Optimization of Multiple Performance Characteristics of Friction Stir Welded Joint with Grey Relational Analysis

Shamsudeen, Shanavas; Dhas, J. Edwin Raja

doi:10.1590/1980-5373-mr-2017-1050

Cited by 10 publications

(4 citation statements)

References 25 publications

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“…Increasing in tilt angle results in increasing the UTS to reach the maximum value at 3 • and 30 mm/min, and then gradually decreases as these two parameters increase. Increasing the tilt angle of the welding tool leads to an increase in the vertical force and torque, this may lead to an increase in the contact between the tool and the workpiece and then the highest heat inputs are achieved which causes a thermal softening of the deformed material and an increase in the flow of downward materials, where the restoration of grains are obtained in stir zone that occurs in conjunction with the deformation, and this process is called dynamic recrystallization, which leads to the grain refinement during welding [50]. Fig.…”

Section: Prediction Of Fsw Process Parametersmentioning

confidence: 99%

A Novel Method for Predicting Tensile Strength of Friction Stir Welded AA6061 Aluminium Alloy Joints Based on Hybrid Random Vector Functional Link and Henry Gas Solubility Optimization

et al. 2020

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Aluminum alloys have low weldability by conventional fusion welding processes. Friction stir welding (FSW) is a promising alternative to traditional fusion welding techniques for producing high quality aluminum joints. The quality of the welded joints is highly dependent on the process parameters used during welding. In this research, a new approach was developed to predict the process parameters and mechanical properties of AA6061-T6 aluminium alloy joints in terms of ultimate tensile strength (UTS). A new hybrid artificial neural network (ANN) approach has been proposed in which Henry Gas Solubility Optimization (HGSO) algorithm has been incorporated to improve the performance of Random Vector Functional Link (RVFL) network. The HGSO-RVFL model was constructed with four parameters; rotational speed, welding speed, tilt angle, and pin profile. The validity of the model was tested, and it was demonstrated that the HGSO-RVFL model is a powerful technique for predicting the UTS of friction stir welded (FSWD) joints. In addition, the effects of process parameters on UTS of welded joints were discussed, where a significant agreement was observed between experimental results and predicted results which indicates the high performance of the model developed to predict the appropriate welding parameters that achieve optimal UTS.

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Section: Prediction Of Fsw Process Parametersmentioning

confidence: 99%

A Novel Method for Predicting Tensile Strength of Friction Stir Welded AA6061 Aluminium Alloy Joints Based on Hybrid Random Vector Functional Link and Henry Gas Solubility Optimization

et al. 2020

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“…Prevention of defects formation during FSP is very important to produce a quality workpiece. Shamsudeen et al [17] demonstrated the influence of tool shape on microstructural properties and tensile strength of AA 5052 H32 aluminum alloy. Govindaraju et al [18] studied the influence of FSP with several heat treatment conditions on the microstructural evolutions of AZ91.…”

Section: Introductionmentioning

confidence: 99%

Numerical and experimental investigation of defects formation during friction stir processing on AZ91

et al. 2021

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The heat generated during friction stir processing greatly affects defects formation in the processed zone of workpieces. In this paper, numerical modeling of this process is performed to determine the influence of tool rotational and traverse speeds and hence their ratio on the thermal distribution attained during the process. The aim is to produce defect-free processed samples by selecting adequate tool speeds. The mechanisms of defects formation depending on the peak temperature are also investigated. Experiments to verify the simulation results were conducted with the same process parameters. Several traverse speeds of 20, 40, 60, and 80 mm/min and rotational speeds of 700, 1000, 1200, and 2000 rpm were used during modeling and conducting the experiments. From the numerical and experimental results, it was found that; the high-speed processing conditions (low-generated heat) can produce defects such as tunnels and grooves, and the low-speed processing conditions (high-generated heat) can cause defects such as flashes. The experimental results show that during friction stir processing with the rotational speed of 1200 rpm and the traverse speed of 60 mm/min (speed ratio of 20), no macro defects in the processed zone were observed. According to the numerical results, the peak temperature during friction stir processing with these speeds was 475 °C. At this temperature, the material softened, the structure finely equiaxed and no large scale melting zone appeared in the processed zone. The developed model can be useful to investigate the occurrence of defects associated with different tool rotational and traverse speeds. Graphic abstract

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“…He et al [7] propusieron una estrategia de optimización robusta basada en funciones de deseabilidad, de manera conjunta con el método de búsqueda simplex para encontrar las múltiples respuestas óptimas. Shamsudeen et al [8] y Jambhale et al [9] consideraron diferentes esquemas de experimentación para optimizar múltiples parámetros de un proceso de soldadura por fricción-agitación de punto. Kilic et al [10] asumieron la metodología de superficie de respuesta (MSR) y el análisis envolvente de datos para optimizar el ácido fítico y el volumen de pan simultáneamente.…”

Section: Introductionunclassified

Comparación de métodos de optimización para un experimento con múltiples variables de respuesta

Mendoza-Gallardo

Rodríguez‐Picón

Méndez‐González

2021

CULCYT

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Dentro del proceso de experimentación estadística existen ciertas variables que en conjunto determinan las condiciones ideales de múltiples variables de respuesta. Un reto importante dentro de la optimización de modelos creados a partir de experimentos recae precisamente en las situaciones en que la calidad de un producto es función de múltiples variables de respuesta y dadas estas condiciones resulta necesario establecer estrategias precisas que permitan optimizar todas las respuestas a la vez. En este trabajo se experimentó con tres métodos de optimización con el propósito de encontrar el mejor de ellos y la estrategia capaz de optimizar las funciones que consisten en más de una característica crítica. El objetivo del artículo es encontrar la estrategia capaz de arrojar las condiciones óptimas de dos variables de respuesta, condicionadas por restricciones iniciales. Los resultados de optimización obtenidos a través de los métodos considerados fueron similares en cuanto al logro de los objetivos de optimización planteados.

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Optimization of Multiple Performance Characteristics of Friction Stir Welded Joint with Grey Relational Analysis

Cited by 10 publications

References 25 publications

A Novel Method for Predicting Tensile Strength of Friction Stir Welded AA6061 Aluminium Alloy Joints Based on Hybrid Random Vector Functional Link and Henry Gas Solubility Optimization

A Novel Method for Predicting Tensile Strength of Friction Stir Welded AA6061 Aluminium Alloy Joints Based on Hybrid Random Vector Functional Link and Henry Gas Solubility Optimization

Numerical and experimental investigation of defects formation during friction stir processing on AZ91

Comparación de métodos de optimización para un experimento con múltiples variables de respuesta

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