Imperfect economic production quantity models under predictive maintenance and reworking

Abstract

Due to the popularity of Industry 4.0, many companies have begun to develop intelligent production systems and perform predictive maintenance. These innovations monitor production systems by using sensors and data analysis, and they maintain production systems before they become ‘out of control'. This paper develops imperfect economic production quantity (EPQ) models that consider predictive maintenance and reworking of defective products. The objective is to determine the optimal predictive maintenance effort and production runtime and minimise the total expected cost. Two situations are considered: (1) the production system continuously producing products when it shifts to the out-of-control state and (2) the production system stops producing when it shifts to the out-of-control state. We formulate the cost functions and provide algorithms to solve the problems. A numerical study is conducted to illustrate our models and the solution procedure. We also discuss the influence of system parameters (such as predictive and corrective maintenance costs) on the predictive maintenance effort and production runtime decisions and total cost. The results could be used by managers as a reference when consider imperfect economic production quantity models under predictive maintenance and reworking.

KEYWORDS:

• Industry 4.0
• production Modelling
• inventory control
• predictive maintenance
• corrective maintenance
• reworking

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This paper is supported in part by the Ministry of Science and Technology in Taiwan under grant 105-2221-E-011-099-MY3 and 108-2636-E-011-004.

Notes on contributors

Yu-Chung Tsao

Yu-Chung Tsao is currently a Professor in the Department of Industrial Management at National Taiwan University of Science and Technology. His research interests are Supply Chain and Logistics Management, Production and Operations Management, Decision Sciences, Business Analysis, and Revenue Management.

Pei-Ling Lee

Pei-Ling Lee is currently a researcher in the Department of Industrial Management, National Taiwan University of Science and Technology. Her research interests are Supply Chain Management and Enterprise Resources Planning.

Lu-Wen Liao

Lu-Wen Liao is currently an Assistant Professor in the Department of Business Management, National Taichung University of Science and Technology. His current research interests include Supply Chain Management, Enterprise Resources Planning, and Scheduling.

Qinhong Zhang

Qinhong Zhang is currently an Associate Professor in the Sino-US Global Logistics Institute, Shanghai Jiao Tong University. His current research interests include Supply Chain Management, Reverse Logistics, and Interface between Operations Management and Finance.

Thuy-Linh Vu

Thuy Linh Vu is currently a Postdoctoral researcher in the Department of Industrial Management, National Taiwan University of Science and Technology. Her research interests are Supply Chain Management and Operations Management.

Jim Tsai

Jim Tsai received his Master degree from the Department of Industrial Management, National Taiwan University of Science and Technology.