Robust condition-based production and maintenance planning for degradation management

• 成果类型: Article
• 署名作者: Sun, Qiuzhuang; Chen, Piao; Wang, Xin; Ye, Zhi-Sheng
• 署名单位: University of Sydney; Zhejiang University; Shanghai Jiao Tong University; Shanghai Jiao Tong University; National University of Singapore; Zhejiang University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.14071
• 发表日期: 2023
• 页码: 3951-3967
• 关键词: condition monitoring; degradation management; production control; robust optimization

摘要

We study the robust production and maintenance control for a production system subject to degradation. A periodic maintenance scheme is considered, and the system production rate can be dynamically adjusted before maintenance, serving as a proactive way of degradation management. Optimal control of the degradation rate aims to strike a balance between the risk of failure and the production profit. We first consider the scenario in which the degradation rate increases linearly with the production rate. Different from the existing literature that posits a parametric stochastic degradation process, we suppose that the degradation increment during a period lies in an uncertainty set, and our objective is to minimize the maintenance cost in the worst case. The resulting model is a robust mixed-integer linear program. We derive its robust counterpart and establish structural properties of the optimal production plan. These properties are then used for real-time condition-based control of the production rate through reoptimization. The model is further generalized to the nonlinear production-degradation relation. Based on a real production-degradation dataset from an extruder system, we conduct comprehensive numerical experiments to illustrate the application of the model. Numerical results show that our model significantly outperforms existing methods in terms of the mean and variance of cost rate when degradation model misspecification is presented.