Multi Objective Optimization of Joining Dissimilar AA5083& AA6061 Alloys Using Friction Stir Welding- Integrated Taguchi and Grey Systems Approach

2020 ◽  
Vol 978 ◽  
pp. 133-139
Author(s):  
B. Ravi Sankar ◽  
P. Umamaheswarrao ◽  
K. Rajasekhara Babu ◽  
M. Pardhasaradhi
Keyword(s):  
Tilt Angle ◽  
Rotational Speed ◽  
Systems Approach ◽  
Vital Role ◽  
Contour Plot ◽  
Multi Objective Optimization ◽  
Tool Rotational Speed ◽  
Friction Stir ◽  
Multi Objective ◽  
Main Effects

In this study, multi objective optimization for improving the joining characteristics of dissimilar AA5083-AA6061 alloys during FSW has been presented. Tool rotational speed, feed and tilt angle are the input parameters whereas tensile strength and hardness are the responses. Experiments are planned and conducted as per Taguchi L9 orthogonal array. Main effects plot and contour plot discloses the parametric influence over the responses. Hybrid GRA and PCA were deployed as tools to perform multi objective optimization. Results pointed out the fact that tilt angle played vital role in affecting the responses followed by feed and tool rotational speed. The optimum parametric settings obtained are speed 710 rpm, Feed 50 mm/rev, and Tilt angle 2o.

Multi-Objective Optimization of Friction Stir Spot Welds of Aluminum Alloy Using Entropy Measurement

2019 ◽  
Vol 45 ◽  
pp. 28-41
Author(s):  
Olatunji Oladimeji Ojo
Keyword(s):  
Rotational Speed ◽  
Dwell Time ◽  
Shear Failure ◽  
Failure Load ◽  
Multi Objective Optimization ◽  
Plunge Depth ◽  
Friction Stir ◽  
Multi Objective ◽  
Entropy Measurement ◽  
Grey Relational

Surface finish accrued extra-production cost, reduced effective sheet thickness, stir zone galling, undesirable flash-root stress concentration and fatigue cracks are consequences of bulk expulsion of flash during friction stir spot welding of aluminum alloys. This paper attempts to cutback the abovementioned challenges and improves the weld strength (shear failure load) of friction stir spot welded joints of an Al alloy by adopting an integrated Grey relational analysis-entropy measurement method as a multi-objective optimization tool. Shear failure load, and expelled flash properties (pushed out length and thickness) are the three examined quality characteristics of the joint while tool rotational speed (600-1400 rpm), dwell time (3-6 s) and plunge depth (1.5-1.7 mm) are the studied process parameters. The experiment was planned via the use of Taguchi method whereas the entropy measurement method facilitated the identification of the precise weighting values required for the estimation of the unified grey relational grade. The failure load of the joint was maximized while both flash height and pushed-out length were minimized. The optimized shear failure load and flash properties were attained at a parameter setting of 1400 rpm rotational speed, 6 s dwell time and 1.5 mm plunge depth. The tool rotational speed was found to have the most significant effect and percentage contribution on the combined responses with 67.75%, followed by plunge depth (12.88 %) and dwell time (11.94 %) respectively. The validation results confirm the robustness of the entropy measurement-based multi-objective optimization as a tool for improving the quality responses of friction stir spot welds.

Parametric optimization of friction stir welding process parameters of dissimilar welded joints using grey relational analysis and desirability function approach

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bhanodaya Kiran Babu Nadikudi
Keyword(s):  
Tensile Strength ◽  
Process Parameters ◽  
Tilt Angle ◽  
Grey Relational Analysis ◽  
Rotational Speed ◽  
Tool Rotational Speed ◽  
Content Type ◽  
Friction Stir ◽  
Relational Analysis ◽  
Grey Relational

Purpose The main purpose of the present work is to study the multi response optimization of dissimilar friction stir welding (FSW) process parameters using Taguchi-based grey relational analysis and desirability function approach (DFA). Design/methodology/approach The welded sheets were fabricated as per Taguchi orthogonal array design. The effects of tool rotational speed, transverse speed and tool tilt angle process parameters on ultimate tensile strength and hardness were analyzed using grey relational analysis, and DFA and optimum parameters combination was determined. Findings The tensile strength and hardness values were evaluated from the welded joints. The optimum values of process parameters were estimated through grey relational analysis and DFA methods. Similar kind of optimum levels of process parameters were obtained through two optimization approaches as tool rotational speed of 1150 rpm, transverse speed of 24 mm/min and tool tilt angle of 2° are the best process parameters combination for maximizing both the tensile strength and hardness. Through these studies, it was confirmed that grey relational analysis and DFA methods can be used to find the multi response optimum values of FSW process parameters. Research limitations/implications In the present study, the FSW is performed with L9 orthogonal array design with three process parameters such as tool rotational speed, transverse speed and tilt angle and three levels. Practical implications Aluminium alloys are widely using in automotive and aerospace industries due to holding a high strength to weight property. Originality/value Very limited work had been carried out on multi objective optimization techniques such as grey relational analysis and DFA on friction stir welded joints made with dissimilar aluminium alloys sheets.

