure 22. The x-axis represents the number of days for the voyage. The y-axis shows the sailing distance per day towards Singapore.
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12000
10000 8000 Distance to 6000 Singapore 4000 Sorted distance 2000
Distance Singaporeto Cum. Distr. Funct.
0 Uniform
1
19 37 55 73 91
109 127 145 163 181 199 Day of voyage
Figure 22: Distance to Singapore for baseline route
The red line shows the sailing distance towards Singapore at each day of the round voyage. The dotted blue line shows the values sorted from small to large. This dotted line looks similar to a cumulative distribution function of a uniform distribution which is shown as the dashed purple line. Specified test results are shown in Appendix J. The results with a coefficient of determination 푅2 of 0.989 support the fact that the uniform distribution function is a good fit for the distance of a ship on a specific moment in time towards the POL. The distribution for this baseline is determined as a uniformly distributed function on the interval from the minimum distance zero to the maximum distance of 12,000 nm. The CDF of this baseline function is:
0 푓표푟 푥 < 0, 푥 퐹(푥) = 푓표푟 0 ≤ 푥 ≤ 12000, {12000 (1) 1 푓표푟 푥 > 12000. where 푥 is the distance away from the POL. When flexibility is increased the expected minimum sailing distance towards the POL decreases. How much the increase in flexibility impacts the expected minimum sailing distance is elaborated next.
Heavy lift ships sail at current downturn market conditions their economical speed which is around 14 knots. Heavy lift ships are roughly 40% of the time navigating in harbors and loading and unloading and 60% of the time the ships are sailing (Leeuwen, 2016), (Nijhuis, 2016). The average distance covered per day is then 14 ∗ 0.6 ∗ 24 = 201.6 nautical miles. Consider nine ships distributed over mobilization distance as shown in Figure 23. These distributed ships follow from the distribution of the baseline. Line A illustrates the mobilization distance from the POL at the starting point of each ship. Each dot represents a location of a specific ship.
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1,2 3,4 5,6 7 8,9 A B C 1,2 3 4 5 6 8,9 7 D E 1,2 3 4 5 6 8,9 7 F
-2000 0 2000 4000 6000 8000 10000 12000 14000 Distance from POL in nm.
Figure 23: Distribution of ships for certain flexibility days
Consider the distances of the ships at line A and then add some flexibility days. The amount of flexibility days in this example is five which is equal to a sailing distance of approximately 1,000 nm. Assumed is that ships are either sailing away or they are sailing towards the POL with equal probability. Line C represents the distance of the ship after five days. Ship 5, which sailed towards the POL, is at 7,000 nm. Ship 6, which sailed away from the POL is at 9,000 nm. The closest point towards the POL during this interval of ship 5 is 7,000 nm. The closest point towards the POL during this interval of ship 6 is 8,000 nm as illustrated by line E in Figure 23. The same method can be applied for all ships but around zero and 12,000 the mobilization distances look different. Once a ship has passed the zero mobilization line the ship will always sail away from the POL. But the minimum mobilization distance remains zero. Since ship cannot sail further then 12,000 nm away from the POL, ships sail towards the POL after they have reached the 12,000 nm point. This is illustrated by ship 7 which starting position is 11,500 nm, after 500 nm are travelled ship 7 reaches the maximum distance from the POL, after that he is sailing closer to the POL. When ship 7 has sailed 1,000 nm ship 7 is at the same distance as it’s starting distance. Figure 24 shows this into more detail.
A
B Ship 1 C
Time Ship 2 D Ship 3 E Ship 4
9000 10000 11000 12000 13000 Mobilization distance
Figure 24: Mobilization distance ships close to maximum
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The distance from the POL is shown for four other ships close to the maximum of 12,000. Each line going down, i.e. from A to B, or B to C, represents a time interval equal to an increase in flexibility of 2.5 days or a distance travelled of 500 nm. The mobilization distance of ship 1 after 2,000 nm is the closest point to zero on the line 12,000 to 10,000 which is 10,000. For ship 2, which started at point 11,500 the minimum point on the line from 11,500 to 12,000 to 10,500 is 10,500. For ship 3 the lowest point on the line from 11,000 to 12,000 to 11,000 is 11,000. The mobilization distance for this ship did not change. There is no ship that can have a starting position in which the mobilization distance after 2,000 nm is higher since the starting position of ship 3 was exactly on half the sailing distance away from the maximum point of 12,000.
Table 5 will show the mobilization distance for each time interval.
Table 5: Mobilization distance for ships close to the maximum
Time interval in days 0 5 10 Ship 1 12,000 11,000 10,000 Ship 2 11,500 11,500 10,500 Ship 3 11,000 11,000 11,000 Ship 4 10,500 10,500 10,500 What can be seen is that the maximum mobilization distance lowers per time unit with half of the travel distance. After 1,000 nm the maximum mobilization distance is 11,500. After 2,000 nm the maximum mobilization distance is 11,000.
This means the maximum mobilization distance is lowered with half of the average covered distance per 201.6 day per flexibility day which is: = 100.8 nm. 2
Following this method there will be a cluster at zero mobilization distance if the amount of flexibility days offered gets higher. Figure 25 shows the continuous cumulative distribution functions of zero, 30 and 60 flexibility days. The blue diamond shaped line is the cumulative distribution of the baseline function. The red squared line and the green triangle line have the same steepness as the CDF of the baseline but with the cluster at zero. This can be captured in the formula by using the same description as formula 1 and then subtracting the average speed the CDF if shifting to the left.
0 푓표푟 푥 < 0, 푥 + 100.8 ∗ 푓푑 푓표푟 0 ≤ 푥 ≤ 12000, (2) 퐹(푥) = { 12000 1 푓표푟 푥 > 12000 − 100.8 ∗ 푓푑. where 푓푑 is the amount of offered flexibility days.
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1
0,8
0,6 0 day 0,4
Probability 30 days 0,2 60 days 0 0 2000 4000 6000 8000 10000 12000 Mobilization distance in nm.
Figure 25: Cumulative Distribution Function with different flexibility days
This holds for POL’s that are on major trade lanes. Other POL’s will be charged a number of days extra dependent on the distance from the major trade lanes and the likelihood a heavy lift ship is sailing by that specific POL. This concludes this section of the mobilization costs. The Sea Rate will be discussed next.
7.1.2. Sea Rate The Sea Rate (SR) stands for the rate per day a ship operator needs to receive to cover the costs for operating and maintaining a ship for normal routes without any additional charges such as port charges, piracy safety measures and canal costs. Stopford (2009) described six costs subjects for maintaining and operating a fleet as described in Appendix H. Four of the six cost components are captured by the SR. These are the Capital and Interest costs (CC), the Operating costs (OC) and the Maintenance costs (MC). Besides these 4 also the Depreciation Costs (DC) is captured by the SR as well as one part of the Voyage costs. This part is the Fuel consumption costs. The other Voyage costs as well as the Cargo handling costs are captured by other cost components and will be discussed later. For each ship an estimation of the different costs has to be made to determine the SR. The elements with the chosen assumptions are described next.
To determine the CC and the IC the initial investment costs (퐼) to purchase a heavy lift ship needs to be known. This initial investment costs is assumed to follow a linear relation of €1,800 per DWT. This is based on the prices of heavy lift ships produced by Damen (Nugteren, 2016). Cranes cost an additional €800,000 per 100 tons for ships cranes’ SWL above 200 tons. In addition to that the top segment of heavy lift ships can have costs for all sort of systems needed to operate these heavy cargo such as Dynamic Positioning (DP) systems. Assumed is these only apply for ships with an SWL of 800 tons or more. These cost €800,000 per 100 tons SWL.
퐼 = 1,800 ∗ 퐷푊푇 + 8000 ∗ 푆푊퐿 푓표푟 푠ℎ𝑖푝푠 푤𝑖푡ℎ 푆푊퐿 > 200 푡표푛푠, (3) 퐼 = 1,800 ∗ 퐷푊푇 + 8000 ∗ 푆푊퐿 + 8000 푆푊퐿 푓표푟 푠ℎ𝑖푝푠 푤𝑖푡ℎ 푆푊퐿 > 800 푡표푛푠
where DWT is the deadweight and SWL is the safe weigh load per specific ship.
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The amount of value a ship should make to satisfy the shareholders can be determined with an weighted average costs of capital (WACC) method.
퐷 퐸 푊퐴퐶퐶 = ∗ 퐾 + ∗ 퐾 (4) 퐷+퐸 푑 퐷+퐸 푒 where D is the total debt, E is the total shareholder’s equity, 퐾푑 is the after-tax cost of debt and 퐾푒 is the cost of equity. Assumed is 60% loan and 40% own equity per investment. 퐾푑is assumed to be 0.04 and 퐾푒 is 0.08 (Nugteren, 2016). The depreciation costs are assumed to be linear and ships are assumed to have a depreciation over 25 years with an average of 350 working days per year (Stopford, 2009). The average cost per day can be then calculated with the following formula.
(푊퐴퐶퐶+1)∗퐼 퐶퐶 = (5) 25/350
퐼 퐷퐶 = (6) 25/350
Operating Costs consists of Crew, Stores, Repair and Maintenance, Insurance and Administration costs. These costs are different depending on the age of the ship. Different studies of Stopford (2009), Moore Stephens (2014) and Drewry (2006) show different results for each component of the operating costs and the maintenance costs but show quite similar total costs. Assumed is that the OC together with the MC is €4,800 per day which is in line with all three studies.
푂퐶 + 푀퐶 = €4,800 (7)
Fuel usage is not public information for most ships. Also no literature is available on the fuel consumption of heavy lift ships. The following part discussed an estimation method to estimate the fuel consumption of heavy lift ships. It is necessary to make a precise estimation since fuel costs is a significant part of the total costs for most voyages.
Fuel consumption is, among other factors, influenced by ship speed, its draught, sea conditions, the length and breadth of a ship and specific engine types (Duizer, 2016). To estimate the fuel consumption for each heavy lift ship a regression analysis is performed of the known Main Engine Capacity (MEC) which is plotted against the DWT of the ship. Shipping companies SAL, BigLift and Hansa Heavy Lift have made their engines types information public on their specifications sheet on the websites of the shipping companies. For other shipping companies the MEC’s are not publicly available. The fleet of these three heavy lift companies consists of 53 heavy lift vessels evenly distributed with DWT between 8,600 DWT and 20,100 DWT. The distribution of the DWT of each ship is shown in Appendix K.
Since there is a lot of variety in the way the data is presented by the shipping companies first the data has to be adjusted in such a way regression analyses can be performed. The listed main engine capacity comes with a maximum speed, speed at specific % of max engine power and sometimes with economic speeds. To go from the maximum speed at a certain energy output to the energy output at a speed of 14 knots the research of Notteboom and Carriou (2009) can be useful. Notteboom and Carriou studied the fuel consumption of 1,868 container ships with a capacity in the range of 2,000-6,000 Twenty Foot
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Equivalent (TEU). They discovered an exponential relation between speed and fuel consumption. This fuel consumption at speed v (퐹퐶푥) for container vessels with a carrying capacity between 2,000-3,000 TEU is given by the function:
퐹퐶푣 = 2.2381 ∗ 푒^(0.1694 ∗ 푣) (8)
Container ships with carrying capacity of 2,000-3000 TEU have a DWT of approximately 20,000-40,000. These ships are larger than most of the heavy lift ships. Figure 26 shows the fuel consumption for container ships for different sizes. For all sizes the relationship remains exponential.
100
80
60 2000-3000 teu
40 3000-4000 teu 4000-5000 teu 20 5000-6000 teu 0
Fuel consumption Fuel MT/day in 10 15 20 Speed in nm
Figure 26: Fuel consumption container ships
This exponential relation (2.2381 ∗ 푒^(0.1694 ∗ 푣)) between fuel usage in MT and speed is used to adjust the provided data to a kW at the economical sailing speed of 14 knots. This is justified since the relation between engine output in kW and fuel consumption is linear. If the datasheet shows the service speed and not the maximum speed the maximum engine power is multiplied with 0.8 to achieve the engine output at the given service speed. To account for the auxiliary engines 10% is added to the kW of the main engine. See Endersen, et al, (2003) Corbett & Koehler (2003) and EPA (2000). Table 6 with three different ships is added for understanding purposes. The DWT, MEC, given engine load factor and speed at load factor is information gathered from the datasheet of the ships.
