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Association rules mining between service demands and remanufacturing services

Published online by Cambridge University Press:  26 October 2020

Wenbin Zhou ,
Xuhui Xia ,
Zelin Zhang Open the ORCID record for Zelin Zhang [Opens in a new window]  and
Lei Wang
Wenbin Zhou
Affiliation:
Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan430081, China
Xuhui Xia
Affiliation:
Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan430081, China
Zelin Zhang*
Affiliation:
Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan430081, China
Lei Wang
Affiliation:
Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan430081, China
*
Author for correspondence: Zelin Zhang, E-mail: zhangzelin@wust.edu.cn; Lei Wang, E-mail: candywang@wust.edu.cn
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Abstract

The potential relationship between service demands and remanufacturing services (RMS) is essential to make the decision of a RMS plan accurately and improve the efficiency and benefit. In the traditional association rule mining methods, a large number of candidate sets affect the mining efficiency, and the results are not easy for customers to understand. Therefore, a mining method based on binary particle swarm optimization ant colony algorithm to discover service demands and remanufacture services association rules is proposed. This method preprocesses the RMS records, converts them into a binary matrix, and uses the improved ant colony algorithm to mine the maximum frequent itemset. Because the particle swarm algorithm determines the initial pheromone concentration of the ant colony, it avoids the blindness of the ant colony, effectively enhances the searchability of the algorithm, and makes association rule mining faster and more accurate. Finally, a set of historical RMS record data of straightening machine is used to test the validity and feasibility of this method by extracting valid association rules to guide the design of RMS scheme for straightening machine parts.

Keywords

Association rulesdata miningremanufacturing servicesservice scheme design
Type
Research Article
Information
AI EDAM , Volume 35 , Special Issue 2: Thematic Collection: Smart Design of Smart Systems , May 2021 , pp. 240 - 250
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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