Real-time sensing of gas metal arc welding process – A literature review and analysis. (October 2021)

• Record Type: Journal Article
• Authors: Cheng, Yongchao; Yu, Rui; Zhou, Quan; Chen, Heming; Yuan, Wei; Zhang, YuMing
• Is Part Of: Journal of manufacturing processes. Volume 70(2021)
• Page Start: 452
• Page End: 469
• Publication Date: 2021-10
• Subjects: Welding -- Gas metal arc welding -- GMAW -- Seam tracking -- Weld pool -- Sensor -- Sensing -- Monitoring -- Control -- Image -- Machine learning -- Deep learning -- CNN; Production management -- Data processing -- Periodicals; Manufacturing processes -- Periodicals; Procestechnologie; Productietechniek; Production -- Gestion -- Informatique -- Périodiques; Fabrication -- Périodiques; Manufacturing processes; Production management -- Data processing; Periodicals; 670.5
• DOI: 10.1016/j.jmapro.2021.08.058
• Languages: English
• ISSNs: 1526-6125

Abstract

Abstract: Welding is a major manufacturing process that joins two or more pieces of materials together through heating/mixing them, with or without pressure, as they cool and solidify. The goal of welding manufacturing is to join materials together to meet service requirements at the lowest costs. Advanced welding manufacturing (AWM) is to use scientific methods to realize this goal. It involves three steps: (1) pre-design that selects process and joint design based on available processes (properties, capabilities, and costs); (2) design that uses models to predict the result from a given set of welding parameters and minimizes a cost function for optimizing the welding parameters; (3) real-time sensing and control that overcome the deviations of welding conditions from their nominal ones used in optimizing the welding parameters by adjusting the welding parameters based on such real-time sensing and feedback control. While step (1) and (2) are pre-manufacturing designs, step (3) is the step during manufacturing that must be addressed by manufacturers. This report reviews and analyzes the state-of-the-art in real-time sensing of the gas metal arc welding, that is the most widely used robotic welding process, including seam tracking, machine vision, weld pool monitoring, machine learning, etc.