A Knowledge Based System for Intelligent Planning of e-motors Remanufacturing Activities

The implementation of circular economy guidelines and new greener policies introduced by governments and agencies have underscored significant challenges in manufacturing systems fexibility. These challenges are particularly severe when considering de-remanufacturing processes, where unpredictable, product-specific variability plays a crucial role. Effiectively managing this input variability requires flexible and reconfg-urable systems that integrate both hardware and software, while meeting production standards and customer expectations. As products reach the end of their operational life and return for remanufacturing, their nominal characteristics are lost, requiring customized disassembly and remanufacturing plans tailored to the condition of each component. To address this need, this work proposes a knowledge-based system for generating activity schedules for de-remanufacturing, within the context of short-term production planning methods. A case study focused on the de-remanufacturing of electric motors is conducted to test and validate the effectiveness of the proposed approach.

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Publication Details

Journal
Procedia CIRP
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procir.2025.03.063
Citations
1
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
1.24

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article

A Knowledge Based System for Intelligent Planning of e-motors Remanufacturing Activities

Maria Chiara Magnanini, Tullio Tolio, Matteo Zanovello
1 citations
Procedia CIRP
Manufacturing Process and Optimization
1.24
article

A Knowledge Based System for Intelligent Planning of e-motors Remanufacturing Activities

Maria Chiara Magnanini, Tullio Tolio, Matteo Zanovello
article en
1 citations

Abstract

The implementation of circular economy guidelines and new greener policies introduced by governments and agencies have underscored significant challenges in manufacturing systems fexibility. These challenges are particularly severe when considering de-remanufacturing processes, where unpredictable, product-specific variability plays a crucial role. Effiectively managing this input variability requires flexible and reconfg-urable systems that integrate both hardware and software, while meeting production standards and customer expectations. As products reach the end of their operational life and return for remanufacturing, their nominal characteristics are lost, requiring customized disassembly and remanufacturing plans tailored to the condition of each component. To address this need, this work proposes a knowledge-based system for generating activity schedules for de-remanufacturing, within the context of short-term production planning methods. A case study focused on the de-remanufacturing of electric motors is conducted to test and validate the effectiveness of the proposed approach.

Procedia CIRPVol. 134
Politecnico di Milano (IT)
HORIZON EUROPE Global Challenges and European Industrial Competitiveness
Sustainable cities and communities
Openalex Percentile: Top 18%
Manufacturing Process and Optimization
1.24
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