Table 6: Engine power heavy lift ships
Ship name and shipping company MV Annette (SAL) F-Series (HHL) Happy Sky (BigLift) DWT (in ton) 8,919 12,744 17,775 MEC (in kW) 9,450 5,400 8,775 MEC + Auxiliary engines (in kW) 10,395 5,940 9,652.5 Given engine load factor 85% 100% 100% Engine power at given load factor (in kW) 8,835.75 5,940 9,652.5 Speed at load factor (SL) (in knots) 18 14.5 17 퐹퐶14 = 2.2381 ∗ 푒^(0.1694 ∗ 14) 23.98 23.98 23.98 퐹퐶푆퐿 = 2.2381 ∗ 푒^(0.1694 ∗ 푆퐿) 47.22 26.10 39.86 퐹퐶14/퐹퐶푆퐿 50.78 % 92.88 % 60.16 % Engine power at 14 knots (in kW) 4,487 5,457 5,807
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To determine the percentage of the maximum power a heavy lift ship needs to produce to sail the economical speed the fuel consumption at 14 knots is divided by the fuel consumption at the given engine load factor (퐹퐶14/퐹퐶푆퐿). This percentage is multiplied with the engine power at the load factor which gives the needed engine power to sail the economical speed. The engine power output at 14 knots is plotted against the deadweight to find a relation between ship size and fuel consumption for heavy lift ships. Ordinary least squares regression is used to find a relation between DWT and energy usage which is shown in Figure 27. Figure 28 shows the residuals of the sample set against the predicted regression line. The model summary and other statistical tests results are shown in Appendix L.
8000
7000 6000 5000 4000 y = 0.1128DWT + 3844.4 R² = 0.5687 Engine Engine 3000 2000
1000 powerkW in at 14 knots 0 5000 10000 15000 20000 25000 DWT
Figure 27: Energy usage ship against DWT
1000
500
0 5000 10000 15000 20000 25000 Residuals -500
-1000 DWT
Figure 28: Residuals of regression line
The results show that 57% of the variance is explained by the linear regression model. With a p value < 0.001 the F-test is significant. This gives an engine power y in kW at 14 knots of
y = 0.1128 ∗ DWT + 3,844.4 . (9)
If the kW needed for a specific speed is known the fuel consumption can be determined if the brake specific fuel consumption (BSFC) is known. Although the BSFC varies from engine to engine and is different for different load factors for each engine 200g/kWh is assumed (Duizer, 2016) (Endersen, et al., 2003).
With ships sailing 24 hours per day this gives a Fuel consumption per day in tons (FC) for heavy lift ships of:
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200 FC = y ∗ (24 ∗ ). (10) 1000000
The relation between ship size, speed and fuel consumption is complex. This is due to the different design of ships. Although there are more variables above method can be used as a good estimation of fuel consumption for heavy lift ships. Situation specific data should be obtained from the shipping company for more accurate analysis.
To summarize, the Mobilizing cost component consist of the mobilization time multiplied with the Sea Rate. The mobilization time is highly dependent on the flexibility offered by the shipper. The Sea Rate is:
푆푅 = 퐶퐶 + 퐷퐶 + 푂퐶 + 푀퐶 + 퐹퐶 (11)
This concludes the Mobilizing costs which is the first of the five cost components for heavy lift shipping. The next chapter will discuss the Loading Costs.
7.2. Loading costs The loading costs consists of two different sub components which are influenced by factors as shown in Figure 29. The first sub component Loading time is the costs payable to the port authorities for the time staying in a port performing loading operations. The second sub component are the costs payable to enter, navigate and leave the port specified in the model as One-off Port costs (OOPC) as shown in Table 7, these costs also incorporate any compulsory stevedoring and any other cargo handling surcharges. The Cargo specs determine the required loading time set per cargo type. This value is based on the required time needed to load the ship in earlier occasions. This is multiplied with the Berth Rate (BR) of the cargo vessel and the Daily port costs (DPC) of the port. The OOPC as well as the DPC are different per port and is usually based on the ship size. I.e. larger ships have higher OOPC and DPC.
Cost Components Sub Costs Components Cost Drivers Relevant Rates
Loading time Cargo specs Berth rate Loading Daily port costs One-off Port costs Ship size
Figure 29: Overview of Loading costs
7.2.1. Berth Rate The Berth Rate stands for the costs for the shipping company to maintain the ship in the port. It is set up by Capital Costs (CC), Depreciation Costs (DC), Operating Costs (OC), Maintenance Costs (MC) and Fuel Consumption costs at Berth (FCB). The CC, DC, OC and MC are the same as explained in section 7.1.2.
The FCB is studied with use of an international survey by Clean North Sea Shipping (2014) where the fuel consumption at berth was analyzed of various ships and ship types. The result is a linear function of fuel usage with deadweight to predict the fuel usage of these ships.
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Based on the datasheets provided by the website of shipping company BBC on which they specifically show the fuel consumption at berth with and without cranes 1 MT of fuel per day was added. The formula is as follows:
퐹퐶퐵 = ((0.0056 ∗ DWT + 18.16) ∗ 24/1000) + 1. (12)
The Berth Rate is:
퐵푅 = 퐶퐶 + 퐷퐶 + 푂퐶 + 푀퐶 + 퐹퐶퐵 (13)
7.2.2. Port Costs As explained in section 5.1.1 the calculation methods to charge ports costs are different from port to port. Table 7 shows the port costs for four different heavy lift ships. This is based on information provided by Wilhelmsen Shipping Agency. Below figures are for entering the harbor and loading one tug 500 ton boat a maximum of two days. Added in Appendix M are two examples of expected port costs provided by agencies to show how these costs are determined.
Table 7: Port costs for different ship sizes
BigLift Jumbo F800 SAL Type 161A BBC Happy Class MV Wiebke Mobile Star Mirabella Deadweight 17,750 14,360 9,370 3,500 Navigation $16,420 $16,763 $15,172 $8,662 Port of Rotterdam Berth per day $1,250 $1,241 $1,202 $486 Cargo Operations $7,573 $5,462 $3,792 $1,580 Navigation $3,401 $3,401 $3,401 $3,401 Port of Sharjah Berth per day $317 $226 $154 $58 (UAE) Cargo Operations $4,834 $4,834 $4,834 $4,834 Navigation $11,895 $11,247 $10,451 $8,064 Port of Shanghai Berth per day $729 $709 $671 $554 Cargo Operations $13,745 $13,745 $13,745 $13,745 Navigation $11,976 $11,563 $8,842 $7,853 Port of Singapore Berth per day $3,060 $3,060 $2,980 $900 Cargo Operations $9,000 $9,000 $9,000 $9,000 Navigation $9,341 $8,375 $6,707 $4,518 Berth per day $220 $154 $101 $30 Anchorage of Ha Long (Vietnam) Cargo Operations (2% on total ocean $8,000 $8,000 $8,000 $8,000 freight)
To estimate the port costs a general calculation method for the One-Off Port Costs and the Daily Ports Costs is used for all ports which is based on the DWT. The OOPC consists of the Navigation charge and the Cargo Operations charge. The sum of the four bigger ports is shown in Figure 30.
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$30.000 Sh = 0.2628x + 21204 R² = 0.9486 $25.000 R = 0.9555x + 8109.7 R² = 0.9427 $20.000 Si = 0.3162x + 15503 R² = 0.94 $15.000 Ha = 0.3401x + 11411 R² = 0.9973 $10.000 Rotterda $5.000 m Shanghai $0 0 5000 10000 15000 20000
Figure 30: One-off Port costs for different ship sizes and ports
The functions and the 푅2 are shown in Figure 30 for each port. Each port shows a linear relation between costs and DWT. Although there are some variations between the different port costs, the influence of this variance on the total costs for transportation is low. Therefore the average of these functions is used to estimate OOPC.
OOPC = $0.4686 ∗ 퐷푊푇 + $14,057. (14)
The average port costs per day is estimated with the same method. The influence of the difference in the daily port costs between ports and ships is minimal. The daily port costs are usually based on the length of ships. The best fit line for the data points as shown in Figure 31 is shown in formula 15.
퐷푃퐶 = $525.1 ∗ 푙푛(퐷푊푇) − $3,728.6. (15)
Figure 31 shows this logarithmic function for the four different ships. A R2 of 0.91 shows a nice fit. Due to the few amount of data points it does not make sense to do further statistical testing for both the OOPC and the DPC.
$1.600,00 $1.400,00 $1.200,00 $1.000,00 y = 525,1ln(x) - 3728,6 $800,00 R² = 0,9143 $600,00 $400,00
Berthcostsperday $200,00 $- 0 5000 10000 15000 20000 DWT
Figure 31: Average daily port costs for different ships
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The charged port costs are impacted by flexibility as well. Only the OOPC are costs that can be lowered by increased flexibility since there economies of scale can be achieved. These economies of scale are of small importance due to their low part of the total costs and the small probability multiple customers are found at the same harbor. Therefore these economies of scale will be neglected.
To summarize, the costs associated with the Loading Time are:
퐿푇 = (퐵푅 + 퐷푃퐶) ∗ 퐶푎푟푔표 푆푝푒푐푠 (16)
The total Loading Costs (LC) can be computed with
퐿퐶 = 퐿푇 + 푂푂푃퐶 (17)
This concludes this chapter about the Loading cost component. The next chapter will discuss the third cost component Sailing costs.
7.3. Sailing Costs The next cost component, Sailing costs (SC), is usually the biggest cost component. Sailing costs consists of three sub components as shown in Figure 32. Sailing costs can vary significant per shipment since these costs are influenced by the ability of the shipping company to find additional cargo. Finding more cargo for similar shipments increases the utilization of the ship which greatly reduces the shipment costs per cargo.
Cost Components Sub Cost Components Cost Drivers Relevant rates
Travelling costs Ship Utilization Sea rate Sailing Canal costs ship Ship size Canal costs cargo Cargo size on deck
Figure 32: Overview of sailing costs
The Sea Rate (SR) is the same as described before in Chapter 7.1.2 Sea Rate. The other components will be discussed next.
7.3.1. Travelling costs The Travelling costs stands for the costs needed to sail from POL to the POD. It depends on the travel time (TT), the ship utilization and the Sea rate. The distance in nautical mile (d) divided by the ships speed in knots (kn) gives the traveling time:
푑 푇푇 = (18) 푘푛
7.3.2. Ship utilization The ship utilization (SU) is a factor that impacts the sailing costs charged to customers. The SR is multiplied with the TT and with the SU. The charged costs are dependent on the utilization of the cargo
36 ship. The higher the shipping company perceives their chance to find additional cargo the lower the costs per customer will be. Adding flexibility days increases these chances. In the model this works as follows.
The ship utilization by customer cargo (SUBC) divided by the utilization for the specific trip (TU) gives the percentage of the total charged costs to the customer (PTCC).
푆푈퐵퐶 푃푇퐶퐶 = (19) 푇푈
The SUBC is determined by dividing the cargo length (CL) by the deck length (DL) of the cargo vessel.
퐶퐿 푆푈퐵퐶 = (20) 퐷퐿
The distribution of the TU is set as a uniform random distribution where the minimum is the SUBC and the maximum is 푀푈 as described in formula 18. This maximum is dependent on the capability of the shipping company to find additional cargo. In turn, this is dependent on the route of the ship and on the flexibility offered to the shipping company. More days for a shipping company to be flexible means higher chances of finding cargo for similar routes. Zero days of flexibility means no additional cargo can be loaded and the TU is the same as the SUBC. I.e. all route costs will be for the account of the customer. Per day of flexibility this probability increases. The speed of this increase is dependent on the route between the POL and POD and the cargo size already on board. Routes on which there is more cargo increase faster than routes on which there is less cargo. Ships that are already close to fully loaded increase less fast then ships that still have plenty of available room. The maximum of the uniform distribution (MU) per ship 𝑖 increases with a value determined with the following calculation.
