Model of a Flow-Shop with Order Dependent Sequencing to Experiment with Capacity and Priority Rule Changes
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MASTER THESIS Model of a flow-shop with order dependent sequencing to experiment with capacity and priority rule changes AUTHOR Niels Leliveld FACULTY BMS: Behavioural, Management & Social sciences MASTER PROGRAM Industrial Engineering & Management SPECIALIZATION Production & Logistics Management EXAMINATION COMMITTEE Dr. E.Topan DR. I. Seyran Topan DATE November 2020 i MANAGEMENT SUMMARY Ovimex is a printing company from Deventer. The factory consists of 3 industrial printers (HP30000, HP12000 and HP T240) and multiple finishing operations. The product portfolio includes amongst others: books, user manuals, leaflets, business cards, carton packaging, menu cards, posters and advertisement folders. Due to changes in the market there is a need to improve the output of the factory. This can be done by optimizing the production process, increasing capacity or a combination of both. The objective of this research is the following: Develop a suitable model to evaluate effects of increasing capacity and/or changing priority rules on production KPIs (tardiness, work-in-process, overtime) for a printing company with a process oriented layout subject to a variable demand. To find effects of changes to the production plant a simulation model is created. This simulation model consists of all the machines on the production floor. Data for the model is acquired from the app that records the action by the printers. This data consists of orders and some properties such as order size, color, double sided and order name. The order type can be derived from the order name in approximately 98% of the cases. This data from the printers was only available for two printers: HP30000 and HP12000. For the HPT240 printer there was no data available, however, since this machine is used to print the inside work of books and brochure the workload of this printer can be derived from the data about covers printed on the HP12000 and HP30000 machines. The simulation model is built in the Plant Simulation software. Any order (book or manual or leaflet etc.) in the factory are modeled using a Poisson distribution with the amount of copies per order following an Exponential distribution. Order routing and size is depended on the order type. The processing rate at the machines can be dependent on the order type and the size of the order. The following performance measures are considered in running experiments: average work-In- process in the factory, average amount of finished orders/copies at the end of each day (throughput), average and maximum tardiness, utilization of the machines and average amount of overtime. Multiple simulation experiments were carried out to investigate the impact of the priority rules and the capacity. We found that out of all priority rules that were tested, the earliest due date (EDD) rule works best. Implementing this rule can reduce the average tardiness from 69 minutes to 48 minutes (See figure 0.1) as opposed to the first-come-first-served (FCFS) rule for the current production layout. The EDD priority rule puts a strong emphasis on preventing late orders whilst scoring good on other measures such as overtime, Work-in-process and maximum tardiness To reduce overtime capacity can be added. 3 machines were considered for increasing capacity: an extra purring machine, extra book trimmer and an extra roll cutter. These machines are tested in various configurations and results are shown in figure 0.2. Experiment 12 shows the current situation, experiment 16 an extra book trimmer, experiment 17 an extra book trimmer and roll cutter and experiment 18 an extra book trimmer, roll cutter and purring machine. It was found that adding extra machines does not decrease the average tardiness however it can reduce overtime (See figure 0.2). This can be explained because tardiness seems to be constrained by the capacity of the HP T240 printer. This reduction in overtime should be weighed against the costs of adding this extra capacity. ii Figure 0.1: Comparison between FCFS and EDD priority rules for the current factory layout Adding an extra book trimmer can reduce the daily average overtime from 143 to 108 minutes. Therefore if the savings from 33 minutes of overtime are greater than the extra costs of an extra machine, then it is worth to invest in an extra book trimmer. It is found that the costs of adding a new book trimmer to the factory is estimated to save € 4120,- per year while the costs would be € 3500,- per year. Thus the net savings would be € 620,- per year. These figures depend on the costs of the machine, operator, and energy costs. On top of this, an extra book trimmer gives more flexibility in the production process. From experiments comparing changing priority rules and increasing capacity it can be concluded that changing the priority rules can decrease the average tardiness of orders but keep overtime stable. In contrast, adding extra machine(s) does not improve average tardiness but reduces overtime. Therefore the advice is to add an extra book trimmer to save overtime costs and to change the priority rule to EDD to increase the service level to customers. Figure 0.2: Effects of adding extra machines. iii PREFACE This thesis is the final part of my study at the University of Twente. I have completed both the bachelor and master program of Industrial Engineering and Management. I liked the campus and the surrounding area of Twente and it was a great place to do my sports activities as well with the people that I have met over the years. I would like to thank some people for supporting me in completing my thesis. My Supervisor Engin helped me a lot during writing of my thesis. Unfortunately all of our meetings where via Skype because of the coronavirus situation, however I liked the meetings. His feedback was very helpful and I always looked forward to our conversations. I would also like to thank Ipek for being the second supervisor and reading my entire report and given solid feedback as well. I did my internship at Ovimex in Deventer. I would like to thank all the people who work there, I could always ask and talk with everyone. And I would like to thank my supervisor from Ovimex, Roland Wolters, for the opportunity. Finally I will thank my parents and my sister for helping me with everything. Niels Leliveld Enschede, 4-11-2020 iv TABLE OF CONTENTS Management Summary ............................................................................................................... ii Preface ......................................................................................................................................... iv Table of Contents ........................................................................................................................ v List of Tables ............................................................................................................................. vii List of Figures ........................................................................................................................... viii Glossary ....................................................................................................................................... x 1 Introduction .......................................................................................................................... 1 Context .......................................................................................................................... 1 Research Motivation ...................................................................................................... 2 Problem identification .................................................................................................... 3 Solution approach.......................................................................................................... 5 Research scope and limitations .................................................................................... 5 Research objective ........................................................................................................ 6 Research methodology ................................................................................................. 7 2 Context Analysis ................................................................................................................. 8 Process description ....................................................................................................... 8 Factory layout .............................................................................................................. 13 Machines and workstations ......................................................................................... 15 Product order types ..................................................................................................... 16 Arrival rates of jobs ...................................................................................................... 18 Conclusions on the context analysis ........................................................................... 22 3 Literature research ............................................................................................................ 24 Models ......................................................................................................................... 24 Probability distributions ............................................................................................... 30 Goodness-of-fit test ....................................................................................................