Optimization of FSW Parameters Using SA Algorithm and ANFIS-Based Models to Maximize Mechanical Properties of AZ80A Mg Alloy Joints

This paper deals with the experimental research, modeling and parametric-based optimization of the mechanical properties of the friction stir welded AZ80A Mg alloy. A four-factor, five-level-based central composite design matrix was employed to minimize the experimental runs. Adaptive neuro-fuzzy in...

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Published inJournal of materials engineering and performance Vol. 34; no. 14; pp. 14487 - 14506
Main Authors Gunasekaran, J., Sevvel, P., Solomon, I. John, Roy, J. Vasanthe
Format Journal Article
LanguageEnglish
Published New York Springer US 01.07.2025
Springer Nature B.V
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ISSN1059-9495
1544-1024
DOI10.1007/s11665-024-10062-z

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Abstract This paper deals with the experimental research, modeling and parametric-based optimization of the mechanical properties of the friction stir welded AZ80A Mg alloy. A four-factor, five-level-based central composite design matrix was employed to minimize the experimental runs. Adaptive neuro-fuzzy inference system (i.e., ANFIS) was employed to map the relationship amid the parameters of FSW process (namely tool pin geometry, traverse speed, axial force, and rotational speed) and mechanical properties (including yield strength, tensile strength and hardness) of the joints. Later, the formulated ANFIS model was used along with simulated annealing (SA) algorithm determining the optimized parameters of FSW process so as to attain flaw free AZ80A Mg alloy joints. Formulated ANFIS model-SA algorithm anticipated that the friction stir welded AZ80A Mg alloy joints will possess a tensile strength of 240.52 MPa during the single-response optimization scenario and a tensile strength of 240.522 MPa during the multiple-response optimization scenario. Experimental results announced that the FSW process parameter combination of tool rotational speed of 1250 rpm, tool traverse speed of 1.75 mm/sec, axial force of 3 kN and tool possessing a threaded cylindrical pin geometry have contributed for attainment of largest values of mechanical properties during both the single-response and multiple-response optimization scenarios. During the confirmatory experimental work, the flaw free friction stir welded AZ80A Mg alloy joints exhibited a tensile strength of 242.16 MPa and the results of confirmatory experiment revealed that the ANFIS-SA system had exhibited superiority in modeling and optimization of the FSW process during joining of AZ80A Mg alloys.
AbstractList This paper deals with the experimental research, modeling and parametric-based optimization of the mechanical properties of the friction stir welded AZ80A Mg alloy. A four-factor, five-level-based central composite design matrix was employed to minimize the experimental runs. Adaptive neuro-fuzzy inference system (i.e., ANFIS) was employed to map the relationship amid the parameters of FSW process (namely tool pin geometry, traverse speed, axial force, and rotational speed) and mechanical properties (including yield strength, tensile strength and hardness) of the joints. Later, the formulated ANFIS model was used along with simulated annealing (SA) algorithm determining the optimized parameters of FSW process so as to attain flaw free AZ80A Mg alloy joints. Formulated ANFIS model-SA algorithm anticipated that the friction stir welded AZ80A Mg alloy joints will possess a tensile strength of 240.52 MPa during the single-response optimization scenario and a tensile strength of 240.522 MPa during the multiple-response optimization scenario. Experimental results announced that the FSW process parameter combination of tool rotational speed of 1250 rpm, tool traverse speed of 1.75 mm/sec, axial force of 3 kN and tool possessing a threaded cylindrical pin geometry have contributed for attainment of largest values of mechanical properties during both the single-response and multiple-response optimization scenarios. During the confirmatory experimental work, the flaw free friction stir welded AZ80A Mg alloy joints exhibited a tensile strength of 242.16 MPa and the results of confirmatory experiment revealed that the ANFIS-SA system had exhibited superiority in modeling and optimization of the FSW process during joining of AZ80A Mg alloys.
This paper deals with the experimental research, modeling and parametric-based optimization of the mechanical properties of the friction stir welded AZ80A Mg alloy. A four-factor, five-level-based central composite design matrix was employed to minimize the experimental runs. Adaptive neuro-fuzzy inference system (i.e., ANFIS) was employed to map the relationship amid the parameters of FSW process (namely tool pin geometry, traverse speed, axial force, and rotational speed) and mechanical properties (including yield strength, tensile strength and hardness) of the joints. Later, the formulated ANFIS model was used along with simulated annealing (SA) algorithm determining the optimized parameters of FSW process so as to attain flaw free AZ80A Mg alloy joints. Formulated ANFIS model-SA algorithm anticipated that the friction stir welded AZ80A Mg alloy joints will possess a tensile strength of 240.52 MPa during the single-response optimization scenario and a tensile strength of 240.522 MPa during the multiple-response optimization scenario. Experimental results announced that the FSW process parameter combination of tool rotational speed of 1250 rpm, tool traverse speed of 1.75 mm/sec, axial force of 3 kN and tool possessing a threaded cylindrical pin geometry have contributed for attainment of largest values of mechanical properties during both the single-response and multiple-response optimization scenarios. During the confirmatory experimental work, the flaw free friction stir welded AZ80A Mg alloy joints exhibited a tensile strength of 242.16 MPa and the results of confirmatory experiment revealed that the ANFIS-SA system had exhibited superiority in modeling and optimization of the FSW process during joining of AZ80A Mg alloys.
Author Sevvel, P.
Solomon, I. John
Gunasekaran, J.
Roy, J. Vasanthe
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AZ80A Mg alloy
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Snippet This paper deals with the experimental research, modeling and parametric-based optimization of the mechanical properties of the friction stir welded AZ80A Mg...
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SubjectTerms Adaptive systems
Algorithms
Alloys
Axial forces
Characterization and Evaluation of Materials
Chemistry and Materials Science
Corrosion and Coatings
Engineering Design
Friction stir welding
Magnesium base alloys
Materials Science
Mechanical properties
Metals
Modelling
Optimization
Optimization algorithms
Original Research Article
Process parameters
Quality Control
Reliability
Residual stress
Safety and Risk
Simulated annealing
Soft computing
Tensile strength
Tribology
Title Optimization of FSW Parameters Using SA Algorithm and ANFIS-Based Models to Maximize Mechanical Properties of AZ80A Mg Alloy Joints
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