푟 푀푈(𝑖) = 푆푈퐵퐶(𝑖) + ((푇푈푚푎푥 − 푆푈퐵퐶(𝑖))/푓)) ∗ 푓푠 (21)
푟 Where 푇푈푚푎푥 is the maximum utilization for the route, variable 푓 is the amount of sailing days divided by 0.6 to account for the amount of distance covered for the heavy lift ship, 푓푠 stands for the amount of offered flexibility divided by 2 to account for the flexibility offered during the transit. The variable 푟 푇푈푚푎푥 stands for the maximum utilization level that can be obtained by shipping companies for the route. This value is 0.7 for routes on major trade lanes. Even for routes on major trade lanes it is highly unlikely ships can utilize their cargo space for 100% of the time for the entire trip. Other routes increase with a lower value and have a lower maximum dependent on the route which is specified manually per route.
To determine the ship utilization by customer cargo the deck length of the heavy lift ship needs to be known. This is not known for all ships. With regression analysis an attempt is made to find a relation between the deadweight and the deck length of heavy lift ships. This analysis is performed over 95 ships of five different shipping companies.
Figure 33 shows the deck length of 95 ships from 5 different shipping companies. Appendix N shows the residuals for the for the found linear relationship between deck length and DWT. Table 34 and Table 35 show the model summary and the F-test value.
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Deck length heavy lift ships 200
150
100 Sample
Deck length 50 Predicted deck length 0 5000 10000 15000 20000 Deadweight
Figure 33: Deck length of heavy lift ships
A regression coefficient 푅2 of 0.65 for linear function 푦 = 0.0051 ∗ 퐷푊푇 + 53.803 with a p-value for the F-test of < 0.0001 and a nicely distributed residuals graph implies a good fit. This linear function will be used to determine the deck length of all heavy lift ships.
퐷퐿 = 0.0051 ∗ 퐷푊푇 + 53.803 (22)
7.3.3. Canal costs ship Canal costs are charged at the Suez Canal and the Panama Canal. Canal costs are charged for cargo vessels that make use of the canal. Suez also charges floating cargo on deck. This will be discussed afterwards.
Canal costs at Suez are charged by the Suez Canal authority and are based on a rate per Suez Canal Net Tonnage. This SCNT is a measurement intended to represent the revenue-earning capacity of a vessel but is not directly comparable with normal cargo capacity. The SCNT is calculated by a classification society or by an official trade organization which offers a Suez Canal Special Tonnage Certificate. The SCNT is usually not published by shipping companies. If a ship does not have a SCNT the Suez Canal toll is issued over the sum of the Gross - and the Net Tonnage divided by 2 and adding 10% (Stopford, 2009). Another way to approximate the SCNT is to divide the deadweight by two (Leth Agencies, 2016). The outcome of these methods differ significantly. Also, the interview with the Commercial Manager of BigLift provided other information. Therefore another approach is needed. In this study the SCNT and DWT of the 18 heavy lift ships of shipping company SAL are used for linear regression analysis. SAL is the only heavy lift shipping company that published their SCNT. After removing two outliers a strong linear relation is founded with a R2 of 0.98. The two removed outliers are ships that are also equipped for container transportation as well as dry cargo. This makes that the SCNT of these vessels cannot be used to represent the SCNT of other ‘normal’ heavy lift ships. The model summary is shown in Appendix O. The value of this relation to represent the whole heavy lift fleet can be discussed. However, it is the only information that is publically available. Therefore this relation will be used to estimate the SCNT of other heavy lift ships.
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From a certain point at lower DWT values this approximation becomes unrealistic. The method provided by Leth Agencies gives a better representation for the SCNT for these smaller ships. From a DWT of 8,100 the DWT is divided by two to approximate this value. This gives
푆퐶푁푇 = 2.3096 ∗ 퐷푊푇 − 14,658 푓표푟 퐷푊푇 > 8,100 (23) 푆퐶푁푇 = 퐷푊푇/2 푓표푟 퐷푊푇 < 8,100
The Suez Canal costs are then calculated with a SDR per SCNT rate. The value of the SDR is a weighted average expressed in USD over a basket of the following five major currencies, the US dollar, Euro, Chinese renminbi, Japanese yen and Pound sterling. This is done to avoid losses due to fluctuations in exchange rates. Suez canal toll charges for general cargo ships are shown in Table 8 (Suez Canal, 2016). The USD/SDR exchange rate used in this study is 1.41.
Table 8: Suez Canal toll charges
Suez Canal Toll SCNT Canal tolls Canal tolls per SCNT (in SDR) per SCNT (in USD) first 5,000 7.88 5.59 next 5,000 6.08 4.31 next 10,000 4.24 3.01 next 20.000 3.18 2.26 next 30,000 3.08 2.18 next 50,000 3.03 2.15
Now the Panama Canal costs will be discussed. A similar method is used to determine Panama canal tolls as at the Suez Canal. Except the rates differ, the currency is the USD and the rate is calculated over the Panama Canal Universal Measurement System (PC/UMS) instead of the SCNT. To determine the PC/UMS, the classification society applies a mathematical formula for the measurement of total ship volume. A PC/UMS ton is equivalent to 100 cubic feet of volumetric capacity. Since the PC/UMS is not public information, again a regression analysis over 18 ships of SAL with ordinary least squares is performed to be able to estimate the PC/UMS for all heavy lift ships. After removing the same two outliers a strong linear relation is found with a R2 of 0.95 for the sample as shown in Appendix O.
This gives the linear relation of z = 1.3788 ∗ DWT − 5,266. Again this gives unrealistic values for smaller ships. The same method is used as at the Suez Canal calculation. The intersection between z and DWT/2 is at 5,992.
푃퐶/푈푀푆 = 1.3788 ∗ 퐷푊푇 − 5,266 푓표푟 퐷푊푇 > 5,992 (24) 푃퐶/푈푀푆 = 퐷푊푇/2 푓표푟 퐷푊푇 < 5,992
Table 9 shows the Panama Canal toll charges in USD (Panama Canal, 2016).
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Table 9: Panama Canal toll charges
Panama Canal Toll Panama canal Canal tolls net tonnage per PCNT (in USD) first 10,000 5.10 next 10,000 4.99 rest > 20,000 4.91
Depending on the canal passage the canal costs for the ship charged to the customer (CCSC) can be determined by multiplying the total canal costs with the costs charged to the customer PTCC.
7.3.4. Canal costs cargo At the Suez Canal costs can be charged for shipping floating cargo (CCC). Based on the overhang or cargo that limits the captain’s sight compulsory tugs are needed. The exact pricing methods are unclear and prices vary significantly from time to time even for the same cargo. In the calculation 1,000 USD per meter cargo length is used.
퐶퐶퐶 = 퐶퐿 ∗ 1,000 (25)
The overall Sailing costs can be determined by multiplying the Sea Rate with the Travelling Time and the Utilization level charged to the customer. Add the Canal costs for the cargo and the Canal costs for the ship with the utilization during canal transit taken into account.
푆퐶 = 푆푅 ∗ 푇푇 ∗ 푃푇퐶퐶 + 퐶퐶 + 퐶퐶푆퐶 (26)
This concludes the Sailing cost component. The next cost component that will be described are the unloading costs.
7.4. Unloading costs Unloading costs are calculated in the same way as loading costs except the unloading time per ship instead of the loading time per ship is set. This is usually half of the loading time. All other values of the parameters stay the same.
7.5. Demobilization costs Demobilization costs are charged to the shipper for the costs made by the shipping company to sail from the desired POD to the next location where it is likely to find cargo. Port of Discharges on major trade lanes or in the neighborhood where it is likely to find new cargo are charged less then exotic locations where ships have a high probability to sail a long distance to find new cargo. This is captured in the model by manually filling in the mobilization days dependent on the POD. This seems inconsistent since the mobilizing costs got a very extensive description. The difference is that the mobilizing costs were about the costs sailing directly to a specified POL. At the moment of booking the demobilizing route is most likely not known yet since other customers have not booked the shipping company at that moment in time. The practical method used by the shipping companies to protect themselves for losses made for the demobilization is to estimate the costs needed to sail to a next loading and/or unloading
40 location. Dependent on the strategy of the shipping company the incorporated costs in the offer is half of the total costs towards the next loading location and the other half is accounted for in the price offered for the next customer.
7.6. Summary of the heavy lift cost model. This concludes the explanation of each major cost component. Per offer for a shipment the shipping company uses expectations for each parameter to set a price. This means that more expensive ships can offer the lowest price if they are close by to the POL at the moment of loading and they have a high ship utilization. The USD to Euro exchange rate used is set as 1: 0.90. Simulation is used as method to determine outcomes for certain scenarios.
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8. Simulation The situation described above is analyzed with use of simulation. MATLAB is used as the simulation software. MATLAB or MATrix LABoratory is a technical software program that is used for all kind of mathematic applications. In this thesis MATLAB is used for manipulating matrices, statistics and drawing graphs.
8.1. Input Parameters The costs for three different ships are simulated to illustrate the differences in pricing for the different ship sizes. Different flexibility windows are simulated to determine the value of offered flexibility per ship weight. Four different routes will be analyzed. Most heavy ships are produced in Vietnam. The most common routes with a distribution of destinations worldwide will be analyzed. These routes are Ha Long Bay (Vietnam) - Rotterdam (The Netherlands), Ha Long Bay - Vera Cruz (Mexico), Ha Long Bay – Lagos (Nigeria) and Ha Long Bay - Sharjah (United Arab Emirates). The route characteristics shown in Table 10 is used as input in MATLAB.
Table 10: Route characteristics
Destination Rotterdam Vera Cruz Lagos Sharjah Distance 9,610 11,292 9,352 4,744 Minimum Mobilization time (in days) 1 1 1 1 Demobilization time (in days) 0 1.5 1.5 1 Suez Canal passage Yes No No No Panama Canal passage No Yes No No r TUmax 0.7 0.578 0.5 0.6
Besides the route characteristics also the ship characteristics is used as an input parameter in the model. The Cargo characteristics per ship are given in Table 11:
Table 11: Cargo characteristics
Ship type ASD2411 ASD3212 ASD3412ICE Ship weight in ton 400 650 750 Ship length in meter 24 32 34 Loading days 2 3 3 Unloading days 1 1 1
Table 12 shows different scenarios that represent different amount of flexibility days per shipment.
Table 12: Scenarios with different flexibility days
Number of flexibility days Destination 1 28 56 84 112 Rotterdam Vera Cruz Lagos Sharjah
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The simulation model works as follows and as visualized in Figure 34. The route characteristics, cargo characteristics and a certain amount of flexibility days per shipment are used as input for the model. The cost elements and ship characteristics for all heavy lift ships as described in the chapters above are used as a database. The top segment of the heavy lift shipping industry is shown in Appendix P. The cost calculation will be performed for the ships that can carry the cargo, all other ships will be discarded. Then the simulation model determines the costs individually per ship for the different cost components and stores the costs per subject per ship. A loop is added for the next heavy lift ship 𝑖 + 1. This continues until all heavy lift ships that have enough SWL are simulated. Another loop is added so multiple simulation runs can be executed. After that the total costs are sorted from low costs to high costs to get a better overview of the costs for each heavy lift ship. Appendix Q shows how this looks in MATLAB.
Input Simulation Results
Route characteristics: - Destination Input Sort data - Distance - Minimum Mobilization time Discard ships with - Demobilization time not enough SWL Create overviews & - Suez Canal passage (yes/no) graphs Specify the - Panama Canal passage (yes/no) database values to - Max Utilization level variables for ship i Interpret the data and simulation run j Cargo characteristics: - Ship type Computations for - Ship weight ship i No Analyze the results End Start - Ship lenght Loop for i+1 - Loading days Store outcome for - Unloading days ship i Interpret the - Flexibility days outcome All ships computed? Heavy lift fleet database: No - Lifting capacity Yes Loop for j+1 - Sea rate - Berth rate Store data - Daily port costs - Ship size All simulation runs - One-off Port costs executed? - etc. Yes
Store data
Figure 34: Visualization of simulation model
To check if the model works as intended validation and verification steps must be applied. The next section describes these control actions.
