International Journal of Civil Engineering and Technology (IJCIET) Volume 10, Issue 09, September 2019, pp. 111-118, Article ID: IJCIET_10_09_012 Available online at http://iaeme.com/Home/issue/IJCIET?Volume=10&Issue=9 ISSN Print: 0976-6308 and ISSN Online: 0976-6316 © IAEME Publication

CONTAINER HANDLING TIME MODEL AS AN EFFORT TO REDUCE DWELLING TIME IN SOEKARNO HATTA PORT OF MAKASSAR

Henny Haerany Doctoral Student of Civil Engineering Department, Hasanuddin University, Makassar, Indonesia

Sakti Adji Adisasmita Professor, Civil Engineering Department, Hasanuddin University, Makassar, Indonesia

Misliah Idrus Associate Professor, Naval Engineering Department, Hasanuddin University, Makassar, Indonesia

Sumarni Hamid Aly Associate Professor, Civil Engineering Department, Hasanuddin University, Makassar, Indonesia

ABSTRACT One of the problems in Makassar container terminal that affects port performance is the waiting time. Dwelling time containers occurs in terminal still relatively long, for domestic goods around 7-8 days. One of the reasons is the pre-custom clearance process, which is unloaded containers process until placed in the stacking yard. The containers handling is needed to optimize port facilities work in loading and unloading equipment case. Container handling process analysis from the dock to the stacking field using Container Crane, Rubber Tyred Gantry Crane, and Head trucks with simulation methods using Arena software. Based on the simulation results, concluded that from the three scenarios conducted, model scenario two was chosen as the best scenario by adding tools to the dock and stacking yard. The addition of this tool produces an average cycle timeless than the initial condition. The cycle time deviation of the unloading process is 12 minutes, while the loading process is 3 minutes. This scenario model becomes a reference to reduce the waiting time in container terminals, such as maximizing tools work by rejuvenating tools or adding tools that have higher capacity and improving container handling systems by suppressing wasted time (idle time). Keywords: Container Handling, Wasted Time, Dwelling Time, Arena Simulation

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Cite this Article: Henny Haerany, Sakti Adji Adisasmita, Misliah Idrus and Sumarni Hamid Aly, Container Handling Time Model As An Effort To Reduce Dwelling Time In Soekarno Hatta Port of Makassar. International Journal of Civil Engineering and Technology 10(9), 2019, pp. 111-118. http://iaeme.com/Home/issue/IJCIET?Volume=10&Issue=9

1. INTRODUCTION Sea transportation contributes significantly to the national and regional economy. The contribution becomes increasingly important because the costs value incurred the smallest when compared to land and air transportation costs (Jusna and Tibertius, 2016). The good port characterized by a reliable quality of port service performance (Triatmojo, 2010). The problem in Indonesian ports is that performance still not good, as evidenced in the 2015-2016 Global Competitiveness Report data, Indonesia has 82 ranks out of 140 countries based on a port quality assessment with 3.8 values, while Singapore has two ranks with 6.7 value. Whereas based on the 2014 Logistics Performance Index (LPI) data, Indonesia is ranked 53 out of 160 countries surveyed. Indonesia is far below Malaysia and Thailand. This index includes infrastructure, shipping, logistics competency, tracking, and loading and unloading time. This is due to loading and unloading productivity, congestion conditions, and lengthy process of document management. One of the leading port efficiency indicators is dwelling time because of shows terminal productivity and overall operational terminal efficiency. Reducing dwelling time will increase port use to the maximum extent possible without the need for new field investment (Marck, 2005). One way to reduce dwelling time by handling tools in the loading and unloading process, Makassar containers handling the process for domestic goods still around 7-8 days. The average dwelling time under ideal conditions according to Rafi and Purwanto (2016) that is; 1.1 days (obtained of Singapore) is excellent; for dwelling time 2 days are very good; 3 days are good; 4 days is average; 5 days are not good; and 6 - 7 days are very slowly. Makassar port still under ideal conditions, so that the Container Terminal is advised to make improvements to the factors affect performance, such as improving operational readiness for loading and unloading equipment (Sulistiana, O., 2012). Based on the concepts and issues of container dwelling time problems and the results of research by Baginda (2016), the waiting time for loading and unloading from the dock to the preclearance is 40% higher than the document handling process. The objective of this study is to model container handling time based on tool working time and wasted time by simulation methods using Arena software tools.

