An Optimization Model for Manufacturing Systems in an Uncertain Environment Available to Purchase

This paper examines a flexible job shop problem that considers dynamic events, such as stochastic job arrivals, uncertain processing times, unexpected machine breakdowns and the possibility of processing flexibility. To achieve this goal, a new agent-based adaptive control system has been developed at the factory level, along with advanced decision-making strategies that provide responsive factories with adaptation and reconfiguration capabilities and advanced complementary scheduling abilities. The aim is to facilitate operational flexibility and increase productivity as well as offer strategic advantages such as analysis of factory development options by simulation. The feasibility of the proposed system is demonstrated by simulation under various experimental settings, among them shop utilization level, due date tightness and breakdown level.