8.2. Validation and verification To check if the model works how its intended we need to use verification and validation. Verification means that that we check if the operational and computation model are logically and semantically consistent with the conceptual model. Next to that the syntax of the model need to be checked and sensitivity analysis can be performed to check for variables that have a big impact on the output values.
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Validation of a model makes sure that the outputs of the model are close enough to empirical data to answer the research question.
The way this model is set up limits the input variables as much as possible to lower chances for mistakes. The same database as shown in is used for each new simulation. In the design of the model each new calculation or step is checked by using easy to handle numbers and manual calculations are performed to check if the step works as intended. Furthermore a loop is used to lower the possibility for input errors even more. Each loop or iteration follows the same steps. The costs are calculated by following the same division of costs as the conceptual model. In total only 11 input parameters need to be inserted. These input parameters are all bound to cargo and route specifications.
To validate the model the received prices of two real life cases are shown in Table 13 below with unknown flexibility days. This shows whether or not the prices calculated by the model represent real life figures received from the shipping companies. Table 13 shows the prices received from four different shipping companies listed vertically. The prices were requested for shipping 1, 2 or 3 ASD2411’s simultaneously. No exact time window was given during for the request for quotation. In these cases one can assume a timeframe between 4 and 8 weeks.
Table 13: Real life route costs ASD2411 Vietnam – Mexico
ASD2411 From Vietnam to Vera Cruz, Mexico Number of ships to be transported 1 2 3 Shipping Company 1 € 985.000 € 1.200.000 € 1.350.000 2 € 745.000 € 765.000 € 785.000 3 € 395.000 € 650.000 € 795.000 4 € 400.000 € 700.000 € 950.000
A copy of Table 17 is shown in Table 14 that gives the results of the simulation.
Table 14: Simulation results with only ASD2411 Vietnam - Mexico
ASD2411 Number of flexibility days Destination 1 28 56 84 112 Vera Cruz € 637.160 € 524.040 € 442.810 € 387.130 € 346.940
Of the above shown costs I would like to highlight two items. The first item is the big amount of price difference received from shipping companies. The second item is that the simulation has the same order size and does approximately represent real life figures.
Table 15 shows the prices received from six different shipping companies to transport 1,2 or 3 ASD2411’s from Vietnam to Rotterdam. If n/a is given this means no prices for that transportation were received. Table 16 shows the simulation results for the route for one ship.
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Table 15: Real life route costs ASD 2411 Vietnam - Rotterdam
ASD2411 From Vietnam to Rotterdam Number of ships to be transported 1 2 3 Shipping Company 1 € 545.000 € 650.000 € 850.000 2 n/a € 695.000 € 1.250.000 3 n/a € 700.000 n/a 4 € 585.000 € 795.000 € 1.125.000 5 n/a € 850.000 € 1.450.000 6 € 695.000 € 895.000 n/a
Table 16: Simulation results with only ASD2411 Vietnam - Rotterdam
ASD2411 Number of flexibility days Destination 1 28 56 84 112 Rotterdam € 579.900 € 431.070 € 348.110 € 298.710 € 282.840
Again can be seen that the prices received from shipping companies represent values similar to the costs determined by the model. Besides that the diversity in received prices of shipping companies is again large. The above given examples show that there is no reason to assume the model is incorrect and that the costs calculated by the model gives a good approximation of real life values.
8.3. Results and analysis of simulation This section shows the results of the simulation for each specified cargo ship and route. The result shows the costs for each shipment for one simulation run. The lowest value of the simulation is equal to the lowest cost for a shipment. Interesting to see is the cost structure per shipment, the variance in costs and the minimum costs for each shipment.
The cost structure per shipment is illustrated with the use of Figure 35 and Figure 36. Figure 35 shows the cost structure for one simulation run of the ASD3412ICE for the route Ha Long – Vera Cruz with 28 days of flexibility. The x-axis shows the number of heavy lift ships that are able to lift the cargo, in this case there are 32 ships. The y-axis shows the costs in Euro. The costs are already sorted from low to high. The dark blue bars show the mobilization costs, the blue bars show the loading costs, the aqua colored bars show the sea voyage costs, the green bars show the canal passage costs, the orange bars show the unloading costs and the yellow bars show the demobilization costs. The red crosses show the utilization rates for each specific ship which can be read in the y-axis on the right.
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Figure 35: Cost structure of shipment of ASD3412ICE
Figure 36 shows the cost structure for the same route but for the ASD2411. In this case there are 171 heavy lift ships that can carry the cargo.
Figure 36: Cost structure of shipment ASD2411
When these simulations would be done again the results would change. This is due to the high stochasticity in the mobilization as well as the sea voyage costs. Because of this high stochasticity the minimum costs for a shipping company is subject to change from one time to the next. Figure 37 illustrates the change in the minimum costs for shipping companies for 100 simulation runs. Each cross represents the costs for that specific simulation. This is for the same route and ship as Figure 36.
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Figure 37: Minimum costs per simulation run ASD2411
This same representation for the heavier ASD3412ICE is shown in Figure 38. Here the difference in the minimum costs for a shipping company is greater. This is due to the fact there are less ships available that can perform the operation.
Figure 38: Minimum costs per simulation run ASD3412ICE
Comparing more costs and the variance of costs by using these graphs is difficult to comprehend and not easy to follow. Boxplot graphs are easier to follow and give a clearer overview. Figure 39 shows such a boxplot. The red line is the median, the blue cross is the average, 50% of the values are inside the rectangle box. So 25% of the values are below the lowest line of this box and 75% of the values are below the upper line of this box. The whiskers represent the highest and lowest values that are not outliers, i.e. values with more than -2.698 or 2.698 standard deviation. These whiskers cover 99.3% of the data.
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Figure 39: Boxplot of minimum costs for 100 simulation runs ASD3212ICE Now that the cost structure for different shipments is elaborated and the variation in costs for different simulation runs is explained the average minimum costs for the different scenarios are shown in Table 17, Table 18 and Table 19.
Table 17: Average minimum costs for ASD2411 for different destinations and flexibility days
ASD2411 Number of flexibility days Destination 1 28 56 84 112 Rotterdam € 579.900 € 431.070 € 348.110 € 298.710 € 282.840 Vera Cruz € 637.160 € 524.040 € 442.810 € 387.130 € 346.940 Lagos € 528.190 € 437.970 € 377.500 € 333.200 € 322.250 Sharjah € 310.090 € 220.200 € 190.240 € 188.400 € 188.300
Table 18: Average minimum costs for ASD3212 for different destinations and flexibility days
ASD3212 Number of flexibility days Destination 1 28 56 84 112 Rotterdam € 703.440 € 576.030 € 483.860 € 421.260 € 400.960 Vera Cruz € 765.190 € 649.720 € 578.270 € 515.110 € 471.180 Lagos € 636.630 € 548.150 € 494.740 € 450.460 € 435.630 Sharjah € 385.600 € 294.940 € 257.170 € 253.970 € 251.820
Table 19: Average minimum costs for ASD3412ICE for different destinations and flexibility days
ASD3412ICE Number of flexibility days Destination 1 28 56 84 112 Rotterdam € 780.730 € 627.220 € 529.560 € 463.090 € 437.730 Vera Cruz € 828.650 € 717.250 € 636.490 € 569.730 € 520.710 Lagos € 677.360 € 597.160 € 539.690 € 491.830 € 476.500 Sharjah € 422.380 € 320.470 € 277.650 € 274.170 € 271.590
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The increase in flexibility lowers the minimum costs in two ways. First the mobilization costs are decreased for more ships. Which makes it more likely that a cheaper ship sails by the POL. Besides that there is also more opportunity for the shipping company to find additional cargo which lowers the costs per cargo. Caution must be applied when interpreting these results. As already mentioned before there is a lot of variation in the minimum per simulation run. To show the variation for different amount of flexibility days Figure 40 and Figure 41 are added. Here the boxplots per amount of flexibility days (in weeks) is shown for an ASD3212 from Vietnam to Rotterdam and a ASD3212ICE from Vietnam to Sharjah.
Figure 40: Boxplot for different flexibility days ASD3212 Figure 41: Boxplot for different flexibility days ASD3212ICE Vietnam-Rotterdam Vietnam - Sharjah
Besides the variation in the minimum costs for a shipping company there is another reason why caution must be exercised. These values represent the minimum costs for the total fleet. So it gives the cost value of the ship that was in a very good position at the loading interval and found a large proportion of additional cargo. It is likely that shipping companies know when they are in a very low cost position compared to their competitors. Especially in the top segment of the heavy lift industry where there are only a few competitors this becomes important. Therefore the offer send to the shipper is most likely higher than their own cost price. There is a simple way to make sure that you always sail with a high proportion of additional cargo. This can be done when a shipper provided the additional cargo themselves. If that is the case the biggest proportion of costs such as the sea voyage costs can be distributed over multiple cargo. Also the mobilization and demobilization as well as the canal costs can be distributed. The loading and unloading costs do get higher but this does not come close to the lowered costs per ship for the other subjects.
For managerial insights and to help decision making by management it is helpful to know the average costs savings for offering more flexibility. The average decrease in the costs is more related to the route then to the ship characteristics. The average costs savings compared to one day of offered flexibility are
49 shown in Table 20. Table 21 shows the relative costs for different flexibility days compared to one offered flexibility day.
Table 20: Cost savings compared to one offered flexibility day
Flexibility days 28 56 84 112 Rotterdam € 143.250 € 234.180 € 293.670 € 314.180 Vera Cruz € 113.330 € 191.143 € 253.010 € 297.390 Lagos € 86.300 € 143.417 € 188.897 € 202.600 Sharjah € 94.153 € 131.003 € 133.843 € 135.453
Table 21: Relative costs compared to one offered flexibility day
Flexibility days 28 56 84 112 Rotterdam 79% 66% 57% 54% Vera Cruz 85% 74% 66% 60% Lagos 86% 77% 69% 67% Sharjah 75% 65% 64% 64%
These costs savings are a combined average results for the three fore mentioned ships, the ASD2411, ASD3212 and ASD3212ICE from origin Vietnam. Table 17, Table 18 and Table 19 show detailed results. This concludes the simulation and results part. The next chapter discusses how these results can contribute to lower logistics costs for the transportation of complete vessels.
9. Conclusion In this section all conclusions and recommendations from this thesis are shown. Section 9.1 answers the main research question together with the three sub research questions. Besides that also other findings that are important but not addressed by the research questions are presented. After that section 9.2 will give the recommendations how these findings can be turned into an advantage for Damen. Finally limitations of this study and suggestions for further research are given in section 9.3
9.1. Research conclusion The first sub question: ‘What are the current processes in the delivery of complete vessels, what types of activities and factors influence cost and delivery performance and how is current performance measured?’ is answered in Chapters 4, 5 and 6. Chapters 5 and 6 are devoted to the market situations. This is by far the most important factor that influences costs and delivery performance. Factors such as the position within a trade network, trade imbalances, complementarity of trade, competition, liner services, connectivity, distance but also the volume or weight of the shipped product are all influencers of costs for maritime shipping. In this thesis we showed that the weight of the heavy lift cargo has a significant impact on the amount of competition and on the minimum cost price per shipment. It is in this very heavy lift markets that combining transports can have significant advantages. Maybe due to the different cargo types, ports of loading, ports of unloading, offered flexibility and the high variation in prices received from shipping companies there are no performance measured stated. The deliveries
50 department tries to find the best option in time window and price for a transportation and makes sure the loading operations go as smooth as possible with the least amount of time and paint damage. The processes are described in Chapter 4. One process that is unclear in the organization and that can significantly lower the transportation costs and increase sales is the process that describes how the different Product Groups, Sales and the Deliveries department should work in making smart choices in combination transportations. No structural information sharing process between the Deliveries department and the different Product Group exists and Sales is unaware of most future transportations which means this information cannot be used in the negotiations with the customers. Combinations are being set up nevertheless, this can be initiated by three different departments. Sales initiates a combination delivery when multiple ships are sold for a similar route for the same Customer. Sometimes a combination is initiated by a Product Group when multiple similar ships are on stock on the same location and sometimes the Deliveries department see multiple shipments coming together and try to make a combination possible.
