Optimization in the resistant spot-welding process of AZ61 magnesium alloy

Afshari, Davood (author), Ghaffari, Ali (author), Barsum, Zuheir (author)

In this paper, an integrated artificial neural network (ANN) and multi-objective genetic algorithm (GA) are developed to optimize the resistance spot welding (RSW) of AZ61 magnesium alloy. Since the stability and strength of a welded joint are strongly dependent on the size of the nugget and the residual stresses created during the welding process, the main purpose of the optimization is to achieve the maximum size of the nugget and minimum tensile residual stress in the weld zone. It is identified that the electrical current, welding time, and electrode force are the main welding parameters affecting the weld quality. The experiments are carried out based on the full factorial design of experiments (DOE). In order to measure the residual stresses, an X-ray diffraction technique is used. Moreover, two separate ANNs are developed to predict the nugget size and the maximum tensile residual stress based on the welding parameters. The ANN is integrated with a multi-objective GA to find the optimum welding parameters. The findings show that the integrated optimization method presented in this study is effective and feasible for optimizing the RSW joints and process.

• Language: English
• Keywords: resistance spot welding, residual stresses, artificial neural network, genetic algorithm, AZ61 magnesium alloy
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FS - Faculty of Mechanical Engineering
• Publication status: Published
• Publication version: Version of Record
• Publication date: 01.07.2022
• Year: 2022
• Number of pages: Str. 485-492
• Numbering: Vol. 68, no. 7/8
• PID: 20.500.12556/RUL-140835
• UDC: 621.791
• ISSN on article: 0039-2480
• DOI: 10.5545/sv-jme.2022.174
• COBISS.SI-ID: 121920259
• Publication date in RUL: 19.09.2022

Record is a part of a journal

• Title: Strojniški vestnik
• Shortened title: Stroj. vestn.
• Publisher: Zveza strojnih inženirjev in tehnikov Slovenije [etc.], = Association of Mechanical Engineers and Technicians of Slovenia [etc.
• ISSN: 0039-2480
• COBISS.SI-ID: 762116

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Title: Optimizacija postopka uporovnega točkovnega varjenja magnezijeve zlitine AZ61
• Keywords: uporovno točkovno varjenje, preostale napetosti, umetna nevronska mreža, genetski algoritem, magnezijeva zlitina AZ61