A Predictive Control Model of Bernoulli Production Line with Rework Loop for Real-Time WIP Optimization in Permutation Flowshop

Abstract

Permutation flowshop design and optimization are crucial in industry as they have a direct impact on production scheduling and efficiency. The ultimate goal is to model the production system (PSM) based on revealing the fundamental principles of the production process, and to schedule or reschedule production release plans in real time without interrupting work-in-progress (WIP). Most existing PSMs are focused on static production processes which fail to describe the dynamic relationships between machines and buffers. Therefore, this paper establishes a PSM to characterize both the static and transient behaviors of automatic and manual machines in the permutation flowshop manufacturing system. Building upon the established PSM, based on Bernoulli’s theory, discrete event model predictive control is proposed in this paper; its aim is to realize real-time optimization of production release plans without interfering with work-in-progress. According to the results of numerical examples, the discrete event model predictive control proposed in this paper is feasible and effective. The model established in this paper provides a theoretical basis for optimizing the effective operation of work-in-progress and replacement process systems.