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Robust condition‐based production and maintenance planning for degradation management

Qiuzhuang Sun1; Piao Chen2; Xin Wang3,4; Zhi‐Sheng Ye5

1 School of Mathematics and Statistics, University of Sydney, Sydney, Australia · 2 ZJUI Institute, Zhejiang University, Haining, China · 3 Sino‐US Global Logistics Institute, Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China · 4 Data‐Driven Management Decision Making Lab, Shanghai Jiao Tong University, Shanghai, China · 5 Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore

Production and Operations Management 2023

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.

DOI
10.1111/poms.14071
Volume
32 (12)
Pages
3951-3967
Language
en
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Sources
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