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

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

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.

• Jezik: Angleški jezik
• Ključne besede: resistance spot welding, residual stresses, artificial neural network, genetic algorithm, AZ61 magnesium alloy
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FS - Fakulteta za strojništvo
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Datum objave: 01.07.2022
• Leto izida: 2022
• Št. strani: Str. 485-492
• Številčenje: Vol. 68, no. 7/8
• PID: 20.500.12556/RUL-140835
• UDK: 621.791
• ISSN pri članku: 0039-2480
• DOI: 10.5545/sv-jme.2022.174
• COBISS.SI-ID: 121920259
• Datum objave v RUL: 19.09.2022

Gradivo je del revije

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

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Naslov: Optimizacija postopka uporovnega točkovnega varjenja magnezijeve zlitine AZ61
• Ključne besede: uporovno točkovno varjenje, preostale napetosti, umetna nevronska mreža, genetski algoritem, magnezijeva zlitina AZ61