Grey Relational Analysis and Anova to Determine the Optimum Process Parameters for Friction Stir Welding of Ti and Mg Alloys

Sivam, S.P. Sundar Singh; Saravanan, K.; Pradeep, N.; Moorthy, K. Sathiya; RajendraKumar, S.

doi:10.3311/ppme.12117

Cited by 35 publications

(13 citation statements)

References 11 publications

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“…GRG may be classified into particularly; Smaller the better, Larger the better, or Nominal could be a better (NB) criterion. The preferred quality characteristics for Final Maximum interface temperature, equivalent Von-Mises stress, and total deformation are Smaller the better criterion, and then it’s expressed by using equation 24 :…”

Section: Methods Of Analysismentioning

confidence: 99%

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Optimization of parameters in rotary friction welding process of dissimilar austenitic and ferritic stainless steel using finite element analysis

Mattie

Ezdeen

Khidhir

2023

Advances in Mechanical Engineering

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Solid state joining techniques are increasingly used in joining different types of materials, in this work TP347HFG austenitic stainless steel will be welded with HiPerFer ferritic stainless-steel alloy due to their similarity in their properties to some extent after making heat treatment to ferritic alloy in addition to difference in their cost which save for economic reasons. In this work, a three-dimensional finite element model was developed. The thermal analysis and profiles between process parameters were predicted by using an ANSYS software tool. Design of experiments by Anova was used to examinate the simulation results and to evaluate contribution ratio of each parameter on responses, while grey relational analysis was used to specify the optimum trial. It was observed that trial 11 give best results (A4B2C1D1) which got higher grey relational grade. It was concluded that the friction pressure and friction time have more impact on interface temperature, whereas forging pressure and friction time affect the equivalent Von-Mises stress directly. The speed and forging pressure have a more influence on total deformation. It was also concluded that the temperature was fade out by diverging toward the end of specimen and the amount of decrease in temperature is less in ferritic side. The amount of flash extruded from both steels are approximately similar due to similarity in properties as heat treatment of ferritic alloy had been achieved. The investigation results show that trial 8 achieved highest Von-Mises stress (300 MPa) while trial 7 induced lower stress (255 MPa), maximum deformation was found equivalent to 0.012 mm with trial 16 whereas, it was found (0.008 mm) with trial 11 which were both less than the allowable deformation in end application. Tensile strength of weld joint was found equivalent to 80% of softer base metal. The hardness of optimum trial was equivalent to 156 HB.

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Section: Methods Of Analysismentioning

confidence: 99%

“…of factors; y i ( k ) = original sequence; y i *( k ) value after Grey relational generation; min y i ( k ) and max y i ( k ) are the minimum and maximum value of y i ( k ), respectively. The calculation for Grey relation coefficient was done using equation 24 :…”

Section: Methods Of Analysismentioning

confidence: 99%

Optimization of parameters in rotary friction welding process of dissimilar austenitic and ferritic stainless steel using finite element analysis

Mattie

Ezdeen

Khidhir

2023

Advances in Mechanical Engineering

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“…GRA depends on grey-system theory, suitable for solving problems with intricate relationship between several factors and levels. Therefore, GRA reduces intricacy and can be used for solving various types of multi-attribute decision-making problems [11,12]. In a similar way TOPSIS-approach is also a simple and effective method for multi-attribute decision making problems used in several applications mainly in selecting the process-parameters in manufacturing studies [13].…”

Section: Introductionmentioning

confidence: 99%

Multi-attribute Optimization of Weld Parameters for Micro-friction Stir Welded Al6061/SS304 Sheets Using TOPSIS Approach

Manohar

Mahadevan

2022

Period. Polytech. Mech. Eng.

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Friction stir welding (FSW) is a solid-state welding approach that can produce high quality joints in a fast and reliable manner. The present study is focused on optimization of multi-responses for micro-friction stir welded Al6061-T6 and SS304 sheets. Weld-parameters such as tool-rotational speed (TRS) and tool-traverse speed (TTS) influenced the mechanical responses of dissimilar welded joints significantly. In order to determine the effect of optimum process parameters on mechanical responses such as ultimate-tensile strength (UTS), micro-hardness (MHV) and surface-roughness (Ra) of dissimilar welded joints, an attempt has been made to find out the best possible set of process variables through multi-attribute optimization using technique for order of preference by similarity to ideal solution (TOPSIS) approach. Finally, the optimal solution shows that multi-responses of micro-friction stir welds can be improved through TOPSIS approach.

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“…Sivam et al [14] applied Grey relational analysis and ANOVA in multi response optimization of setting input variable for getting better product quality in machining of magnesium AM60, the expected response and measured response are fairly close in the study. Sivam et al [15] also studied the friction stir welding of Ti and Mg alloys by using Taguchi method, Grey relational analysis and ANOVA approaches to determine the optimum process parameters. Their results showed that the measured values are close to the expected values.…”

Section: Introductionmentioning

confidence: 99%

The Study of Optimal Molding of a LED Lens with Grey Relational Analysis and Molding Simulation

Wang¹,

Arifin

2019

Period. Polytech. Mech. Eng.

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Injection molding technology is known as the most widely used method in mass production of plastic products. To meet the quality requirements, a lot of methods were applied in optimization of injection molding process parameter. In this study the optimization based on Taguchi orthogonal array and Grey relational analysis (GRA) is used to optimize the injection molding process parameters on a LED lens. The four process parameters are: packing pressure, injection speed, melt temperature and mold temperature. The multi-response quality characteristics are total displacement, volumetric shrinkage, and thermal residual stress. The optimal molding parameters are packing pressure (90 MPa), injection speed (300 mm/sec), melt temperature (270 °C) and mold temperature (90 °C). The luminous uniformity of the LED is 92.61 % and the viewing angle of the LED is 124.76°. Among the four factors, packing pressure plays the key role in reducing total displacement, volumetric shrinkage, and thermal residual stress.

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Grey Relational Analysis and Anova to Determine the Optimum Process Parameters for Friction Stir Welding of Ti and Mg Alloys

Abstract: Abstract

Cited by 35 publications

References 11 publications

Optimization of parameters in rotary friction welding process of dissimilar austenitic and ferritic stainless steel using finite element analysis

Optimization of parameters in rotary friction welding process of dissimilar austenitic and ferritic stainless steel using finite element analysis

Multi-attribute Optimization of Weld Parameters for Micro-friction Stir Welded Al6061/SS304 Sheets Using TOPSIS Approach

The Study of Optimal Molding of a LED Lens with Grey Relational Analysis and Molding Simulation

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