PERANCANGAN SISTEM PENJADWALAN UNTUK FLEXIBLE FLOW SHOP DENGAN ALGORITMA LONGEST PROCESSING TIME DAN SEARCH-AND-PRUNE PADA PT ELANG PERDANA TYRE INDUSTRY

• Main Author: Patricia, Angelina
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/81783
• Institution: Institut Teknologi Bandung

PT Elang Perdana Tire Industry is a manufacturing company that focuses on car tires production with a Make To Stock (MTs) business process and a pull system for its production system. in between June to October of 2023, the production average is only able to meet 75.80% of the demand, which can be caused by many factors, such as large production makespan, limited machine capacity and various types of tire sizes, that may lead to the complexity of the production scheduling process. This complexity in scheduling may cause the existing system’s schedule to be less effective. Therefore, a capable scheduling system is needed to minimize production makespan that will have an effect on increasing the machine utility and production demand fulfillment. As for PT Elang Perdana Tyre Industry’s case, the production flow to be focused on is a flexible flow shop. To accommodate this type of production flow, The method proposed in this study is a heuristic method by Sriskandarajah and Sethi that combines the Longest Processing Time (LPT) algorithms and Search-and-Prune algorithms. The Longest Processing Time (LPT) algorithm will be used in assigning jobs and the Search-and-Prune algorithm will be used in sequencing jobs. This method was able to meet the conditions of the problem and does not require too much computing time, in the mean time, is able to produce a solution close enough to optimal. Hence, this particular method is chosen to be used in designing the scheduling system at PT Elang Perdana Tire Industry. The scheduling algorithm in this research is able to produce a solution in the form of 3 large flow schedules with 98 flows for radial type tires and 7 flows for bias type tires.Based on the results of the study, the solution obtained was able to minimize production makespan up to 30.01% when compared to actual conditions.it is possible as by minimizing idle time between jobs for each workstation, it will also minimizing the solution makespan.