The second sub question: ‘What is the value of offered flexibility by customers and what factors influence this value? ‘ is answered in Chapters 7 and 8. Here also the cost structure and cost subjects are described and evaluated. Offering more flexibility is definitely of great value to receive low prices from the shipping companies due to a couple of reasons that are listed below.
- More chance finding a ship close by the port of loading. - More chance finding a more cost efficient ship close by the port of loading. - More chance for the shipping company to find additional cargo - More competition for shipping companies
The value of offered flexibility is more dependent on route then cargo specifications. On average the savings are as listed in Table 22 and Table 23.
Table 22: Cost savings compared to one offered flexibility day
Flexibility days 28 56 84 112 Rotterdam € 143.250 € 234.180 € 293.670 € 314.180 Vera Cruz € 113.330 € 191.143 € 253.010 € 297.390 Lagos € 86.300 € 143.417 € 188.897 € 202.600 Sharjah € 94.153 € 131.003 € 133.843 € 135.453
Table 23: Relative costs compared to one offered flexibility day
Flexibility days 28 56 84 112 Rotterdam 79% 66% 57% 54% Vera Cruz 85% 74% 66% 60% Lagos 86% 77% 69% 67% Sharjah 75% 65% 64% 64%
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Figure 42: Boxplot for different flexibility days ASD3212 Figure 43: Boxplot for different flexibility days ASD3212ICE Vietnam-Rotterdam Vietnam - Sharjah
Figure 42 and Figure 43 show the variation in minimum costs for the shipping company. These boxplots show that there can be significant changes in costs for shipping companies from one time to the next. This should be taken into account when interpreting the values in Table 22 and Table 23.
Besides the external advantages having more flexibility to execute a shipment also increases the possibility to find combinations internally. Offering more flexibility does not always mean that shipments will be performed later. It does mean that shipping companies will understand there is more competition for the cargo and will most likely use a pricing strategy accordingly. For the reasons mentioned above it seems wise to always offer a wide range in flexibility. The Deliveries department usually does offer a wide indication for a time of shipment to the shipping companies. This is most of the time a combination of the factors above but also due to uncertainties in the completion date of the ship and uncertainties in receiving a green light from Sales due to payment issues from customers. Determining the exact value of offered flexibility is difficult since estimations have to be made about the increase in cargo room utilization values for each ship with each increase in flexibility. Data analysis of earlier transportations could help improve the estimations. Unfortunately due to the way data about costs and all other relevant information data analyses cannot be performed accurately.
The third and final sub research question formulated is: ‘What processes need to be redesigned to go to a longer-term planning and what would be the consequences on the flexibility towards the customer?’. This research question was formulated with the underlying assumption that current short to mid- term planning is not cost efficient. After discussing this with the two biggest Dutch heavy lift shipping companies BigLift and Jumbo Maritime and studying the prices received from shipping companies the conclusion can be made that going to a longer term planning is not to be recommended. This is due to the following reasons. Shipping companies do not know themselves where their ships will be in a period further away than approximately three months from now. Also the amount of other cargo that can be
52 found for a similar route is difficult to estimate. This makes that shipping companies indicate prices with a lot of safety margin. Jumbo Maritime and BigLift also explained that there have been efforts in the past with other customers to set up such a longer term commitment for multiple shipments but these efforts stranded quite soon due to practical and cost issues. We have shown in Chapter 8 how the costs for shipping companies vary significantly from one time to the next. Therefore it is very unlikely that having a long term relationship with only one shipping company is cost efficient. When shipping companies are booked first the cargo of the shipper becomes base cargo. Cargo that is booked later becomes additional cargo or spot cargo. These spot cargo is cargo that is going with a ship that already covered all or most of its costs for a journey. This makes that spot cargo usually does not account for much more costs for the shipping company which can make the price offered to the shipper a low one. The downside is that it can be risky to always wait for the spot market option. Ships can be fully booked or be booked for other destinations which makes this option disappear. It is always a trade-off between waiting longer for booking the best spot option price and taking a lot of risk or booking earlier with less risk. The above story is backed up by the prices received from shipping companies. Where in the offer phase, i.e. 5-4 months before the time of shipment, indications are made based on rough estimations the closer one gets to the time of shipment the better estimations the shipping companies will have. Some ships will have found less cargo, most shipping companies will have found cargo close to their estimations and some will have found more cargo. Shipping companies that found less cargo will not raise their initial indication but ships that have found more cargo than earlier anticipated can take the spot cargo for a low costs. After negotiations between the deliveries department and the different shipping companies this is reflected by a new offer with a lower price. For the reasons mentioned above spot cargo transportations is ideal for stock transportations.
The main research question of this thesis is: ‘How can maritime heavy lift transportations for complete vessels be designed in an efficient way and what are the impacts on costs and delivery performance?’
The description at the three research sub questions all indicate how maritime heavy lift transportation for complete vessels should be designed in an efficient way. A brief summary is that it should be designed in a way where the decision makers, in this case Sales and the different Product Groups are aware of the value of offered flexibility. Due to the high complexity that arises from the fact that there are different Sales Areas, Product Groups, cargo weights, delivery deadlines and geographical distances information sharing is a major component for an organization to optimally use the market and lower the total logistic costs. This organization wide information sharing system is not present at this time. Both raising the awareness of the value of offered flexibility and creating a information sharing system will not impact the delivery performance. The impact of having a information sharing system on costs is not studied in this thesis. The impact of flexibility is discussed in Chapter 8.
9.2. Recommendations To improve the chances for cost efficient stock transportations and to help Sales in their negotiations there should be a fast and efficient information sharing system. For stock transportations the Product Groups should be in the lead guided by forecasts provided by Sales. Even if the Product Group cannot combine transportations within their own group the information should still always be shared with the Deliveries department. A good option can be to make an information sharing platform that can be
53 accessed by everyone that needs access. These are at least Sales, Product Groups and the Deliveries department. Since Damen transports over 100 ships each year it is recommended that this information sharing platform is easy to understand. Therefore it is recommended that a graphical presentation as well as a list is shown in which more detailed information is available. In this list all necessary information is provided by the different departments. The Product Groups show their current stock levels and the planned delivery dates and show which ships are an option to be transported for stock keeping purposes. They also give an indication for which price the stock may be transported. The Deliveries department inputs the shipments that are planned and the shipments that are booked with information such as time of shipment and ship route. The Sales department’s forecast can be inserted in this overview. This can help the Product Groups to make better stock transportation decision. Sales can also see all current booked and planned transportations and can take this information into consideration when negotiating with customers. To go one step further heavy lift shipping companies can be invited as well. The shipping companies can see all stock vessels that can be transported for a certain price. Since stock transportations are for similar routes for a longer period the heavy lift shipping companies can take a look at the stock transportations preferred by Damen if the shipping company already has a good route from a stock position to another stock position.
Figure 44 shows an example. The yellow lines represent transportations that are booked and the orange lines represent transportations that are in the planning. The numbers in the light blue globes represent the number of ships on different locations. When zooming in on each globe more information of the ships and the exact location becomes visible.
Figure 44: Graphical overview of information sharing system
Currently a lot of information provided by shipping companies with regard to price is not easy to find. It is recommended that all offers from shipping companies are stored in a database that can be used for future statistical computations on prices. This new to be formed database can be implemented together with the information sharing system.
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9.3. Limitations and further research There are several limitations in this research. The limited amount of literature on maritime heavy lift shipping and the information provided by shipping companies makes that a lot of estimations have been made in determining the different costs for each heavy lift ship. Although these estimations were done with utmost care and are validated as much as possible there are most likely some important deviations in costs for some heavy lift ships. Another important limitation is that the utilization levels for different routes in the simulation model is difficult to estimate. The utilization level is an important factor in total the costs of a transportation.
For a shipping company further research can go into a direction of keeping track and mapping al heavy lift transportations. This can help to make estimations on predicted utilization levels more accurate. For Damen further research can go into the direction of integrating the suppliers directly in the process for stock transportations to try to find an answer if heavy lift shipping companies are interested and what type of information should be available. Other research can be about which geographical locations are interesting for Damen for stock keeping purposes. One could think of a place nearby Nigeria and a place in the Caribbean. Which vessels can be kept on stock for what costs? Is a question that can be answered in this research.
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10. Bibliography Angeloudis, P., Bichou, K., Bell, M. & Fisk, D., 2006. Security and reliability of the liner container shipping network: Analysis of robustness using a complex network framework, Melbourne. 12–14 July: Presented at the International Association of Maritime Economists conference.
Baltic Dirty Tanker Index, 2015. charter rates for crude oil tankers on selected routes, London: Baltic Exchange .
BBC-Chartering, 2016. www.bbc-chartering.com. [Online] Available at: https://www.bbc-chartering.com/uploads/tx_bbcfleetlist/BBC_Everest_type%20- %20dwt%209282.pdf?ts=1476877518 [Accessed 10 April 2016].
Clarksons Research, 2015a. Dry Bulk Trade Outlook. 21(1), UNCTAD: United Nations Publications.
Clarksons Research, 2015b. Seaborne Trade Monitor. 2(6) June, UNCTAD: United Nations Publications.
Clean North Sea Shipping, 2014. www.cnss.no. [Online] Available at: http://cnss.nl/wp-content/uploads/2014/06/fuel-consumption-web.pdf [Accessed 6 April 2016].
Corbett, J. & Koehler, H., 2003. Updated emissions from ocean shipping. Journal of Geophysical Research, 108(20).
Damen, 2015. www.Damen.com. [Online] Available at: http://www.damen.com/about/a-family-history [Accessed 15 December 2015].
Drewry, 2006. Drewry Ship Management. [Online] [Accessed June 2016].
Duizer, G., 2016. Design and Proposal Engineer [Interview] (10 April 2016).
Endersen, O. et al., 2003. Emission from international sea transportation and environmental impact. Journal of Geophysical Research, 108(D17), p. 108.
Energeo Politics, 2015. Energeo Politics. [Online] Available at: https://energeopolitics.com [Accessed 14 April 2016].
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Kumar, S., 2010. Logistics routing flexibility and lower freight costs through use of incoterms, London: Transportation Journal, 48-56.
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Kumar, S. & Hoffmann, J., 2002. Globalization: The maritime nexus. In: CT Grammenos Handbook of Maritime Economics and Business, London: Lloyds List Press..
Leeuwen, P. v., 2016. Service Delivery Coordinator Damen [Interview] (26 May 2016).
Leth Agencies, 2016. www.lethagencies.com. [Online] Available at: http://lethagencies.com/calculator-guidelines [Accessed 10 May 2016].
Marquez-Ramos, L., Martinez-Zarzoso, I., Perez-Garcia, E. & Wilsmeier, G., 2005. Determinants of Maritime Transport Costs. Importance of Connectivity Measures., Le Havre 28-29 September: Presented at the International Trade and Logistics,Corporate Strategies and the Global Economy Congress.
McCalla, R., Slack, B. & Corntois, C., 2005. The Caribbean basin: Adjusting to global trends in containerization., 32(3):245–261: Maritime Policy and Management.
Mitroff, I., Betz, F., Pondy, L. & Sagasti, F., 1974. On Managing science in the systems age: two schemas for the study of science as a whole systems phenomenon. Interfaces, 3(4), pp. 46-58.
Moore Stephens, 2014. Ship operating costs: Current and future trends. [Online] Available at: https://opcost.moorestephens.org/ [Accessed 20 5 2016].
