Towards Zero Defect and Zero Waste Manufacturing by Implementing Non-Destructive Inspection Technologies

This study aims to provide an overview of Zero Defect, Zero Waste, and non-destructive inspection technologies (NDITs), which play a crucial role in the early detection of defects and material consumption in industrial processes. Integrating Zero Defect and Zero Waste strategies with non-destructive...

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Veröffentlicht in:Journal of Manufacturing and Materials Processing 2025-01, Vol.9 (2), p.29
Hauptverfasser: Lario, Joan, Mateos, Javier, Psarommatis, Foivos, Ortiz, Ángel
Format: Artikel
Sprache:eng
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Zusammenfassung:This study aims to provide an overview of Zero Defect, Zero Waste, and non-destructive inspection technologies (NDITs), which play a crucial role in the early detection of defects and material consumption in industrial processes. Integrating Zero Defect and Zero Waste strategies with non-destructive inspection technologies supports Industry 4.0 by using advanced sensors, robotics, and AI to create smart manufacturing systems that optimise resources and improve quality. The analysis covers the main functionalities, applications and technical specifications of several NDITs to automate the inspection of industrial processes. It also discusses both the benefits and limitations of these techniques through benchmarking. Deploying inspection as a service solution based on NDITs with data-driven decision-making Artificial Intelligence for in-process or in-line inspection policies increases production control by reducing material waste and energy use, and by optimising the final factory cost. After a comprehensive assessment, this paper aims to examine and review recent developments in the Zero Defects and Zero Waste field due to emerging non-destructive inspection systems, and their combination with other technologies, such as augmented reality. Advances in sensors, robotics, and decision-making processes through Artificial Intelligence can increase Human–Robot Collaboration in the inspection process by enhancing quality assurance during production.
ISSN:2504-4494
2504-4494
DOI:10.3390/jmmp9020029