2. LITERATURE REVIEW

2.1. Container Terminal A container terminal is a place where containers collected from hinterland or other ports to transported to the destination. The terminal as a subsystem of other ports that serves to support sea transportation activities. The terminal is responsible to containers transfer from land to sea transportation modes or vice versa, but this activity is a derivative of transportation activities so that container flows at the terminal is more influenced by external factors.

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2.2. Container Port Facilities The container port facility consists of (Eric Rath, 1973, Misliah, 2011) a port pool; dock apron; marshaling yard (temporary piling yard); Container Yard; Container Freight Station (CFS) is a warehouse provided for goods transported by LCL and a crane or container loading and unloading tool, unloading equipment used to move containers from the ship to the dock apron or vice versa, and from the apron to the stacking field or the opposite. The Indonesia Port (2000) describes some container loading and unloading equipment as follows:  Gantry cranes are container taps located at the jetty to load and unload containers from and to container ships, which installed on rails along the jetty. Gantry cranes are also called container cranes.  Forklifts are supporting equipment at container terminals for loading and unloading in small tonnages, usually used in CFS as well as delivery or interchange activities.  Head truck or chassis is a trailer used to transport containers from the dock to the stacking yard or vice versa and from the container stacking field to the CFS warehouse or vice versa.  Straddle carrier, used for loading and unloading containers to/from the chassis and can stack up to three levels.  Side loader used to lift containers and stack them up to three levels.  Transtainer, which is a container valve that is shaped like a portal and can run on rails or has rubber tires. This tool can stack containers up to four levels and place them on top of train cars or chassis.  Reach stacker is combination equipment between Forklift and Mobile Crane which is equipped with Spreader (container lifters), lifting containers capable with 45 tons maximum load and has a flexible lifting range, maximum lifting height of 15 meters.

2.3. Container handling system at the port According to Triatmodjo (2009), the container handling process from the container inside the ship to the container shelter or until it exits the terminal. The process of handling containers outside the waters can use more than one type of handling equipment, including Container Crane, Rubber Tyred Gantry Crane, forklifts, reach stackers, side loaders, head trucks, and chassis. In general, the process of handling containers seen in Figure 1.

Figure 1 Container Handling Process (Tsinker, Gregory P., 2004) Container handling system at the port divided into four types that are Chasis system; Fork Lift Truck system; Straddle Carrier system; and the Rubber Tyred Gantry (RTG) system. Based on the layout of the container above, the Makassar Container Terminal applied the layout of the container with Rubber Tired Gantry handling tool, as shown in Figure 2 with 13 block-stacking number.

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Handling in the RTGC system used in this study is started when the container crane unloads the container from the ship and loaded on the head truck which then takes it to one blocks in container stacking field and places with RTG tool help. There are three tools used; Container Crane, Rubber Tyred Gantry, and Head Truck. The handling system on this system seen in Figure 2.

Figure 2 The layout of handling the equipment from the dock to stacking yard This handling does not need a wide aisle different from other systems until field use can be more productive. This system used at terminals service more than 200,000 TEU's / year.  Container port activities that are the movement of goods from land to sea transport with a full container transportation system with its activities (Morlok, 1985): 1. The container is transported by land transportation (trailer) to the port and then transported by rubber-tired gantry (RTG) placed in piling yard. 2. By using RTG, container appointed and arranged to wait for transporting ship. 3. After carrier arrived and was ready at the dock, the container from the buildup field lifted with the RTG placed on the head truck (HT) being lifted to the ship's dock apron leaning. 4. By using a gantry crane, the container is removed from the HT and loaded onto the ship. 5. After the goods transported to the ship leaves the dock to the destination country or region. 6. Some common problems often arise in a port management context. These problems are:  The length of loading and unloading process at ports in Indonesia  The duration of customs management in Indonesia  Poor quality port facilities  The length of dwelling time at ports in Indonesia  Depth of ports in Indonesia that do not meet requirements

2.4. Dwelling Time According to the World Bank definition (2011), dwelling time is the time calculated from a container unloaded and unloading from the ship until the container leaves the port terminal through the main gate. The process determines dwelling time length at the port is divided into three stages, that is pre-clearance, customs clearance, and post-clearance. Nicoll (2007) explains that the definition of dwelling time is time length container at the port before embarking on a road trip using either truck or train.

