Electronic waste (e-waste) represents one of the world's most significant environmental challenges, with over 50 million tons generated annually. A key component is the management of Printed Circuit Boards (PCBs), which are integral components of electronic devices and have an operational lifespan of 15 years. However, on average, electrical equipment is discarded after 5 years due to individual defects, prompting the EU to enforce regulations supporting the right to repair. Although industrial remanufacturing of PCBs could be a viable solution, it is not currently feasible due to the complex inspection process required. This paper presents a novel inspection process approach based on data fusion of thermography, current measurement and optical inspection using artificial intelligence. The result is intelligent diagnostics in less time and with lower investment costs. In addition to the concept, initial investigations with real industrial applications in the field of automation are presented.

Integrative inspection methodology for enhanced PCB remanufacturing using artificial intelligence / Stamer, Florian; Jachemich, Rouven; Puttero, Stefano; Verna, Elisa; Galetto, Maurizio. - ELETTRONICO. - 132:(2025), pp. 227-232. (Intervento presentato al convegno 12th CIRP Global Web Conference, CIRPe 2024 tenutosi a USA nel 2024) [10.1016/j.procir.2025.01.038].

Integrative inspection methodology for enhanced PCB remanufacturing using artificial intelligence

Puttero, Stefano;Verna, Elisa;Galetto, Maurizio
2025

Abstract

Electronic waste (e-waste) represents one of the world's most significant environmental challenges, with over 50 million tons generated annually. A key component is the management of Printed Circuit Boards (PCBs), which are integral components of electronic devices and have an operational lifespan of 15 years. However, on average, electrical equipment is discarded after 5 years due to individual defects, prompting the EU to enforce regulations supporting the right to repair. Although industrial remanufacturing of PCBs could be a viable solution, it is not currently feasible due to the complex inspection process required. This paper presents a novel inspection process approach based on data fusion of thermography, current measurement and optical inspection using artificial intelligence. The result is intelligent diagnostics in less time and with lower investment costs. In addition to the concept, initial investigations with real industrial applications in the field of automation are presented.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2999521
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