Effects of an Inaccurate Sorting Procedure on Optimal Procurement and Production Decisions in a Remanufacturing System

Abstract

Under the uncertainty of market demand and quality of returns, sorting prior to disassembly is effective for timely obtaining information about the remanufacturability of used products. In this article, we assume that the remanufacturable fraction of used products is a random variable and introduce an inaccurate sorting procedure of used products prior to disassembly. Then, three two-stage optimization models are formulated to maximize the expected profits of a remanufacturer in a single period with used products and/or new parts as inputs to meet the stochastic market demand. Moreover, the article provides a case study to explore the optimal decisions under different scenarios and analyzes the effects of parameters, such as the unit disassembly cost, unit sorting cost, and proportion of sorting errors. Finally, the results indicate that whether remanufacturing with sorting is more profitable than that without sorting mainly depends on the sorting accuracy and the relative value between disassembly cost and sorting cost. When considering or not considering a long lead time of new parts, the effects of sorting errors on procurement policies are different. A long lead time will result in lower expected profits. Finally, the diverse types of classification errors have different influences on procurement policies and corresponding expected profit.

Keywords:

• Procurement and Production Decisions
• Remanufacturing
• Two-Stage Optimization Model
• Value of Information

EMJ Focus Areas:

• Supply Chain Management, Operations Management, Decision Making

Acknowledgment

The authors are very thankful for the constructive comments and suggestions from the editors and reviewers.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (NSFC): [Grant Numbers 71571042, 71271054, 71501046] and Research Support Project for Doctoral Teachers in Jiangsu Normal University: [Grant Number 17XLW015].

Notes on contributors

Weida Chen

Weida Chen received his PhD in management science and engineering from Southeast University in 2002. He is currently a professor in the Department of Management Science and Engineering at the Southeast University. His research interests are in production and operations management, supply chain management, and remanufacturing management.

Yongjian Wang

Yongjian Wang is a lecturer in the Business School at Jiangsu Normal University. He received his PhD in Management Science and Engineering from Southeast University in 2017. His research interests are in production and operations management, supply chain management, financial management, and systems simulation modeling and optimization.

Peng Zhang

Peng Zhang received a Master’s of Management in Business Management from Central University of Finance and Economics. Currently, he is a lecturer in the School of Foreign Languages at Jiangsu Normal University and pursuing a PhD in Management Science and Engineering at Southeast University. His research interests are in internet finance, supply chain finance, and green finance.

Xu Chen

Xu Chen is an undergraduate student in Business Administration at the Hefei University of Technology. Her research interests are in production management and computer application.