http://iaeme.com/Home/journal/IJCIET 114 [email protected] Container Handling Time Model As An Effort To Reduce Dwelling Time In Soekarno Hatta Port of Makassar 3. RESEARCH METHODS The research location was Soekarno Hatta port in Makassar Container Terminal (TPM) unit. The research scope is container handling in the loading and unloading process — data collection based on primary and secondary data. Primary data obtained by calculating container handling cycle times during the loading and unloading process, the data included equipment working time in container cranes and rubber-tired gantry with four working steps. The average handling one box on a Container Crane tool is ± 2 minutes with loading and unloading productivity of 24 boxes/hour while the average handling one box RTG tools is around ± 2 minutes with 27 boxes/hour productivity. The head truck work time divided into two working steps; the process from the dock to the stacking field as step 1 and for step 2 on the contrary; from the stacking field to the dock. The average head truck cycle time is 20.22 minutes, and the average head truck cycle is 4-5 times in one working hour. This data collection obtained arrival time, service time, and queue time, which is input data in Arena software. Secondary data is supporting data, such as a stacking field layout to create an existing condition scheme for processing simulation data. Data processing from the establishment of container handling schemes then conducts data sufficiency tests and data uniformity tests, and distribution tests. Furthermore, model verifies an existing condition, and determine improvement scenario for handling system. The results will compare simulation output results and choose the best scenario, which then becomes a reference for efforts to reduce dwelling time at the Makassar container terminal.

4. RESULTS AND DISCUSSION This study analyzes the container handling system from the dock to stacking field using six units container cranes, 16 units rubber tire gantry and 16 units head truck. The initial model formation based on tools number in the Makassar container terminal and its handling system, as shown in Figure 3, the schema built for loading and unloading process.

(a) Unloading Process

(b) Loading Process Figure 3 Unloading and Loading Process simulation Based on the initial model in Figure 3, therefore, the distribution test is shown in Tables 1 and 2. This distribution type will use for the Arena simulation model.

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This study analyzes container handling systems from the dock to stacking field using six units of container cranes, 16 units of tired gantry rubber and 26 units of head trucks, based on tools number in Makassar container terminal. Model validation conducted by comparing cycle time when existing conditions and simulation results. The cycle time in the loading process is 20.22 minutes while loading process is 19.01 minutes for existing conditions. While the simulation loading process output is 22.37 minutes while the loading process is 18.53 minutes. The closeness of the results between existing conditions and simulation conditions shows that the model can be used to find the best scenario for handling system. Then the data distribution test is performed to represent existing data. Tables 2 and 3 show the distribution of each data input for the loading and unloading process. Table 2 Recapitulation of Unloading Process data distribution

Activity Distribution Type Expression Time of arrival Triangular TRIA(129, 159, 265) Queue time Weibull (-0.001 + WEIB(123, 0.409)) Retrieval Time Beta 23.5 + 100 * BETA(0.581, 1.23) Appointment Time Weibull 10.5 + WEIB(19, 1.14) Deviation Time Normal NORM(47.5, 19.2) Delivery Queue Time Exponential 99 + EXPO(166) CC Processing Time Weibull 12.5 + WEIB(13.5, 1.22) Table 3 Recapitulation of Unloading Process data distribution Activity Distribution Type Expression Time of arrival Triangular TRIA(139, 145, 410) Queue time Triangular TRIA(-0.001, 43.4, 1.28e+003) Retrieval Time Beta 13.5 + 47 * BETA(0.875, 0.85) Appointment Time Lognormal 8.5 + LOGN(7.55, 7.82) Deviation Time Normal NORM(40.8, 11.6) Delivery Queue Time Triangular TRIA(-0.001, 34.9, 1.28e+003) RTG Processing Time Triangular TRIA(12.5, 25, 64.5) Model validation is done by verifying the initial model by pressing F4 on the simulation scheme, and the results obtained no errors in the model. The next step is data validation, compare the simulation results and the real results of trucks number. Table 4 Throughput Difference Simulation Replication to Output real Simulation System Throughput system Difference 1 130 131 -1

2 132 126 6 3 129 136 -7 4 125 131 -6 5 140 136 4 Average 131.2 132 -0.8 Standard 5.541 4.183 1.358 Deviation The difference results are obtained, then the hypothesis test is performed with a significant level of α = 0.05.

