Optimization and modeling of spot welding parameters with simultaneous multiple response consideration using multi-objective Taguchi method and RSM

Muhammad, Norasiah; Manurung, Yupiter Harangan Prasada; Hafidzi, Mohammad; Abas, Sunhaji Kiyai; Tham, Ghalib; Haruman, Esa

doi:10.1007/s12206-012-0618-x

Cited by 61 publications

(24 citation statements)

References 11 publications

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“…Though all the three input variables affected the failure energy, ANOVA indicates that welding current contributed more on the failure energy, followed by welding time and electrode force. The optimum process parameters maximizing the failure energy of the welded joints developed from the mathematical model using AFSA were respectively welding time of 9.54 ms, welding current of 2.4 kA, and electrode force of 127 N. Norasiah Muhammad et al [7] aimed to Optimize and modelled spot welding parameters with simultaneous multiple response consideration using multi-objective Taguchi method and RSM. In this paper an alternative method to optimize process parameters of resistance spot welding (RSW) towards weld zone development.…”

Section: ©Ijraset (Ugc Approved Journal): All Rights Are Reservedmentioning

confidence: 99%

Analysis and Optimization of Process Parameters of Resistance Spot Welding Process Using Response Surface Method-A Review

Gawai¹

2018

IJRASET

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Resistance Spot welding is low cost and adequate which has made it highly popular in the making of sheet joints. Various types of resistance welding are developed for producing continuous and pressure tight joints on overlapped materials. Controlling the welding parameters plays an important role in the quality of the weld. This paper reviews on various effects of process parameters on response variables. Input parameters such as welding current, weld time, electrode force and electrode geometry effects on the response variables such as tensile strength, hardness, nugget size. In any automobile, there are 3000-6000 spot welds which demonstrate the level significance of the resistance spot welding. Controlling the welding parameters assumes an imperative part on the nature of the weld.Quality and strength of the welds and therefore body mainly are defined by quality of the weld nuggets. Resistance Spot Welding (RSW) is widely used for its low cost, high speed; simple mechanism and applicability for automation. There are various process parameters (weld current, weld time, pressure) which affect the weld nugget and its strength. So it is necessary to optimize the process parameters of resistance spot welding process. Therefore it is very important to understand the behaviour of spot welds and their failure characteristics.

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Section: ©Ijraset (Ugc Approved Journal): All Rights Are Reservedmentioning

confidence: 99%

Analysis and Optimization of Process Parameters of Resistance Spot Welding Process Using Response Surface Method-A Review

Gawai¹

2018

IJRASET

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“…Furthermore, Taguchi parameter design can reduce the fluctuation of system performance and quality to the source of variation. The signalto-noise (S/N) ratio (η) represents the ratio of the mean to the square deviation to measure the quality characteristic deviation from the desired value and can be computed as [20,21]:…”

Section: Experimental Design and Proceduresmentioning

confidence: 99%

Effect of Process Parameters on the Mechanical Properties and Failure Behavior of Spot Welded Low Carbon Steel

et al. 2015

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In this research, the effect of spot welding parameters on weld quality was investigated. The main affecting welding parameters such as weld current, weld time, electrode force and holding time were determined as the basis for quality evaluation. The selected quality features were classified into mechanical properties and failure behavior, which were required for application with highly dynamic loading. The peak load as one of the important mechanical properties, as well as the two distinct failure modes which were cross-nugget and complete button pull, were observed using tensile-shear stress. To obtain detailed shear stress testing results and to determine the significance of parameters, a servo-hydraulic testing machine was run at a constant cross-head speed of 2mm/min followed by statistical analysis methods, which were Taguchi's L 16 orthogonal array and Analysis of Variance (ANOVA). Furthermore, the failure mode was to be observed based on the fracture surface used as reference for acceptance or rejection of the weld joint. Based on the results, the weld current was the significant factor affecting shear stress and the complete button pull was mostly found, which leads to the satisfactory condition of the joint. Cross-nugget and full button pull-out were the dominant failures observed in the lap-shear test. The cross-nugget failure leads to a low shear load, while complete button pull-out displays maximum shear load.

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“…Good bond density at weld interface of USWAL alloy joints was due to the combine effects of temperature rise around the horns tip and intensity of weld interface waviness. [8] The significant effect of weld parameters are analyzed on the resistant spot welding from developed linear response surface model. The prediction based on the nugget radius and the intention of the nugget radius justified for steel joints.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Spot Welding Parameters for Dissimilar Weld Joints

Sankar¹,

Lawrence²,

Jayabal³

2016

BIJIEMS

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Optimization and modeling of spot welding parameters with simultaneous multiple response consideration using multi-objective Taguchi method and RSM

Cited by 61 publications

References 11 publications

Analysis and Optimization of Process Parameters of Resistance Spot Welding Process Using Response Surface Method-A Review

Analysis and Optimization of Process Parameters of Resistance Spot Welding Process Using Response Surface Method-A Review

Effect of Process Parameters on the Mechanical Properties and Failure Behavior of Spot Welded Low Carbon Steel

Prediction of Spot Welding Parameters for Dissimilar Weld Joints

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