Big data driven Hierarchical Digital Twin Predictive Remanufacturing paradigm: Architecture, control mechanism, application scenario and benefits

Abstract 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.

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