National University of Singapore, 2008. Heavy-Lift transport ships. Singapore, Marine Operations Specialty Symposium 2008.
Nijhuis, R., 2016. Regional Commercial Manager Jumbo Maritime [Interview] (10 March 2016).
Notteboom, T. & Carriou, P., 2009. Fuel surcharge practices of container shipping lines: Is it about cost recovery or revenue making?. Copenhagen, International Association of Maritime Economists (IAME).
Nugteren, R., 2016. General Manager Cargo Vessels Damen [Interview] (8 04 2016).
OECD, 2008. Clarifying trade costs in maritime transport, s.l.: OECD, TAD/TC/WP(2008)10, Paris, April 2008.
Panama Canal, 2016. www.pancanal. [Online] Available at: http://www.pancanal.com/eng/op/tolls.html [Accessed 02 June 2016].
Port of Rotterdam Authority, 2016. www.portofrotterdam.com. [Online] Available at: https://www.portofrotterdam.com/nl/scheepvaart/havengelden/zeehavengeld [Accessed 03 April 2016].
Sanchez, R. et al., 2003. Port efficiency and international trade: Port efficiency as a determinant of maritime transport costs, Published online: Maritime Economics & Logistics, 5, 199–218.
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Smits, L. L., 2016. Improving deliveries by smart use of the Maritime Heavy Lift Transportation Industry, Eindhoven: Technical University of Eindhoven.
Stopford, M., 2009. Maritime Economics. 3th ed. London: Routledge.
Suez Canal, 2016. Suez Canal Toll Circulars. [Online] Available at: http://www.suezcanal.gov.eg/TollCirculars.aspx [Accessed 15 June 2016].
Toepfers, 2016. Multipurpose shipping report, Hamburg: Toepfers.
United Nations Conference on Trade and Development, 2015. Review of maritime transport, Geneva: United Nations Publication.
United States Environmental Protection Agency, 2000. Analysis of Commercial Marine Vessels Emissions and Fuel Consumption Data, Washington: BiblioGov.
Wilmsmeier, G., 2014. International Maritime Transport Costs: Market Structures and Network Configurations. United Kingdom: Ashgate Publishing Ltd.
Wilmsmeier, G. & Hoffmann, J., 2008. Liner shipping connectivity and port infrastructure as determinants of freight rates in the Caribbean., Published online: Maritime Economics and Logistics. 10(1):130–151..
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11. Appendix
Appendix A: Damen ship types Below is an picture of ships for different markets produced by Damen. Damen produces a wide variety of ships on different shipyards worldwide.
Tug Boats Ferries
High Speed Vessels Naval Defense vessels
Pontoons Transportation ships
Offshore Fishing ships
Dredgers
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Appendix B: Damen worldwide Figure 22 is an overview of Damen worldwide activities.
Figure 45: Global activities Damen Shipyards Group
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Appendix C: Organogram Damen The Organogram below shows the organization of Damen. The darker blue boxes show the hierarchy of the Service Deliveries departments.
CFO CPO CCO
Purchase Office Sales
Damen Finance HR Research
Sales & Excellerate IT&IM Business Unit Support
PLM Operations High Speed Pontoons & Program Workboats Offshore Technical Support Craft Cooperation Barges
DSko E&A DSGo Yard Product & Product & Product & DSGo Proposal C&CM Proposal Proposal Product & Facilities Offshore & Proposal Damen Tugs High Speed Transport Offshore XL Holding Dredging Craft DTC PMO Cargo Vessels Inland Vietnam Workboats Fast Ferries Yacht Support Cruise & Ferries Waterway Transport
Engineering Project Project Project Project Damen Office Management Management Management Management Services
Area Contracting Engineering Engineering Engineering Engineering Services Parts Service Operations Services Teams 1-7
Yard Purchase / Purchase / Purchase / Purchase / Support MC MC MC MC Initial Configuration Web-Based Parts Sales Provisioning Management Services
Logistics (Avelingen Oost) Training & Combined Service Service Maintenance Field Service Delivery Services Services Calls Hubs Services - DSCS HSEQ - DSGa (Tugs & - DSSi - DSGa - Customer Ship Workboats) - DSAN - DYS Yards Deliveries & Training - DDE Trials - DSCh QC
Figure 46: Organogram Damen
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Appendix D: Swimlane diagram Figure 47 below shows the swimlane diagram of the activities of the process for a make to order heavy lift delivery. A line in the swimlane diagram with one arrow represents a step towards the next activity where a line with arrows on both ends represents an interaction between multiple departments or third parties.
Delivery Heavy Lift proces
Finance/Legal/ Suppliers & Agencies Customer Sales AST Deliveries PG Yard Carrier Insurance & Support
Preparations before booking
Kick-off info Project - Budget Budget in IFS Worklist specification - Worklist
Create IFS project + Planning Check Planning check planning + approval
General Lifting Plan Negotiates Arrangement Check Lifting Negotiating Sets margin on Determining best Transport Options delivery with IDC Stowing Plan and +Stowing Plan delivery delivery based on dates and rates Lifting Plan customer Price with MWS Cradle Plan Initial approval delivery Lashing Plan CC Booking Permission Request for booking Booking Permission Memo permission Memo Revaluate price
Hedge USD / EUR (BIMCO) Contract
Check contract Signing of Contract Lifting Gear with Carrier Cradles Preparations before loading MWS Agencies Arrange crew / Fuel Purchasing Loading assistance Inland Transport
Insurance Cert Insurance cert. Insurance cert. AON AON AON
Approval Releasememo Releasememo for for departure (Also by CPO) departure
CCuussttoommeerr ccoonnttaacctt Arrange shipping Local Export ddeettaaiillss ffoorr vvooyyaaggee agent Formalities uuppddaatteess Transport ship from Delivery Contract yard to port Delivery Contract Input / required present at EXW present at EXW info ddeelliivveerryy??
Loading, voyage, delivery and closing Damage and Planning & Marine Warranty Loading Warranty Updates Operations Surveyor
Securing
Payment of invoice Arrange payment of shipping line invoice Carrier
Loading Report Voyage Updates
Update Update Update Update Update Loading Report and Voyage Updates
Release Bill of Lading Shipping Documents Bill of Lading
Commercial Invoice
Letter of Credit Send documents to Destination and LC Documents Bank Related Documents
LC Documents
Request for Damen Presence Arrival and at Arrival Discharge Discharge Request customer for arrangements for discharge (clearance, tugboat, berth)
Arrange Payment of Request for Invoices Legend all Invoices
Closing Project and Subsequent subsequent calculation Milestones calculation
Figure 47: Swimlane diagram at the Delivery process
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Appendix E: Container freight markets and rates In Table 24 the freight rates of the last six years for the different main routes are shown. It shows that there can be big differences of up to 50% within a year for freight markets.
Table 24: Container freight markets and rates
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Figure 48 shows this in a graphical manner and Figure 49 shows the freight rates per nautical mile.
Container freight rates per route $3.000 Shanghai-Singapore
$2.500 Shanghai-Northern Europa
$2.000 Shanghai-Mediterranean
$1.500 Shanghai-South America
(Santos) $ per$ TEU $1.000 Shanghai-Australia (Melbourne) Shanghai-West Africa $500 (Lagos) Shanghai-South Africa $0 (Durban) 2009 2010 2011 2012 2013 2014
Figure 48: Container freight rates
Container freight rates per nautical mile $0,350 Shanghai-Singapore $0,300 Shanghai-Northern $0,250 Europa Shanghai-Mediterranean $0,200 Shanghai-South America (Santos) $perTEU $0,150 Shanghai-Australia $0,100 (Melbourne) Shanghai-West Africa $0,050 (Lagos) Shanghai-South Africa $0,000 (Durban) 2009 2010 2011 2012 2013 2014
Figure 49: Container freight rates per nautical mile
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Appendix F: Port tariff structures Asian ports Table 25: Port tariff structure Asian ports overview
Service Component / type of Charging system group service Basis Units Payer Recipient Port dues Size of ship GRT Shipping line Port Pilotage Size of ship Time GRT Shipping line Port/ Hours Pilotage Association Tug services Tug time Number Shipping line Port/ Tug Navigation involved Size of GRT owner ship Mooring / unmooring Size of ship GRT Shipping line Port
Ancillary services Various Various Shipping line Port
Berth hire Time of ship Hours Shipping line Port alongside GRT Size of ship Berth Wharfage Volume/weight/ Tonnes/TEU/m3 Consignee/ Port size of cargo Consignor Ancillary services Amount Various Shipping line Port consumed Stevedorage Volume/weight/ Tonnes/TEU/m3 Shipping line Provider of size of cargo service Wharf handling Volume/weight/ Tonnes/TEU/m3 Consignee/ Provider of size of cargo Consignor service Extra-movement Volume/weight/ Tonnes/TEU/m3 Consignee/ Provider of size of cargo Consignor service Cargo Special cargo handling Volume/weight/ Unit Shipping line Provider of operations size of cargo Types service Type of special handling Storage Time Tonnes/TEU/m3 Consignee/ Provider of Days Consignor service Packing / unpacking Volume/weight/ Tonnes/TEU/m3 Shipping line Provider of size of cargo Unit type service
Equipment/ service/ Hours of use Hours Stevedore Equipment/ facility hire services owner Real estate, licensing, Various Various Hirer Port Other management services and Business consultancy etc.
Lease Dedicated costs Lease area Various Lessee Port Rental charge Lease area Various Lessee Port
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Appendix G: Heavy lift fleet overview Figure 50 shows the market share of the shipping companies for ships that can lift over 100 tons.
Figure 50: Market share of top 15 multipurpose shipping companies by deadweight with a combined lifting capacity above 100 tons (Toepfers, 2016)
Table 26 shows the ships that have a SWL of 800 metric tons or more. There are 70 ships of 9 different shipping companies in this range.
Table 26: Top of Heavy lift fleet
Shipping company Shipname DWT Max lift. Cap. Jumbo Maritime Jumbo Kinetic 14000 3000 Jumbo Maritime Fairmaster 14000 3000 SAL Heavy Lift Svenja 12500 2000 SAL Heavy Lift Lone 12500 2000 BigLift Shipping Happy Sky 18680 1800 BigLift Shipping Happy Star 17750 1800 Jumbo Maritime Jumbo Javalin 13278 1800 Jumbo Maritime Fairpartner 13278 1800 Jumbo Maritime Jumbo Jubilee 13278 1800 Jumbo Maritime Fairplayer 6300 1800 BigLift Shipping Happy Buccaneer 13740 1400 Hansa Heavy Lift HHL Valparaiso 19450 1400
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Hansa Heavy Lift HHL Tokyo 19450 1400 Hansa Heavy Lift HHL Lagos 19450 1400 Hansa Heavy Lift HHL Richards Bay 19450 1400 Hansa Heavy Lift HHL Fremantle 19450 1400 Intermarine Industrial Grace 19347 1400 Intermarine Industrial Guide 19347 1400 SAL Heavy Lift Regine 12000 1400 SAL Heavy Lift Trina 12000 1400 SAL Heavy Lift Anne-Sofie 12000 1400 SAL Heavy Lift Frauke 12000 1400 BBC Chartering Palmerton 10124 900 BBC Chartering Palembang 10124 900 BBC Chartering Palau 10124 900 BBC Chartering Palabora 10124 900 Hyundai Merchant Marine Phoenix 10128 900 Hyundai Merchant Marine Pegasus 10128 900 Intermarine Ocean Glory 19834 900 Intermarine Ocean Grand 19834 900 SAL Heavy Lift Amoenitas 9963 900 SAL Heavy Lift Calypso 9963 900 BBC Chartering BBC Spring 16500 800 BBC Chartering BBC Tourmaline 14800 800 BBC Chartering BBC Topaz 14800 800 BBC Chartering BBC Sapphire 14800 800 BBC Chartering BBC Ruby 14800 800 BBC Chartering BBC Quartz 14800 800 BBC Chartering BBC Pearl 14800 800 BBC Chartering BBC Opal 14800 800 BBC Chartering BBC Moonstone 14800 800 BBC Chartering BBC Emerald 14800 800 BBC Chartering BBC Coral 14800 800 BBC Chartering BBC Citrine 14800 800 BBC Chartering BBC Aquamarine 14800 800 BBC Chartering BBC Amethyst 14800 800 BBC Chartering BBC Amber 14800 800 BigLift Shipping Happy River 15634 800 BigLift Shipping Happy Rover 15634 800 BigLift Shipping Happy Ranger 15634 800 Hansa Heavy Lift HHL Rio de Janeiro 20100 800 Hansa Heavy Lift HHL Kobe 20100 800 Hansa Heavy Lift HHL New York 20100 800 Hansa Heavy Lift HHL Venice 19350 800 Hansa Heavy Lift HHL Lisbon 19350 800 Hanssy Shipping MV HAN YI 15970 800 Intermarine Ocean Giant 16868 800 Intermarine Ocean Globe 16476 800 Intermarine Ocean Freedom 14360 800 Jumbo Maritime Daniella 14360 800 Jumbo Maritime Mirabella 14360 800 Jumbo Maritime HLV Jumbo Vision 7051 800
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Jumbo Maritime Fairplane 7051 800 UnitedHeavyLift Atlantic Winter 19100 800 UnitedHeavyLift Baltic Winter 19100 800 UnitedHeavyLift Pacific Winter 19100 800 UnitedHeavyLift Prima Dora 19100 800 UnitedHeavyLift Ran J 14360 800 UnitedHeavyLift Eris J 14360 800 UnitedHeavyLift Senda J 14360 800
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Appendix H: Stopford model for revenue and costs of operating a ship The below figure is a summary made by Stopford presented in his book Maritime Economics, 2009. It shows all subjects for operating a transportation on revenue and costs. This is used as a baseline for the model.