Procedure to find out the optimal ranges of process parameters for friction stir welding

2021 ◽  
pp. 146442072199314
Author(s):  
Shubham Verma ◽  
Joy Prakash Misra ◽  
Meenu Gupta
Keyword(s):  
Friction Stir Welding ◽  
Process Parameters ◽  
Tilt Angle ◽  
Welding Speed ◽  
Rotational Speed ◽  
Optical Microscope ◽  
Graphical Analysis ◽  
Friction Stir ◽  
Steepest Ascent ◽  
Vertical Milling Machine

The present study deals with the application of sequential procedure (i.e. steepest ascent) to obtain the optimum values of process parameters for conducting friction stir welding (FSW) experiments. A vertical milling machine is modified by fabricating fixture and tool ( H13 material) for performing FSW operation to join AA7039 plates. The steepest ascent technique is employed to design the experiments at different rotational speed, welding speed, and tilt angle. The ultimate tensile strength is considered as a performance characteristic for deciding the optimal levels. The mechanical and metallurgical characteristics of the joints are studied by executing tensile and microhardness tests. It is concluded from the graphical analysis of the steepest ascent technique that the optimal maximum and minimum values are 1812–1325 r/min for rotational speed, 43–26 mm/min for welding speed, and 2°–1.3° for tilt angle, respectively. Besides, optical microscope and scanning electron microscope are utilized for microstructural and fractographic analyses for a better understanding of the process.

Comparison of response surface methodology with artificial neural network for prediction of the tensile properties of friction stir-processed surface composites

2021 ◽  
pp. 095440892110368
Author(s):  
Ravi Butola ◽  
Ranganath M. Singari ◽  
Qasim Murtaza ◽  
Lakshay Tyagi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Tensile Strength ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Rotational Speed ◽  
Total Elongation ◽  
Tool Rotational Speed ◽  
Friction Stir ◽  
Artificial Neural

In the present work, nanoboron carbide is integrated in the aluminum matrix using friction stir processing: by varying process parameters, that is, tool pin profile, tool rotational speed and tool traverse speed, based on Taguchi L16 design of experiment. A self-assembled monolayer is successfully developed on the substrate to homogeneously and uniformly distribute the reinforcement particles. Response surface methodology and artificial neural network models are developed using ultimate tensile strength and total elongation as responses. Percentage absolute error between the experimental and predicted values of ultimate tensile strength and total elongation for the response surface methodology model is 3.537 and 2.865, respectively, and for artificial neural network is 2.788 and 2.578, respectively. For both the developed models experimental and forecasted values are in close approximation. The artificial neural network model showed slightly better predictive capacity compared to the response surface methodology model. From the scanning electron microscopy micrograph, it is evident that throughout the matrix B4C reinforcement particles are well distributed also; with increasing tool rotational speed grain size decreases up to 1200 r/min; on further increasing the tool rotational speed particles starts clustering.

Effect of Al2O3 nanoparticles on microstructure and mechanical properties of friction stir-welded dissimilar aluminum alloys AA7075-T6 and AA6061-T6

2021 ◽  
pp. 095440892110655
Author(s):  
Sumit Jain ◽  
R.S. Mishra
Keyword(s):  
Mechanical Properties ◽  
Tensile Strength ◽  
Rotational Speed ◽  
Traverse Speed ◽  
Particle Dispersion ◽  
Al2o3 Nanoparticles ◽  
Tool Rotational Speed ◽  
Micro Hardness ◽  
Friction Stir ◽  
Dissimilar Aluminum Alloys

In this research, a defect-free dissimilar weld joint of AA7075-T6 and AA6061-T6 reinforced with Al2O3 nanoparticles was fabricated via friction stir welding (FSW). The influence of tool rotational speed (700, 900 and 1100 rpm), traverse speed (40, 50 and 60 mm/min) with varying volume fractions of Al2O3 nanoparticles (4%, 7% and 10%) on microstructural evolution and mechanical properties were investigated. The augmentation of various mechanical properties is based on the homogeneity of particle dispersion and grains refinement in the SZ of the FSWed joint. The findings revealed that the remarkable reduction in grain size in the SZ was observed owing to the incorporation of Al2O3 nanoparticles produces the pinning effect, which prevents the growth of grain boundaries by dynamic recrystallization (DRX). The increasing volume fraction of Al2O3 nanoparticles enhanced the mechanical properties such as tensile strength, % elongation and micro-hardness. Agglomeration of particles was observed in the SZ of the FSWed joints produced at lower tool rotational speed of 700 rpm and higher traverse speed of 60 mm/min due to unusual material flow. Homogenous particle dispersion and enhanced material mixing ensue at higher rotational speed of 1100 rpm and lower traverse speed of 40 mm/min exhibit higher tensile strength and micro-hardness.

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