A Product Evolution Rules Based Method for Retired Mechanical Product Demand Acquisition

Wenbin Zhou, Xuhui Xia, Lei Wang (), Zelin Zhang and Baotong Chen
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Wenbin Zhou: Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China
Xuhui Xia: Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China
Lei Wang: Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China
Zelin Zhang: Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China
Baotong Chen: Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China

Sustainability, 2022, vol. 14, issue 23, 1-17

Abstract: Accurate acquisition of retired mechanical products demand (RMPD) is the basis for realizing effective utilization of remanufacturing service data and improving the feasibility of remanufacturing schemes. Some studies have explored product demands, making product demands an important support for product design and development. However, these studies are obtained through the transformation of customer and market demand information, and few studies are studied from a product perspective. However, remanufacturing services for retired mechanical products (RMP) must consider the impact of the failure characteristics. Consequently, based on the generalized growth of RMP driven by the failure characteristics, the concept of RMPD is proposed in this paper. Then, the improved ant colony algorithm is proposed to mine the generalized growth evolution law of RMP from the empirical data of remanufacturing services, and the RMPD is deduced based on the mapping relationship between the product and its attributes. Finally, the feasibility and applicability of the proposed method are verified by obtaining the demand for retired rolls. In detail, the results show that the proposed method can obtain the RMPD accurately and efficiently, and the performance of the method can be continuously optimized with the accumulation of empirical data.

Keywords: retired mechanical product demand (RMPD); demand acquisition; generalized growth; evolutionary rule (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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