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A real-time quality monitoring framework for steel friction stir welding using computational intelligence

  • Published:2015-10 Issue: Volume:20 Page:137-148
  • ISSN:1526-6125
  • Container-title:Journal of Manufacturing Processes
  • language:en
  • Short-container-title:Journal of Manufacturing Processes

Author:

Baraka Ali,Panoutsos George,Cater Stephen

Funder

TWI Ltd

Department of Automatic Control and Systems Engineering, The University

Publisher

Elsevier BV

Subject

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

Reference48 articles.

1. Friction stir welding for the transportation industries;Thomas;Mater Des,1997

2. Friction stir welding and processing;Mishra;Mater Sci Eng R,2005

3. Fundamentals of friction stir welding;Cater,2014

4. Energy input during friction stir spot welding;Cox;J Manuf Process,2014

5. Simultaneous measurement of tool torque, traverse force and axial force in friction stir welding;Su;J Manuf Process,2013

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2. Prediction of friction stir welding performances of dissimilar AA3003-H12 and C12200-H01 using machine learning algorithms;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2024-09-05

3. Online prediction of joint mechanical properties of FSW thick AA2219-T8 based on multi-source information fusion using 1DCNN;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2024-08-20

4. Advances in welding sensing information processing and modelling technology: an overview;Journal of Adhesion Science and Technology;2024-08-06

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