A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring
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 remanufa...
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8723174/ |
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doaj-541a604f1bad46c3be73f957908ef4e62021-03-30T00:11:50ZengIEEEIEEE Access2169-35362019-01-017700467005810.1109/ACCESS.2019.29191568723174A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition MonitoringQingtao Liu0https://orcid.org/0000-0002-0764-0188Ziyu Shang1Kai Ding2https://orcid.org/0000-0002-8121-0258Jingxiang Lv3Key Laboratory of Road Construction Technology and Equipment of MoE, Chang’an University, Xi’an, ChinaKey Laboratory of Road Construction Technology and Equipment of MoE, Chang’an University, Xi’an, ChinaKey Laboratory of Road Construction Technology and Equipment of MoE, Chang’an University, Xi’an, ChinaKey Laboratory of Road Construction Technology and Equipment of MoE, Chang’an University, Xi’an, ChinaRemanufacturing 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.https://ieeexplore.ieee.org/document/8723174/Service-oriented remanufacturingrecovery timing predictionremote condition monitoringWeibull distributiongene expression programming |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Qingtao Liu Ziyu Shang Kai Ding Jingxiang Lv |
| spellingShingle |
Qingtao Liu Ziyu Shang Kai Ding Jingxiang Lv A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring IEEE Access Service-oriented remanufacturing recovery timing prediction remote condition monitoring Weibull distribution gene expression programming |
| author_facet |
Qingtao Liu Ziyu Shang Kai Ding Jingxiang Lv |
| author_sort |
Qingtao Liu |
| title |
A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring |
| title_short |
A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring |
| title_full |
A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring |
| title_fullStr |
A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring |
| title_full_unstemmed |
A Service-Oriented Remanufacturing Framework With Recovery Timing Prediction Based on Remote Condition Monitoring |
| title_sort |
service-oriented remanufacturing framework with recovery timing prediction based on remote condition monitoring |
| publisher |
IEEE |
| series |
IEEE Access |
| issn |
2169-3536 |
| publishDate |
2019-01-01 |
| description |
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. |
| topic |
Service-oriented remanufacturing recovery timing prediction remote condition monitoring Weibull distribution gene expression programming |
| url |
https://ieeexplore.ieee.org/document/8723174/ |
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