A Balanced Optimization Approach to Inspection and Disassembly in Multi-Stage Manufacturing Systems

Abstract

This study addresses the critical decision-making challenge of optimizing inspection (of production components and finished products) and disassembly (of defective items) strategies within manufacturing systems. Existing research primarily focuses on isolated inspection or disassembly policies, lacking an integrated computational framework. To bridge this gap, we develop a novel multi-stage optimization model capturing the interdependencies between inspection and disassembly decisions. An exhaustive enumeration algorithm is employed to systematically evaluate all feasible decision combinations across stages, with the primary objective of maximizing overall manufacturing throughput capacity. The model explicitly incorporates the impact of defects and resource constraints on system performance. Furthermore, sensitivity analysis is conducted to identify key operational parameters that significantly influence the optimal decision strategy. The results demonstrate that the proposed model and algorithmic approach effectively determine computationally efficient production control strategies, leading to enhanced system throughput and product quality robustness.