Markov modeling and analysis of multi-stage manufacturing systems with remote quality information feedback

Modeling and analysis of multi‐stage manufacturing systems (MMSs) for product quality propagation have attracted a great deal of attention recently. Due to cost and resources constraints, MMSs do not always have ubiquitous inspection, and MMSs with remote quality information feedback (RQIF, i.e., quality inspection operation is conducted at the end of the production line) are widely applied. This paper develops a Markov model to analyze quality propagation in MMSs with RQIF. Analytical expressions of the final product quality are derived and the monotonicity properties are investigated. A quality bottleneck identification method is explored based on the proposed Markov model. The results of case study demonstrate the effectiveness of the proposed model.