TY - JOUR
T1 - Component-Oriented Reassembly in Remanufacturing Systems
T2 - Managing Uncertainty and Satisfying Customer Needs
AU - Wang, Yue
AU - Mendis, Gamini P.
AU - Peng, Shitong
AU - Sutherland, John W.
N1 - Funding Information:
The authors gratefully acknowledge the support of the Indiana Next Generation Manufacturing Competitiveness Center (IN-MaC) and the Discovery Park Big Idea Challenge Grant (F.00038152.06.005) at Purdue University.
Publisher Copyright:
Copyright © 2019 by ASME.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Remanufacturing has recently received significant interest due to its environmental and economic benefits. Traditionally, the reassembly processes in remanufacturing systems are managed using a product-oriented model. When a product is returned and disassembled, the used components may be processed incorrectly, and the quality of the remanufactured products may not meet customer needs. To solve these problems, a component-oriented reassembly model is proposed. In this model, returned components are inspected and assigned scores according to their quality/function and categorized in a reassembly inventory. Based on the reassembly inventory, components are paired under the control of a reassembly strategy, and these pairs are then assembled into reassembly chains. Each chain represents a product. To evaluate the performance of different reassembly strategies under uncertain conditions, we describe the reassembly problem using an agent-environment system. The platform is modeled as a Markov decision process (MDP), and a reassembly score iteration algorithm (RSIA) is developed to identify the optimal reassembly strategy. The effectiveness of the method is demonstrated via a case study using the reassembly process of diesel engines. The results of the case study show that the component-oriented reassembly model can improve the performance of the reassembly system by 40%. A sensitivity analysis is carried out to evaluate the relationship between the parameters and the performance of the reassembly system. The component-oriented model can reassemble products to meet a larger variety of customer needs, while simultaneously producing better remanufactured products.
AB - Remanufacturing has recently received significant interest due to its environmental and economic benefits. Traditionally, the reassembly processes in remanufacturing systems are managed using a product-oriented model. When a product is returned and disassembled, the used components may be processed incorrectly, and the quality of the remanufactured products may not meet customer needs. To solve these problems, a component-oriented reassembly model is proposed. In this model, returned components are inspected and assigned scores according to their quality/function and categorized in a reassembly inventory. Based on the reassembly inventory, components are paired under the control of a reassembly strategy, and these pairs are then assembled into reassembly chains. Each chain represents a product. To evaluate the performance of different reassembly strategies under uncertain conditions, we describe the reassembly problem using an agent-environment system. The platform is modeled as a Markov decision process (MDP), and a reassembly score iteration algorithm (RSIA) is developed to identify the optimal reassembly strategy. The effectiveness of the method is demonstrated via a case study using the reassembly process of diesel engines. The results of the case study show that the component-oriented reassembly model can improve the performance of the reassembly system by 40%. A sensitivity analysis is carried out to evaluate the relationship between the parameters and the performance of the reassembly system. The component-oriented model can reassemble products to meet a larger variety of customer needs, while simultaneously producing better remanufactured products.
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U2 - 10.1115/1.4042150
DO - 10.1115/1.4042150
M3 - Article
AN - SCOPUS:85059487672
SN - 1087-1357
VL - 141
JO - Journal of Manufacturing Science and Engineering, Transactions of the ASME
JF - Journal of Manufacturing Science and Engineering, Transactions of the ASME
IS - 2
M1 - 021005
ER -