Real-time sensing of gas metal arc welding process – A literature review and analysis

Yongchao Cheng, Rui Yu, Quan Zhou, Heming Chen, Wei Yuan, Yu Ming Zhang

Research output: Contribution to journalReview articlepeer-review

41 Scopus citations

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.

Original languageEnglish
Pages (from-to)452-469
Number of pages18
JournalJournal of Manufacturing Processes
Volume70
DOIs
StatePublished - Oct 2021

Bibliographical note

Publisher Copyright:
© 2021

Keywords

  • CNN
  • Control
  • Deep learning
  • GMAW
  • Gas metal arc welding
  • Image
  • Machine learning
  • Monitoring
  • Seam tracking
  • Sensing
  • Sensor
  • Weld pool
  • Welding

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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