PRODUCTION CONTROL UNDER PROCESS QUEUE TIME CONSTRAINTS IN SYSTEMS WITH A COMMON DOWNSTREAM WORKSTATION

Authors

  • Yu-Ting Chen National Taiwan University
  • Cheng-Hung Wu National Taiwan University
  • Yin-Jing Tien
  • Cheng-Juei Yu

DOI:

https://doi.org/10.23055/ijietap.2016.23.5.2950

Keywords:

production control, equipment health, queue time constraints, common machines

Abstract

This research develops a dynamic scheduling method for multi-product production systems under process queue time (PQT) constraints, wherein waiting time between consecutive processing steps is constrained by predefined upper limits. If the waiting time of a work-in-process (WIP) violates the corresponding PQT constraint, the WIP may be scrapped or the yield quality will deteriorate seriously. When machines are unreliable, random machine failures cause high cycle time variance and significantly increase the risk of violating PQT constraints. Therefore, for production systems with PQT constraints, a robust dynamic scheduling method with real time machine reliability considerations is critical.

In this research, multi-product production systems with a common downstream workstation are considered. PQT constraints before the downstream workstation are assumed. The Markov decision process model is developed to address production control problems, and the objective is to minimize total expected waiting and scrap costs. Simulation results show the robustness of the proposed control method. On average, the proposed method reduces production costs by 20% and improves system throughput by 2%.

Author Biography

Cheng-Hung Wu, National Taiwan University

Associate Professor, Institute of Industrial Engineering/Dept. of Mechanical Engineering/Dept. of Business Administration, National Taiwan University

Published

2017-01-06

How to Cite

Chen, Y.-T., Wu, C.-H., Tien, Y.-J., & Yu, C.-J. (2017). PRODUCTION CONTROL UNDER PROCESS QUEUE TIME CONSTRAINTS IN SYSTEMS WITH A COMMON DOWNSTREAM WORKSTATION. International Journal of Industrial Engineering: Theory, Applications and Practice, 23(5). https://doi.org/10.23055/ijietap.2016.23.5.2950

Issue

Section

Special Issue: 2015 International Symposium on Semiconductor Manufacturing Intelligence