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H0: µ1-µ2 = 0 or there is no significant difference between the real results and the simulation results. H1: µ1-µ2 ≠ 0 or there is a significant difference between the real results and the simulation results. (t n-1 , α/2) . s.dv hw = 

= 1,683

So the confidence interval is:

= [(X1- X2) – Hw ≤ µ1-µ2 ≤ (X1- X2) + Hw] = [-0,8 - 1,68 ≤ µ1-µ2 ≤ -0,8 + 1,68] = ( -2,48 ≤ µ1-µ2 ≤ 0,88)

Because the value in the specified range, then H0 accepted. Moreover, it can be concluded that there is no significant difference between real conditions results with simulations results. This shows that simulation designed is valid. Likewise, the results in the loading process, the simulation is designed valid. The selection proposed scenarios based on real conditions that occur in the terminal and running Arena software results. It was found slowdown delivery process to the stockyard. There are three proposed scenarios. The first proposal is to add a reach-stacker tool that helps the delivery process. While the selection process is handling added using a reach stacker or truck, the second proposed scenario adds tools to the dock and stacking field, reach stacker and side/top loader without any addition to the model. The best-proposed scenario is chosen based on low cycle times compared to real conditions. This was done as an effort to reduce dwelling time at Makassar Container Terminal (TPM).

Table 5a Unloading Process Simulation Output VA Time Wait Time Total Time (second) (second) (second) No Simulation Average Average Average

1 Initial Model 617.09 32238.92 32856.02 2 Scenario I 325.25 10486.91 10812.16 3 Scenario II 550.35 33839.17 34389.52 Table 5b Load Process Simulation Output VA Time Wait Time Total Time (second) (second) (second) No Simulation Average Average Average

1 Initial Model 476.75 20900.64 21377.40 2 Scenario I 354.26 15403.74 15758.00 3 Scenario II 492.36 37815.55 38307.92

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The best scenario selection is made by looking the smallest average cycle time fixed as existing conditions with the same queue and head trucks number. Based on results shown in Tables 5a and 5b, the proposed scenario selected is the two proposed scenario. The delivery process problems such as bottleneck occurrence in stacking field decomposed by adding a reach stacker to the delivery process. In the initial conditions, average total cycle time was 32856.02 seconds or 547.60 minutes in a day, with trucks number by TPM, on average, one truck handled 18 minutes of containers. Whereas in the chosen scenario, the average total cycle time is 15758 seconds or 180.20 minutes a day. Therefore, the average cycle time of 1 truck is 6.01 minutes. The time reduction obtained between the real conditions and the proposed two scenario model is 12 minutes. This is very influential in work optimizing tool which has an impact on reducing dwelling time in container handling systems at TPM.

4. CONCLUSIONS Makassar container terminal handling system is quite good, by looking at average results container service for CC and RTG ± 2 minutes. Efforts need to reduce dwelling time by rejuvenating tools, that idle time reduced. The best scenario model has selected two proposed scenarios by adding the reach stacker tool to the dock and side/top loader in the stacking field. In the two scenario simulation model, the option is added to use aids or head truck in the delivery process and stacking field. This selection based on average head cycle time for container handling to and from stacking yard in one day. The time difference between real and simulation conditions in scenario two, for 12-minutes loading process and 3-minutes loading process, this result reduce dwelling time at the TPM container handling system. Suggestions for further research is to take into account operator, and container placement routes each block in stacking field.

REFERENCES

[1] Idrisa, Alli. 2015. Dwell time for import transit containers at dar es salaam port: an analysis of the role of free storage time. [2] Kramadibrata, Soedjono. 2002. Perencanaan Pelabuhan, Ganeca Exact, Bandung [3] Misliah. 2012. Optimasi pemanfaatan lapangan penumpukan Petikemas di pelabuhan indonesia IV ditinjau dari kepentingan operator dan pengguna (kasus sepuluh pelabuhan). [4] Morlok, 1985, Pengantar Teknik dan Perencanaan Transportasi, Penerbit Erlangga [5] Nicole. Duane, Emily. Wren, Hward. 2007 Optimizing the landside operation of a container [6] Rafi S dan Purwanto, B. 2016. Dwelling Time Management: Antara Harapan dan Kenyataan di Indonesia. Jurnal Manajemen Bisnis Transportasi dan Logistik. [7] Tsinker, Gregory, P. 2004. Port Engineering: Planning, Construction, Maintenance, and Security. New Jersey: Hoboken [8] Triatmojo, 2009, Pelabuhan, Beta Offset, Yogyakarta

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