Figure 51: Revenue and cost summary (Stopford, 2009)
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Appendix I: Distances per location baseline route Table 27 shows the distances between a port of loading and a port of unloading as well as the distances towards Singapore per port of loading.
Table 27: Baseline ship route
Distance in Port of Loading Port of Discharge Distance POL to Singapore nautical mile Rotterdam, The Netherlands Gothenburg, Sweden 501 8288 Gothenburg, Sweden Gdansk, Poland 406 8732 Rotterdam, The Gdansk, Poland 874 9105 Netherlands Rotterdam, The Netherlands La Habana, Cuba 4314 8288 La Habana, Cuba Houston, Texas USA 758 10956 Houston, Texas USA Veracruz, Mexico 665 11695 Veracruz, Mexico Balboa, Panama 1449 11746 Balboa, Panama Tokyo, Japan 7699 10495 Tokyo, Japan Busan, South Korea 669 2904 Busan, South Korea Shanghai, China 492 2503 Shanghai, China Singapore, Singapore 2237 2237 Singapore, Singapore Perth, Australia 2220 0 Perth, Australia Jakarta, Indonesia 1763 2220 Jakarta, Indonesia Singapore, Singapore 525 525 Singapore, Singapore Bushehr, Iran 3720 0 Bushehr, Iran Ras Tanura, Saudi Arabia 145 3720 Ras Tanura, Saudi Arabia Sjarjah, UAE 298 3701 Sjarjah, UAE Dakar, Senegal 6294 3422 Dakar, Senegal Douala, Cameroon 1987 8425 Douala, Cameroon Lagos, Nigeria 439 7976 Rotterdam, The Lagos, Nigeria 4171 8166 Netherlands Total distance travelled 41626
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Appendix J: Regression results distance round voyage Table 28 and Table 29 show the outcomes of the regression test results performed to determine if the baseline route of heavy lift ships follow a similar distribution as a CDF of a uniform distribution.
Table 28: Model summary regression baseline against CDF uniform distribution
Model summary R 0.989 R-square 0.978 Adjusted R square 0.978 SE of the estimate 531.53 Sample size 211
Table 29: Statistical tests regression analysis baseline against CDF uniform distribution
ANOVA df Sum of squares Mean Square F P-value Regression 1 2.65*109 2.65*109 9363.7 <0.01 Residuals 209 5.9*107 2.8*105 Total 210 2.7*109
Figure 52 shows the result of the residuals of the baseline route compared with the CDF of a uniform distribution. Although the residuals are high and positive in the middle the figure still shows a nice fit where the residuals are following the zero line. Together with the summary of the tests results as shown above there can be concluded that the distance towards Singapore of the baseline route follows a cumulative distribution function of a uniform distribution.
1500 1000 500 0 0 2000 4000 6000 8000 10000 12000 14000
Residuals -500 -1000 -1500 0
Figure 52: Residual plot baseline against CDF uniform distribution
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Appendix K: Sample for fuel consumption analysis Figure 53: Deadweight distribution of sample size shows the DWTs of the 53 ships used in the fuel consumption sample size. It shows a nice distribution of ships between DWT of 8600 and 20100.
DWT of sample 25000
20000
15000
10000 DWT DWT MT in
5000
0 1 3 5 7 9 11131517192123252729313335373941434547495153 Ship number
Figure 53: Deadweight distribution of sample size
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Appendix L: Regression tests results energy usage Table 30 and Table 31 below show the outcomes of the regression analysis performed to determine the fuel consumption of heavy lift ships.
Table 30: Model summary regression analysis energy usage against DWT
Model summary R 0.754 R-square 0.569 Adjusted R square 0.560 SE of the estimate 400.030 Sample size 53
Table 31: Statistical tests regression analysis energy usage against DWT
ANOVA df Sum of squares Mean Square F P-value Regression 1 10763047 10763047 67.26 <0.0001 Residuals 51 8161210 160024 Total 52 18924257
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Appendix M: Example of Port costs calculation Table 32 shows an example of the port costs in Valparaiso, Chili and Table 33 shows the calculation method for the Anchorage of Ha Long, Vietnam. The examples are of two different ships but it already shows the major differences between calculation methods and the major differences in the total port costs per port.
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Table 32: Port costs Valparaiso, Chili
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Table 33: Port costs Anchorage of Ha Long, Vietnam ESTIMATED PORT DISBURSEMENT
154 LOA
MV. BigLift Happy Star 18,374 GRT CARGO DISCHARGING : NIL CARGO LOADING : 02-03 units of tug (approx 1,000 MT) PORT : HA LONG Anchorage Amount (USD) A. Port charges and dues Formulas 7,471.16 - Tonnage due : usd 0.034 x GRT x 2 (inward & outward) 1,249.43 - Channel due : usd 0.1 x GRT x 2 (inward & outward) 3,674.80 - Pilotage charge (first 10 miles) : usd 0.0034 x GRT x 10miles x 02 (IN/OUT) 1,249.43 - Pilotage charge (last 08 miles) : usd 0.0022 x GRT x 08miles x 02 (IN/OUT) 646.76 - Anchorage due : usd 0.0005 x GRT x 36 Hrs 330.73 - Quarantine : Gov't tariff (inward + outward) 220.00 - Clearance Fee : Gov't tariff (inward + outward) 100.00 B. Miscellaneous 1,100.00 - Freight tax : 2% on total ocean freight Pls adv - Arrangement fee : for anchorage position 1,000.00 - Shore pass for crew : usd 4 x 25prs 100.00 C. Agency fees 1,500.00 D. Agency Expenses 700.00 - Transportation Charge : 500.00 - Communication Charge : 200.00 10,771.16 + freight tax The freight tax can be a substantial amount. The 2% is calculated over the total sum paid from the shipper to the shipping company.
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Appendix N: Deck length regression analysis. The figures and tables below show the outcomes of the regression analysis performed to determine the deck length of heavy lift ships. This is used as a variable to determine the utilization levels of the ships.
Figure 54 shows the residuals per ship. The residuals show a good distribution over the DWT.
30
20
10
0 5000 10000 15000 20000
-10 Decklength -20
-30
-40 DWT
Figure 54: Residuals deck length
The Model summary in Table 34 and the other regression results in Table 35 show that the assumption can be made that the relation between deck length and DWT is linear.
Table 34: Model summary regression analysis deck length against DWT
Model summary R 0.808 R-square 0.653 Adjusted R square 0.649 SE of the estimate 13.12 Sample size 95
Table 35: Statistical tests regression analysis deck length against DWT
ANOVA df Sum of squares Mean Square F P-value Regression 1 30111 30111 174.80 <0.0001 Residuals 93 16020 172 Total 94 46131
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Appendix O: Canal Net Tonnage regression analyses. To estimate the SCNT of ships linear regression analysis is performed over the ships that published their DWT and SCNT. Figure 55 shows the data points of the 16 heavy lift ships. Some ships have the same DWT and SCNT that is why there are not 16 points visible in the figure. The SCNT goes below zero at lower DWT. This is unrealistic. From point that the DWT is 8,100 the DWT is divided by 2 to calculate the SCNT.
16000
14000 y = 2,3096x - 14658 12000 R² = 0,9768 10000 Sample SCNT 8000 6000 Predicted SCNT 4000 Lineair (Sample 2000 Suez Net Canal Tonnage SCNT) 0 0 10000 20000 Deadweight
Figure 55: Suez Canal Net Tonnage regression analyses
Table 36 shows the model summary of regression analysis of SCNT against DWT and Table 37 shows the model summary of regression analysis of PC/UMS against DWT.
Table 36: Model summary regression analysis SCNT against DWT
Model summary R 0.988 R-square 0.977 Adjusted R square 0.975 SE of the estimate 526.39 Sample size 16
Table 37: Model summary regression analysis PC/UMS against DWT.
Model summary R 0.976 R-square 0.952 Adjusted R square 0.948 SE of the estimate 458.83 Sample size 16
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Appendix P: Top Heavy Lift ships characteristics and costs. The following Tables show the characteristics and the costs per subject for the top 40 heavy lift ships.
