The purpose of this article is to balance product quality requirements and maintenance costs. Considering that manufacturing system is deteriorating and its maintenance situations are complex, maintenance strategies, control chart parameters, and sampling rules are designed for different stages of the system life cycle. A searching algorithm combined particle swarm optimization with heuristic rules is introduced to solve this integrated optimization problem. A numerical example study is implemented to validate the effectiveness and rationality. A comparison model is built to illustrate the advantages of the proposed model. Sensitivity analysis is also performed to investigate the effect of nine cost factors.

本文的目的是平衡产品质量要求和维护成本。考虑到制造系统正在恶化并且其维护状况复杂，因此针对系统生命周期的不同阶段设计了维护策略，控制图参数和采样规则。提出了一种结合启发式规则的粒子群优化搜索算法来解决该集成优化问题。通过数值算例研究验证了有效性和合理性。建立了一个比较模型来说明所提出模型的优点。还进行了敏感性分析，以调查九种成本因素的影响。