2021AIP conference proceedingsRequires access

Parameters optimization using factorial analysis method for Gas Metal Arc Welding (GMAW) process

Mohd Hasril Amiruddin, Mohd Erfy Ismail, Sri Sumarwati, Mohd Rezal Mohd Salleh, Nur Aisyah Ahmad Noor

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Abstract

Gas Metal Arc Welding (GMAW) is the most widely used process and an essential component in many industrial operations. GMAW welding parameters are the most significant factors influencing the quality, productivity, and cost of the welding joint. Therefore, there is a need to optimize the GMAW process to achieve welding quality because currently, the most common problem faced by the manufacturer is to control the process input parameter to obtain a proper welded joint with the required quality in strength with a minimal defect. Factorial Design does the Design of Experiment (DOE) Approached used SPSS software to define the welding characteristics of mild steel and optimize the welding parameter. The considered parameters are welding current (Amp), welding voltage (Volts), and wire feed rate (m/min) while the desired output responses are tensile strength. Optimization is done used factor analysis to find the optimum welding parameters value of welded specimen and the results show that the three new factors have been identified current 150 amps, voltage 23 volts, and wire feed rate 4 m/min. The value of these parameters can be used as a reference for operators and welders in the welding industry to improve the quality of welding to a better level without any defects or losses.

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What this paper is about

Gas Metal Arc Welding (GMAW) is the most widely used process and an essential component in many industrial operations. GMAW welding parameters are the most significant factors influencing the quality, productivity, and cost of the welding joint. Therefore, there is a need to optimize the GMAW process to achieve welding quality because currently, the most common problem faced by the manufacturer is to control the process input parameter to obtain a proper welded joint with the required quality in strength with a minimal defect. Factorial Design does the Design of Experiment (DOE) Approached used SPSS software to define the welding characteristics of mild steel and optimize the welding parameter. The considered parameters are welding current (Amp), welding voltage (Volts), and wire feed rate (m/min) while the desired output responses are tensile strength. Optimization is done used factor analysis to find the optimum welding parameters value of welded specimen and the results show that the three new factors have been identified current 150 amps, voltage 23 volts, and wire feed rate 4 m/min. The value of these parameters can be used as a reference for operators and welders in the welding industry to improve the quality of welding to a better level without any defects or losses.

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Available abstract

Gas Metal Arc Welding (GMAW) is the most widely used process and an essential component in many industrial operations. GMAW welding parameters are the most significant factors influencing the quality, productivity, and cost of the welding joint. Therefore, there is a need to optimize the GMAW process to achieve welding quality because currently, the most common problem faced by the manufacturer is to control the process input parameter to obtain a proper welded joint with the required quality in strength with a minimal defect. Factorial Design does the Design of Experiment (DOE) Approached used SPSS software to define the welding characteristics of mild steel and optimize the welding parameter. The considered parameters are welding current (Amp), welding voltage (Volts), and wire feed rate (m/min) while the desired output responses are tensile strength. Optimization is done used factor analysis to find the optimum welding parameters value of welded specimen and the results show that the three new factors have been identified current 150 amps, voltage 23 volts, and wire feed rate 4 m/min. The value of these parameters can be used as a reference for operators and welders in the welding industry to improve the quality of welding to a better level without any defects or losses.

Key concepts: Welding, Gas metal arc welding, Fractional factorial design, Process variable, Mechanical engineering, Design of experiments, Materials science, Factorial experiment

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