Abstract:
Welding is an indispensable manufacturing process widely used across different commercial industries. Embedded monitoring and control systems are necessary to make this p...Show MoreMetadata
Abstract:
Welding is an indispensable manufacturing process widely used across different commercial industries. Embedded monitoring and control systems are necessary to make this process more maintainable, error-free, and cost-effective. This paper reviews literature about machine learning approaches for improving embedded quality monitoring and control systems for welding processes. Based on the literature included in international peer-reviewed journals and conferences, we build a comprehensive overview of pre-process, in-process, and post-process approaches for established welding techniques. Furthermore, we motivate future research for technologies that enable detecting defects in the manufacturing environment.
Date of Conference: 15-18 December 2021
Date Added to IEEE Xplore: 13 January 2022
ISBN Information: