BATCH SCHEDULING MODEL ON A THREE-STAGE FLOWSHOP WITH THE SEQUENCE OF JOB PROCESSOR BATCH PROCESSOR JOB PROCESSOR TO MINIMIZE TOTAL ACTUAL FLOW TIME

• Main Author: Az Zahro, Shafira
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/66817
• Institution: Institut Teknologi Bandung

This study discusses a batch scheduling model on a three-stage flowshop with the sequence of job processor, batch processor, and job processor that process multiple items. In stage 1 products are processed with a common machine as a job processor, then in stage 2 different types of products can be processed simultaneously with a common machine as a batch processor and the batch size is limited by the capacity of the batch processor, and in stage 3 products are processed based on the type of product with dedicated parallel machines as a job processor. All finished products should be delivered at a common due date. The performance criteria used in this study is the minimization of the total actual flow time. The decision variables in this study are the number, size, sequence, starting time of the production batch (vacuum, sterilization, and labeling). Problems in a batch scheduling model on a three-stage flowshop with the sequence of job processor batch processor job processor to minimize total actual flow time are solved by developing a proposed algorithm and a heuristic algorithm. The process of finding a solution with the proposed algorithm is carried out using the enumeration process and using Lingo 19.0 software. The process of finding a solution with the heuristic algorithm is carried out by first determining the number and size of the batch, then determining the sequence of the batch with the help of Lingo 19.0 software. The result of the numerical example with the proposed algorithm shows that the model can be solved and produce the best solution. The result of the numerical example with the heuristic algorithm does not guarantee that the resulting solution is the best solution, but it could solve a larger problem case. The results of model testing indicate that the model is sensitive to changes in the number of demand parameter and the number of product type parameter, not too sensitive to changes in the capacity of the batch processor parameter, and not sensitive to changes in the due date parameter.