Name DWT Suez Panama Engine Fuel Fuel Lifting Total NT NT kW at consumption consumption Capacity Costs 14 Berth knots Jumbo 14000 17676 14037 5424 26 3,3 3000 € 64,20 Kinetic Fairmaster 14000 17676 14037 5424 26 3,3 3000 € 64,20 Svenja 12500 14212 11969 5254 25 3,1 2000 € 48,50 Lone 12500 14212 11969 5254 25 3,1 2000 € 48,50 Happy Sky 18680 28485 20490 5952 29 3,9 1800 € 57,02 Happy Star 17750 26337 19208 5847 28 3,8 1800 € 55,35 Jumbo 13278 16009 13042 5342 26 3,2 1800 € 47,30 Javalin Fairpartner 13278 16009 13042 5342 26 3,2 1800 € 47,30 Jumbo 13278 16009 13042 5342 26 3,2 1800 € 47,30 Jubilee Fairplayer 6300 3150 3420 4555 22 2,3 1800 € 34,74 Industrial 19347 30026 21410 6027 29 4,0 1400 € 53,02 Grace Industrial 19347 30026 21410 6027 29 4,0 1400 € 53,02 Guide Happy 13740 17076 13679 5394 26 3,3 1400 € 42,93 Buccaneer Regine 12000 13057 11280 5198 25 3,0 1400 € 39,80 Trina 12000 13057 11280 5198 25 3,0 1400 € 39,80 Anne-Sofie 12000 13057 11280 5198 25 3,0 1400 € 39,80 Frauke 12000 13057 11280 5198 25 3,0 1400 € 39,80 HHL 19450 30264 21552 6038 29 4,0 1400 € 53,21 Valparaiso HHL Tokyo 19450 30264 21552 6038 29 4,0 1400 € 53,21 HHL Lagos 19450 30264 21552 6038 29 4,0 1400 € 53,21 HHL 19450 30264 21552 6038 29 4,0 1400 € 53,21 Richards Bay HHL 19450 30264 21552 6038 29 4,0 1400 € 53,21 Fremantle Ocean 19834 31151 22081 6082 29 4,1 900 € 47,40 Glory Ocean 19834 31151 22081 6082 29 4,1 900 € 47,40 Grand Phoenix 10128 8734 8698 4987 24 2,8 900 € 29,93 Pegasus 10128 8734 8698 4987 24 2,8 900 € 29,93 Amoenitas 9963 8353 8471 4968 24 2,8 900 € 29,63
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Calypso 9963 8353 8471 4968 24 2,8 900 € 29,63 BBC 10124 8724 8693 4986 24 2,8 900 € 29,92 Palmerton BBC 10124 8724 8693 4986 24 2,8 900 € 29,92 Palembang Palau 10124 8724 8693 4986 24 2,8 900 € 29,92 Palabora 10124 8724 8693 4986 24 2,8 900 € 29,92 Atlantic 19100 29455 21069 5999 29 4,0 800 € 44,78 Winter Baltic 19100 29455 21069 5999 29 4,0 800 € 44,78 Winter Pacific 19100 29455 21069 5999 29 4,0 800 € 44,78 Winter Prima Dora 19100 29455 21069 5999 29 4,0 800 € 44,78 Ocean 16868 24300 17992 5747 28 3,7 800 € 40,76 Giant Ocean 16476 23395 17451 5703 27 3,7 800 € 40,05 Globe MV HAN YI 15970 22226 16753 5646 27 3,6 800 € 39,14 Happy 15634 21450 16290 5608 27 3,5 800 € 38,54 River
Name Daily Daily Daily Fuel Daily Ship Ship Suez Panama Port Costs capital operating costs Sea Fuel daily daily canal canal costs costs costs rate sea rate costs costs Berth berth Jumbo € 15.085 € 4.800 € 7.029 € 896 € 26.914 € 20.781 € 134.380 € 68.531 € 19.212 Kinetic Fairmas € 15.085 € 4.800 € 7.029 € 896 € 26.914 € 20.781 € 134.380 € 68.531 € 19.212 ter Svenja € 11.396 € 4.800 € 6.810 € 841 € 23.006 € 17.037 € 115.739 € 59.243 € 18.509 Lone € 11.396 € 4.800 € 6.810 € 841 € 23.006 € 17.037 € 115.739 € 59.243 € 18.509 Happy € 13.399 € 4.800 € 7.713 € 1.066 € 25.912 € 19.265 € 181.124 € 97.475 € 21.405 Sky Happy € 13.006 € 4.800 € 7.577 € 1.032 € 25.383 € 18.837 € 172.456 € 91.752 € 20.969 Star Jumbo € 11.114 € 4.800 € 6.923 € 870 € 22.838 € 16.784 € 125.407 € 64.060 € 18.873 Javalin Fairpart € 11.114 € 4.800 € 6.923 € 870 € 22.838 € 16.784 € 125.407 € 64.060 € 18.873 ner Jumbo € 11.114 € 4.800 € 6.923 € 870 € 22.838 € 16.784 € 125.407 € 64.060 € 18.873 Jubilee Fairplay € 8.163 € 4.800 € 5.903 € 616 € 18.866 € 13.579 € 35.999 € 20.200 € 15.603 er Industri € 12.459 € 4.800 € 7.811 € 1.090 € 25.070 € 18.349 € 187.340 € 101.539 € 21.717 al Grace Industri € 12.459 € 4.800 € 7.811 € 1.090 € 25.070 € 18.349 € 187.340 € 101.539 € 21.717 al Guide Happy € 10.088 € 4.800 € 6.991 € 886 € 21.879 € 15.774 € 131.149 € 66.921 € 19.090 Buccan eer
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Regine € 9.352 € 4.800 € 6.737 € 823 € 20.888 € 14.975 € 109.526 € 56.147 € 18.275 Trina € 9.352 € 4.800 € 6.737 € 823 € 20.888 € 14.975 € 109.526 € 56.147 € 18.275 Anne- € 9.352 € 4.800 € 6.737 € 823 € 20.888 € 14.975 € 109.526 € 56.147 € 18.275 Sofie Frauke € 9.352 € 4.800 € 6.737 € 823 € 20.888 € 14.975 € 109.526 € 56.147 € 18.275 HHL € 12.503 € 4.800 € 7.826 € 1.093 € 25.129 € 18.396 € 188.300 € 102.167 € 21.766 Valparai so HHL € 12.503 € 4.800 € 7.826 € 1.093 € 25.129 € 18.396 € 188.300 € 102.167 € 21.766 Tokyo HHL € 12.503 € 4.800 € 7.826 € 1.093 € 25.129 € 18.396 € 188.300 € 102.167 € 21.766 Lagos HHL € 12.503 € 4.800 € 7.826 € 1.093 € 25.129 € 18.396 € 188.300 € 102.167 € 21.766 Richard s Bay HHL € 12.503 € 4.800 € 7.826 € 1.093 € 25.129 € 18.396 € 188.300 € 102.167 € 21.766 Freman tle Ocean € 11.138 € 4.800 € 7.882 € 1.107 € 23.820 € 17.045 € 191.879 € 104.506 € 21.946 Glory Ocean € 11.138 € 4.800 € 7.882 € 1.107 € 23.820 € 17.045 € 191.879 € 104.506 € 21.946 Grand Phoenix € 7.033 € 4.800 € 6.463 € 755 € 18.296 € 12.588 € 83.305 € 44.426 € 17.397 Pegasus € 7.033 € 4.800 € 6.463 € 755 € 18.296 € 12.588 € 83.305 € 44.426 € 17.397 Amoeni € 6.963 € 4.800 € 6.439 € 749 € 18.202 € 12.512 € 80.365 € 43.382 € 17.320 tas Calypso € 6.963 € 4.800 € 6.439 € 749 € 18.202 € 12.512 € 80.365 € 43.382 € 17.320 BBC € 7.031 € 4.800 € 6.462 € 755 € 18.293 € 12.586 € 83.234 € 44.401 € 17.395 Palmert on BBC € 7.031 € 4.800 € 6.462 € 755 € 18.293 € 12.586 € 83.234 € 44.401 € 17.395 Palemb ang Palau € 7.031 € 4.800 € 6.462 € 755 € 18.293 € 12.586 € 83.234 € 44.401 € 17.395 Palabor € 7.031 € 4.800 € 6.462 € 755 € 18.293 € 12.586 € 83.234 € 44.401 € 17.395 a Atlantic € 10.522 € 4.800 € 7.775 € 1.081 € 23.097 € 16.403 € 185.038 € 100.034 € 21.602 Winter Baltic € 10.522 € 4.800 € 7.775 € 1.081 € 23.097 € 16.403 € 185.038 € 100.034 € 21.602 Winter Pacific € 10.522 € 4.800 € 7.775 € 1.081 € 23.097 € 16.403 € 185.038 € 100.034 € 21.602 Winter Prima € 10.522 € 4.800 € 7.775 € 1.081 € 23.097 € 16.403 € 185.038 € 100.034 € 21.602 Dora Ocean € 9.578 € 4.800 € 7.448 € 1.000 € 21.826 € 15.378 € 164.235 € 86.290 € 20.556 Giant Ocean € 9.412 € 4.800 € 7.391 € 986 € 21.603 € 15.198 € 160.582 € 83.863 € 20.372 Globe MV € 9.198 € 4.800 € 7.317 € 967 € 21.315 € 14.965 € 155.866 € 80.730 € 20.135 HAN YI Happy € 9.056 € 4.800 € 7.268 € 955 € 21.124 € 14.811 € 152.734 € 78.649 € 19.977 River
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Appendix Q: MATLAB functions and calculations. The following shows how all input parameters and calculations are set in MATLAB. Green text means that this is not taken into account in calculations, it gives a description of the formula. clear all %delete workspace close all % clc
%% Variables weightemptyship = 750; loadingdays = 3; unloadingdays = 1; CargoLength = 34; %Damen ship length in meters distance = 4744; % in nautical miles flexdays = 112; %number of offered flexibility days for mobilization suez = 0; %1 is suez passage, 0 is no suez passage panama = 0; %1 is panama passage, 0 is no panama passage mobdays = 1; %minimum days charged as mobilization costs demobdays = 1; MUFR = 0.6 %Max utilization for route, maximum is one for destination on major trade lanes. %gets lower for more exotic places ( SCCPMC = 1000; %Suez Canal Costs Per Meter Cargo
shipweight = weightemptyship*1.1; sailingdays = distance/336; flexdayssea = flexdays/2; if suez > 0.5 SCCPMC = 1000 else SCCPMC = 0 end if flexdays>119 flexdays=119 end
%% data load [data] = xlsread('Database_Heavy_Lift_fleet'); %read excel database [num,txt,raw] % data
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%% Calculations [k] = find(data(:,1) >= shipweight);
%% Forward loop to determine average of minima aantalvooraverage=1; %number of ships for average per simulation run aantalruns = 100; %nr of simulation runs for j=1:aantalruns; for i=1:size(k)
SR(i) = data(k(i),2); %SeaRate SRB(i) = data(k(i),3); %SeaRateBirth if suez > 0,5; SCC(i) = data(k(i),4); %Suezcanal costs else SCC(i)=0; end
if panama > 0,5; PCC(i) = data(k(i),5); %Panama canal costs else PCC(i)=0; end
OOPC(i) = data(k(i),6); %One of port costs PCPD(i) = data(k(i),7); %Port cost per day DL(i) = data(k(i),8); %decklenght cargo ship
SUBC(i)= CargoLength/DL(i); %Ship utilization by cargo f=sailingdays/0.60; MU(i)=SUBC(i)+(((MUFR-SUBC(i))/f))*flexdayssea; %MU(i)= maximum utilization if MU(i) < SUBC(i); MU(i)= SUBC(i)+0.01 ; end if MU(i) > MUFR; MU(i) = MUFR; %sets maximum to maximum for that specific trade lane, %0.7 is max for major trade lane end
SUT(i)= makedist('Uniform','lower',SUBC(i),'upper',MU(i)); %ship utilization from uniform dist. lower is SUBC upper is max utilization for route q(i)=random(SUT(i)); r(i)=(SUBC(i)/q(i));%Utilization Costs Charged to customer SUC(i)=r(i); %SUC(i) Ship utilization canal, gives the number to multiply the total sea voyage costs that is charged to the customer MobilizationCosts(i) = SR(i)*(((rand(1)- 0.0084*flexdays)*(12000))/(24*14));%rand(1) is uniform between 0 and 1; - 0.0084 is speed that maximum lowers if MobilizationCosts(i) 83 end Test = [MobilizationCosts+LoadingCosts+SeaVoyageCosts+CanalCosts+UnLoadingCosts+DeMo bilizationCosts+SUC+q; MobilizationCosts; LoadingCosts; SeaVoyageCosts; CanalCosts; UnLoadingCosts; DeMobilizationCosts; SUC; q]; TestSorted = sortrows(Test'); %sorteer de waardes TestSortedFiltered = TestSorted(1:aantalvooraverage,:); %filter de laagste getallen averagetestsortedfiltered(j) = mean(TestSortedFiltered(:,1)); end average_averagetestsortedfiltered=mean(averagetestsortedfiltered) %% adjustments to make nice graph sortMobilizationCosts= sortrows(MobilizationCosts'); The figures below were all used in the verification of the model figure hold yyaxis left bar([TestSorted(:,2) TestSorted(:,3) TestSorted(:,4) TestSorted(:,5) TestSorted(:,6) TestSorted(:,7)],0.6,'stacked') legend('Mobilization Costs','Loading Costs','SeaVoyage Costs', 'Canal Costs', 'Unloading Costs', 'DeMobilization Costs') grid on title('Mob, Load, SeaVoyage, Canal, Unloading and Demobilization Costs') ylabel('Costs in Euro') hold on yyaxis right ylim([0,1]) plot([ TestSorted(:,9)],'x') figure plot(averagetestsortedfiltered, 'x') title('Minimum costs per simulation run') figure hold boxplot(averagetestsortedfiltered) title('Boxplot of minimum costs for 100 simulation runs') avg= mean(averagetestsortedfiltered) hold on plot(avg,'x') 84 Appendix R: Poster thesis 85