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F.L Cheong

Bio: F.L Cheong is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Electrode & Welding. The author has an hindex of 1, co-authored 1 publications receiving 99 citations.
Topics: Electrode, Welding

Papers
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Journal ArticleDOI
TL;DR: In this paper, the effect of current, electrode polarity, electrode diameter and electrode extension on the melting rate, bead height, bead width and weld penetration in submerged arc welding was analyzed.

113 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, an attempt is made to establish input-output relationships in MIG welding process through regression analyses carried out both globally (i.e., one set of response equations for the entire range of the variables) as well as cluster-wise.

59 citations

Journal Article
TL;DR: In this paper, a set of experimental data has been used to assess the influence of GMAW process parameters in weld bead geometry, and the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the GMAw process parameters.
Abstract: Gas Metal Arc Welding (GMAW) processes is an important joining process widely used in metal fabrication industries. This paper addresses modeling and optimization of this technique using a set of experimental data and regression analysis. The set of experimental data has been used to assess the influence of GMAW process parameters in weld bead geometry. The process variables considered here include voltage (V); wire feed rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate distance (D). The process output characteristics include weld bead height, width and penetration. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the GMAW process parameters. The objective is to determine a suitable set of process parameters that can produce desired bead geometry, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure. Keywords—Weld Bead Geometry, GMAW welding, Process parameters Optimization, Modeling, SA algorithm

59 citations

Journal ArticleDOI
TL;DR: In this article, an attempt is made to determine input-output relationships of the MIG welding process by using regression analysis based on the data collected as per full-factorial design of experiments.
Abstract: In this paper, an attempt is made to determine input-output relationships of the MIG welding process by using regression analysis based on the data collected as per full-factorial design of experiments. The effects of the welding parameters and their interaction terms on different responses have been analyzed using statistical methods. Both linear as well as nonlinear regression analyses are employed to establish the input-output relations. The results of these regression techniques are compared and some concluding remarks are made.

50 citations

Proceedings ArticleDOI
10 Apr 2013
TL;DR: In this paper, the application of Taguchi technique and regression analysis to determine the optimal process parameters for submerged arc welding (SAW) has been described, where the planned experiments are conducted in the semiautomatic underwater arc welding machine and the signal-to-noise ratios are computed to calculate the optimum parameters.
Abstract: This paper details the application of Taguchi technique and regression analysis to determine the optimal process parameters for submerged arc welding (SAW). The planned experiments are conducted in the semiautomatic submerged arc welding machine and the signal-to-noise ratios are computed to determine the optimum parameters. The percentage contribution of each factor is validated by analysis of variance (ANOVA) technique. Multiple regression analysis (MRA) is conducted using statistical package for social science (SPSS) software and the mathematical model is built to predict the bead geometry for any given welding conditions.

49 citations

Journal ArticleDOI
TL;DR: In this paper, a regression analysis was performed to set up input-output relationships in the submerged arc welding (SAW) process and the influence of the input variables on weld bead geometry was represented as graphs.

40 citations