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Optimizing efficiency and zero-defect manufacturing with in-process inspection: challenges, benefits, and aerospace application
University of Oslo, SIRIUS, Centre for Scalable Data Access, Gaustadalleen 23B, Oslo, 0373, Norway. Research Center on Production Engineering and Management (CIGIP), Universitat Politècnica de València, Spain.
Department of Mechanical Engineering, University of North Florida, Jacksonville, United States.
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
National Technical University of Athens, Institute of Communication and Computer Systems, Athens, Greece.
2024 (English)In: Procedia Computer Science, Elsevier B.V. , 2024, Vol. 232, p. 2857-2866Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a comprehensive study on the implementation of machine vision-enabled in-process quality inspection systems in machining operations. Our objective is to enable zero-defect manufacturing by maximizing efficiency and effectiveness in production processes. We utilize machine vision technology as a transformative tool, playing a vital role in our comparative analysis which reveals its superiority over traditional in-situ approaches in both ideal and challenging real-world scenarios. Through simulation, we demonstrate how machine vision improves the performance of in-line process systems. We also discuss substantial challenges of implementation, such as managing environmental contamination, optimizing machine coordination, accommodating a range of part sizes, and configuring effective coolant delivery systems. Our in-depth analysis of essential factors includes the robustness of machine vision equipment, operator training for machine vision technology, and cost-benefit analysis of its implementation. The research emphasizes machine vision's crucial role in transforming manufacturing setups and enhancing advanced automation systems. The study underscores the immense potential of machine vision in in-process quality inspection to significantly reduce production costs and time, fostering higher manufacturing sustainability and competitive advantage in the era of Industry 4.0.

Place, publisher, year, edition, pages
Elsevier B.V. , 2024. Vol. 232, p. 2857-2866
Keywords [en]
in-process inspection, Industry 4.0, Quality inspection, vision systems, ZDM, Zero Defect Manufacturing
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-66461DOI: 10.1016/j.procs.2024.02.102ISI: 001196800602088Scopus ID: 2-s2.0-85189794863OAI: oai:DiVA.org:mdh-66461DiVA, id: diva2:1852658
Conference
5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023, Lisbon, November 22-24, 2023
Available from: 2024-04-18 Created: 2024-04-18 Last updated: 2024-12-19Bibliographically approved

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Azamfirei, Victor

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