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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 11 Issue: 04 | Apr 2024

p-ISSN: 2395-0072

www.irjet.net

WELDING OF ALUMINUM ALLOY BY USING RESISTANCE SPOT WELDING Sagar Datta1, Dr. D.K. Bhalla2 1B.Tech. Mechanical Engineering (Evening) Scholar, School of Mechanical Engineering, Lingaya’s Vidyapeeth,

Faridabad, Haryana, India

2Professor and LEET Coordinator B.Tech., M.Tech., PhD, FIE in Lingaya’s Vidyapeeth, Faridabad, Haryana, India

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Abstract -Aluminium alloy that is utilised in the automobile sector is used to process Resistance Spot Welding (RSW). The challenge of adjusting RSW parameters results in uneven weld quality. The welding current, electrode force, and welding duration are critical RSW characteristics. An further RSW parameter that is thought to be required is the aluminium alloy's electrical resistance, which changes according to the material's thickness. When working with aluminium alloy, the RSW process's parameters are very sensitive to precise measurement. It was looked at if parameter prediction could be done by using an artificial neural network (ANN) to discover the optimal parameter. Using the parameters and the aluminium alloy's tensile shear strength as the input and output data, respectively, the artificial neural network (ANN) was created and evaluated for predicted weld quality. The RSW procedure is implemented using the results of the estimated parameter optimisation and the tensile shear strength testing. The mean squared error (MSE) and accuracy of the tensile shear strength output were 0.054 and 95%, respectively. This suggests that the use of artificial neural networks (ANNs) in welding machine control has been very effective in determining the welding parameters.

possible to verify the computations using ideal parameters [5]. There are several sensitive aspects, making it challenging to adjust the parameters of each welding equipment. Due to this, testing several specimens of the building material in order to get sufficient findings from experiments to determine ideal parameter values. There are more than 200 welding machines in every auto body plant. The expense of modifying the parameter settings for each unique welding machine type, for various materials (such as thickness), for replacement electrodes, and other factors has increased in an effort to achieve standard weld quality overall [6–8]. Thus, it's critical to comprehend the RSW process's parameter connections, quality-improvement strategies, evaluation and efficiency forecasting, and suitable parameter optimisation.

Key Words: RSW Process, ANN, MSE, Aluminum alloy etc.

1. INTRODUCTION Every vehicle in production contains between 7,000 and 12,000 spot welds. A computer-controlled robotic welder uses the Resistance Spot Welding (RSW) method to complete the welds. RSW is being applied to lighter aluminium alloys more often [1, 2]. In the process of producing automobiles, thin shell components are often joined using the fast joining method (RSW). Using lightweight materials to maintain robust structural vehicle bodies while conserving energy and natural resources is an essential task [3]. Since steel is now the main manufacturing material for vehicles, aluminium alloys, which have substantial mechanical qualities and low densities, are predicted to be widely employed in the future [4].This study is interested in the mechanical characteristics and light weight of the 6061-T6 aluminium alloy. For the automobile sector, the RSW process's weld quality has been a major issue. The accuracy and correctness of welding parameters have not always been achieved by manual computation, operator experience, or technician ability in altering the parameter settings. Previously, it has not been

Impact Factor value: 8.226

Figure 1: RSW process resistance [10]. This research, officially named "parameter optimisation for resistance spot welding of 6061-T6 aluminium alloy based on artificial neural network," was prompted by the aforementioned issues. Using ANN will result in more accurate and efficient RSW parameter estimation. Particularly in the automotive sector, the ANN shown efficacy in solving both linear and nonlinear functions needed to modify the RSW parameter settings of computer operated robotic welders.

2. The RSW Method The RSW procedure aims to minimise heat conduction to colder surrounding material while producing heat quickly in

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