A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring

作     者：Liu, Qingtao Shang, Ziyu Ding, Kai Lv, Jingxiang 

作者机构：Changan Univ Key Lab Rd Construct Technol & Equipment MoE Xian 710064 Shaanxi Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Peoples R China Cardiff Univ Sch Engn Inst Energy Cardiff CF24 3AA S Glam Wales 

出 版 物：《IEEE ACCESS》 (IEEE Access)

年 卷 期：2019年第7卷

页      面：70046-70058页

核心收录：

基　　金：National Natural Science Foundation of China [51305042, 51705030] Shaanxi Natural Science Foundation [2018JM5108] Fundamental Research Funds for the Central Universities 

主　　题：Service-oriented remanufacturing recovery timing prediction remote condition monitoring Weibull distribution gene expression programming 

摘      要：Remanufacturing is generally regarded as a key technology to implement cleaner production. However, in traditional remanufacturing, scrap products are recycled and remanufactured after their performance declines sharply. This passive approach easily arises many problems such as increases of remanufacturing cost, unstable product quality, and unsatisfactory customer demand, which brought great challenges to the remanufacturing industry. To address these challenges, a novel framework, namely service-oriented remanufacturing (SORM), is proposed to improve the overall efficiency of remanufacturing. Contrast to the traditional mode, SORM actively recovers in-service products at the optimal recovery time based on their real-time performance obtained by remote monitoring. The operational logic and implementation path of SORM is firstly discussed. Then the recovery timing prediction (RTP) model, as the core issue of the SORM, is presented to figure out the optimal recovery time of in-service products. Moreover, a comprehensive method combining a two-parameter Weibull distribution (TPWD) and gene expression programming (GEP) is developed to solve the model. The example of excavator remanufacturing illustrates the feasibility of the SORM. Finally, the key findings and managerial implications from application results and discussion are summarized, which provides the theoretical guidance and technical support for better sustainable development.