Development of an Intelligent System for Selection of the Process Variables in Gas Metal Arc Welding Processes

Kim, L.S.; Park, C.E.; Jeong, Young Jae; Son, Joon-Sik

doi:10.1007/s001700170080

Cited by 22 publications

(9 citation statements)

References 3 publications

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“…El error relativo medio que arroja el modelo es del 9% para ambas variables, lo que supone un valor ajustado para este tipo de experimentos aplicados a procesos de soldeo por arco si se compara con los resultados de otros autores (Miguel et al, 2012;Kim et al, 2001;Kim et al, 2003). -La cuantificación de la zona afectada térmica-mente, junto con la penetración permite optimizar las variables tecnológicas del proceso estableciendo los criterios de control a emplear.…”

Section: Conclusionesunclassified

“…Wahab y Painter (1997) consideran como variables del proceso la tensión e intensidad del arco, la velocidad de soldeo y el caudal de gas empleado, limitándose a obtener un modelo similar al indicado. Kim et al (2001) también se basan en el modelo curvilíneo, obteniendo como funciones de respuesta la penetración, el sobreespesor y la anchura del cordón. Estos autores establecen que la exactitud de los modelos encontrados varía desde 0 a 25%.…”

Section: Introductionunclassified

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Optimización multiobjetivo del proceso de soldeo GMAW de la aleación AA 6063-T5 basado en la penetración y en la zona afectada térmicamente

Miguel¹,

Marín-Ortiz²,

Manjabacas³

et al. 2015

REVMETAL

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RESUMEN:La selección de los parámetros tecnológicos que regulan los procesos de soldadura por arco debe efectuarse de forma que se optimice el resultado de la operación. La penetración es uno de los factores decisivos, ya que es determinante en el modo de ejecutar el proceso así como en el comportamiento de la unión. Otro factor importante es la Zona Afectada Térmicamente (ZAT), cuando ésta presenta propiedades diferentes a las del material base. El modo en que afectan los parámetros tecnológicos en ambos, penetración y ZAT, es inverso a los objetivos que suelen plantearse. En este trabajo se presenta una metodología de optimización del proceso GMAW de la aleación AA 6063-T5 basado en el diseño de experimentos y la superficie de respuesta. Los resultados obtenidos permiten evaluar la conveniencia de fijar como objetivo valores de penetración tendentes a mantener ZAT en ratios asumibles. Se obtiene que la variable que más afecta a la optimización es la velocidad de soldadura. ABSTRACT:Multiobjective optimization of GMAW process of the AA 6063-t5 alloy based on penetration and heat affected zone. The selection of technological parameters in a welding process must be led to the optimized results of the operation. Penetration is one of the most decisive factors for the success of the joint. Another important factor is the Heat Affected Zone (HAZ), when the mechanical properties of this one are modified respecting to the base material. The way in which the technological variables of the process affects to both them, penetration and HAZ, are inverse in each case. This work presents an optimization methodology based on the Design of Experiments (DOE) and the Response Surface Method (RSM) of the GMAW process applied to the aluminum alloy AA 6063-T5. This research is focused to obtain penetration rates that make HAZ values to be suitable in current applications. Welding rate has been found to be the most significant technological parameter for controlling the process.

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Section: Conclusionesunclassified

Section: Introductionunclassified

Optimización multiobjetivo del proceso de soldeo GMAW de la aleación AA 6063-T5 basado en la penetración y en la zona afectada térmicamente

Miguel¹,

Marín-Ortiz²,

Manjabacas³

et al. 2015

REVMETAL

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“…However, most applications of the Taguchi method emphasize only one single quality characteristic [5][6][7][8][9]. When optimizing a process with MPCs, the objective is to determine the best set of process parameters that simultaneously optimizes all of the quality characteristics of interest to the designer.…”

Section: Introductionmentioning

confidence: 99%

Using a principal components analysis for developing a robust design of electron beam welding

Jean

Wang

2006

Int J Adv Manuf Technol

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This paper presents the application of principal components analysis for Taguchi orthogonal experiments to develop a robust electron beam welding treatment (EBWT) process with high efficiency multiple performance characteristics (MPCs). In this study, the principal components analysis (PCA) design incorporating the correlation matrix of tested trials is employed. In the first step, the MPCs are reduced to two independent components using PCA. Both components accounted for 98.8% of the total variance. The first principal component (PC), which refers to the integrated hardening capability index of the EBWT process, accounts for 70.7% of the total variation. The remaining 28.1% were contributed by the second PC, which can be interpreted as the penetration capability index. In the second step, we identify the most important PC loading vectors using PCA, and estimate the importance of the PCs. By using PCA, relationships between different MPCs can be investigated and the most important factors for the variance of the EBWT process can be identified.The experimental results show that redundant information could be eliminated by using principal components in conjunction with Taguchi's orthogonal array experiments. This proposed approach is simple, effective, and efficient for developing a robust and high-efficiency EBWT process of high quality. In this study, the MPCs in the EBWT process are successfully optimized.Keywords Electron beam welding treatment (EBWT) 9 Multiple performance characteristic (MPC) 9 Optimization 9 Principal components analysis (PCA)

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“…The failure load directly influences the welding quality and therefore is considered one of the most important features in the welding process. The proper selection of spot welding parameters is essential in carrying out a convincing failure load analysis [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…By using the experimental design and regression analysis, some researchers [3][4][5][6] have tried to develop empirical formulas for analyzing the relationship between the welding quality and process parameters. The spot welding process is intrinsically nonlinear, and additionally is a highly coupled multivariable system.…”

Section: Introductionmentioning

confidence: 99%

Welding parameters optimization for economic design using neural approximation and genetic algorithm

Tseng

2005

Int J Adv Manuf Technol

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Welding is a basic manufacturing process for making components or assemblies. Recent welding economics research has focused on developing the reliable machinery database to ensure optimum production. It is an important issue, especially for the expensive equipment and the high quality preference in welding. An integrated approach is proposed to address the welding economic design problem. The integrated approach applies general regression neural network to approximate the relationship between welding parameters (welding current, electrode force, welding time, and sheet thickness) and the failure load. Analytical formula can be generated from the trained general regression neural network, and the mathematical model for the economic welding design can be constructed. An optimization method based on genetic algorithms is then applied to resolve the mathematical model and to select the optimum welding parameters. These parameters are used to obtain the preferred welding quality at the least possible cost.

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Development of an Intelligent System for Selection of the Process Variables in Gas Metal Arc Welding Processes

Cited by 22 publications

References 3 publications

Optimización multiobjetivo del proceso de soldeo GMAW de la aleación AA 6063-T5 basado en la penetración y en la zona afectada térmicamente

Optimización multiobjetivo del proceso de soldeo GMAW de la aleación AA 6063-T5 basado en la penetración y en la zona afectada térmicamente

Using a principal components analysis for developing a robust design of electron beam welding

Welding parameters optimization for economic design using neural approximation and genetic algorithm

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