This paper proposes a new model that integrates opportunistic maintenance and routine maintenance to enhance the effectiveness of predictive maintenance and inventory management in complex manufacturing systems subject to a reliability chance constraint. It considers both hard and soft failure modes and their mutual dependence. When a machine experiences a hard failure, an opportunistic maintenance policy is utilized on the machine’s components. When the soft failure degradation level of a machine component surpasses a threshold, imperfect preventive maintenance or replacement maintenance is carried out. The choice of component supplier, including OEM and aftermarket suppliers, significantly impacts the joint decision model. To improve the model’s realism and applicability, a random variable representing supplier availability intervals is introduced, reflecting a more nuanced understanding of supply chain dynamics. We develop a simulation optimization method to determine the degradation thresholds for opportunistic and regular maintenance, the component inventory policy, and supplier selection. The objective is to minimize the total maintenance and inventory cost, while ensuring a high level of system reliability. The proposed algorithm effectively addresses the system reliability chance constraint by formulating a surrogate model of the quantile of system downtime. A numerical study is conducted to verify the efficacy of the proposed model and to demonstrate the efficiency of the solution method in finding the optimal feasible solution. Furthermore, the influence of critical factors in the model on the optimal policy is analyzed to derive useful managerial insights.

中文翻译：

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可靠性机会约束下的预测性维护和库存管理集成模型

本文提出了一种集成机会性维护和日常维护的新模型，以提高受可靠性机会约束的复杂制造系统中预测性维护和库存管理的有效性。它考虑了硬失效模式和软失效模式以及它们的相互依赖性。当机器遇到硬故障时，将对机器的组件采用机会性维护策略。当机器部件的软故障劣化水平超过阈值时，将进行不完善的预防性维护或更换维护。组件供应商（包括 OEM 和售后市场供应商）的选择对联合决策模型有重大影响。为了提高模型的真实性和适用性，引入了一个表示供应商可用性区间的随机变量，反映了对供应链动态的更细致的理解。我们开发了一种仿真优化方法，以确定机会性和定期维护的退化阈值、组件库存策略和供应商选择。目标是最大限度地降低总维护和库存成本，同时确保高水平的系统可靠性。所提出的算法通过制定系统停机时间分位数的代理模型，有效地解决了系统可靠性机会约束。进行数值研究以验证所提模型的有效性，并证明求解方法在寻找最优可行解方面的效率。此外，分析模型中关键因素对最优政策的影响，以获得有用的管理见解。