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Title: | Development of an Intelligent Quality Management System for Micro Laser Welding: An Innovative Framework and Its Implementation Perspectives |
Authors: | Velázquez de la Hoz, JL Cheng, K |
Keywords: | laser micro-welding;in-process quality monitoring;welding quality;Industry 4.0;end-to-end integration;value chain networks |
Issue Date: | 26-Oct-2021 |
Publisher: | MDPI |
Citation: | Velázquez de la Hoz, J. L. and Cheng, K. (2021) ‘Development of an Intelligent Quality Management System for Micro Laser Welding: An Innovative Framework and Its Implementation Perspectives’, Machines, 9 (11), 252, pp. 1-21. doi: 10.3390/machines9110252. |
Abstract: | Laser micro-welding manufacturers face substantial challenges in verifying weldment quality, as the industry and applications are requiring increasingly the miniaturization and compactness of products. The problem is compounded by new stringent demands for personalized products at competitive, low costs and the highest quality levels. High-pressure equipment manufacturers, in particular, rely on ISO 3834:2021 to assure and demonstrate best welding practices but also to manage risks associated with liability issues. ISO 3834:2021, like all conventional quality management systems, offers a one-dimensional, quasi-static overview of welding quality that may fail to deal with these new challenges and underlying complexities required to deal effectively with process variability. This paper presents a framework for welding companies to integrate horizontally their suppliers and customers with their processes and products, which are also integrated vertically in the context of Smart Manufacturing or Industry 4.0. It is focused on the development of a smart quality management system for intelligent digitization of all company manufacturing and business processes. Furthermore, an innovative data-based welding quality management framework is described for laser micro-welding applications and their implementation perspectives. The research is driven by an inductive methodology and based on a seamless integration of engineering-oriented heuristic and empirical approaches that is appropriate for intelligent and autonomous quality management, given the lack of research in this niche, but increasingly important topic area. |
Description: | Data Availability Statement: No significant datasets were analyzed in this study or created to support it. |
URI: | https://bura.brunel.ac.uk/handle/2438/23621 |
DOI: | https://doi.org/10.3390/machines9110252 |
Other Identifiers: | ORCiD: José Luis Velázquez de la Hoz https://orcid.org/0000-0002-6609-1721 ORCiD: Kai Cheng https://orcid.org/0000-0001-6872-9736 Article no. 252 |
Appears in Collections: | Dept of Mechanical and Aerospace Engineering Research Papers |
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