Work

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

Year: 2025

Type: article

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.

Source: Procedia CIRP

DOI: 10.1016/j.procir.2025.03.063

Authors: Matteo Zanovello, Tullio Tolio, Maria Chiara Magnanini

Institution: Politecnico di Milano

Language: English

Topic: Sustainable Supply Chain Management

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Responsible consumption and production, Industry, innovation and infrastructure

Open Access status: diamond

Funders: European Commission, HORIZON EUROPE Global Challenges and European Industrial Competitiveness