Journal
JOURNAL OF CLEANER PRODUCTION
Volume 248, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.119299
Keywords
multi-life-cycle remanufacturing; Sustainable products; Big data; CPS-Digital-twin(CPSDT); IoT-cloud; Reconfiguration
Categories
Funding
- National Key Research and Development Project of China [2018AAA0101800]
- Technological Innovation and Application Development Project of Chongqing [cstc2019jscx-mbdxX0056]
- National Defense Basic Research Project of China [JCKY2016204A502]
- open research fund project of State Key Laboratory of Complex Product Intelligent Manufacturing System Technology [QYYE602]
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Remanufacturing is deemed to be an effective method for recycling resources, achieving sustainable production. However, little importance of remanufacturing has been attached in PLM. Surely, there are many problems in implementation of the remanufacturing strategy, such as inability to effectively reduce uncertainty, lack of product multi-life-cycle remanufacturing process tracking management, lack of smart enabling technology application in the full lifecycle that focusing on multi-life-cycle remanufacturing. After analyzing the reasons, through integrating smart enabling technologies, a new PLM paradigm focusing on the multi-life-cycle remanufacturing process: Big Data driven Hierarchical Digital Twin Predictive Remanufacturing (BDHDTPREMfg) is proposed. And the definition of BDHDTPREMfg is proposed. A big data driven layered architecture and the hierarchical CPS-Digital-Twin(CPSDT) reconfiguration control mechanism of BDHDTPREMfg are respectively developed. Then, this paper presents an application scenario of BDHDTPREMfg to validate the feasibility and effectiveness. Based on the above application analysis, the benefits of penetrating BDHDTPREMfg into the entire lifecycle are demonstrated. The summary of this paper and future research work is discussed in the end. (C) 2019 Elsevier Ltd. All rights reserved.
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