2nd Asia Pacific International Conference on Industrial Engineering and Operations Management

A Flow Shop Batch Scheduling Model with Part Deterioration and Operator Learning-Forgetting Effects to Minimise Total Actual Flow Time

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Track: Production Planning and Management
Abstract

This paper proposes a batch scheduling model where two time-changing effects simultaneously occur, i.e., parts deteriorating and operator learning-forgetting effects. A mathematical model is proposed for the problem where the decision variables are the number of batches, batch sizes, and a schedule of the resulting batches to minimize total actual flow time. A proposed algorithm is developed by trying different numbers of batches, starting from one and then increasing it one by one until the objective function value does not improve anymore. Numerical examples show that the faster operators learn, the lower the optimal number of batches and the lower the optimal total actual flow time. Second, the faster parts deteriorate, the higher the optimal number of batches and the higher the optimal total actual flow time. Finally, the model divides parts into small batches to prevent the processing time from increasing due to part deterioration.

Published in: 2nd Asia Pacific International Conference on Industrial Engineering and Operations Management, Surakarta, Indonesia

Publisher: IEOM Society International
Date of Conference: September 13-16, 2021

ISBN: 978-1-7923-6129-6
ISSN/E-ISSN: 2169-8767