Optimization of Process Parameters for Submerged Arc Welding by Weighted Principal Component Analysis Based Taguchi Method

In submerged arc welding (SAW), weld quality is greatly affected by the weld parameters such as welding current, traverse speed, arc voltage and stickout since they are closely related to weld joint. The joint quality can be defined in terms of properties such as weld bead geometry and mechanical properties. There are several control parameters which directly or indirectly affect the response parameters. In the present study, an attempt has been made to search an optimal parametric combination, capable of producing desired high quality joint in submerged arc weldment by Taguchi method coupled with weighted principal component analysis. In the present investigation three process variables viz. Wire feed rate (Wf), stick out (So) and traverse speed (Tr) have been considered and the response parameters are hardness, tensile strength (Ts), toughness (IS).

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Bead Geometry Optimization of Submerged Arc Weld: Exploration of Weighted Principal Component Analysis (WPCA)

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.110-116.790 ◽

2011 ◽

Vol 110-116 ◽

pp. 790-798 ◽

Cited By ~ 5

Author(s):

A. Biswas ◽

S. Bhaumik ◽

Gautam Majumdar ◽

Saurav Datta ◽

S.S. Mahapatra

Keyword(s):

Principal Component Analysis ◽

Taguchi Method ◽

Principal Components ◽

Principal Component ◽

Component Analysis ◽

Optimization Techniques ◽

Confirmatory Test ◽

Bead Geometry ◽

Weighted Principal Component ◽

Submerged Arc

The present work attempts to overcome underlying assumptions in traditional Taguchi based optimization techniques highlighted in literature. Taguchi method alone fails to solve multi-response optimization problems. In order to overcome this limitation, exploration of grey relation theory, desirability function approach, utility theory etc. have been found amply applied in literature in combination with Taguchi method. But aforesaid approaches relies on the assumption that individual response features are uncorrelated i.e. independent of each other which are really impossible to happen in practice. The study takes into account this response correlation and proposes an integrated methodology in a case study on optimization of multiple bead geometry parameters of submerged arc weldment. Weighted Principal Component Analysis (WPCA) has been applied to eliminate response correlation and to convert correlated responses into equal or less number of uncorrelated quality indices called principal components. Based on individual principal components a Multi-response Performance Index (MPI) has been introduced to derive an equivalent single objective function which has been optimized (maximized) using Taguchi method. Experiments have been conducted based on Taguchi’s L25 Orthogonal Array design with combinations of process control parameters: voltage, wire feed, welding speed and electrode stick-out. Different bead geometry parameters: bead width, bead height, penetration depth and HAZ dimensions have been optimized. Optimal result has been verified by confirmatory test. The study highlights effectiveness of the proposed method for solving multi-objective optimization of submerged arc weld.

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USE OF DESIRABILITY FUNCTION AND PRINCIPAL COMPONENT ANALYSIS IN GREY-TAGUCHI APPROACH TO SOLVE CORRELATED MULTI-RESPONSE OPTIMIZATION IN SUBMERGED ARC WELDING

Journal of Advanced Manufacturing Systems ◽

10.1142/s0219686710001843 ◽

2010 ◽

Vol 09 (02) ◽

pp. 117-128 ◽

Cited By ~ 4

Author(s):

SAURAV DATTA ◽

SIBA SANKAR MAHAPATRA

Keyword(s):

Principal Component Analysis ◽

Process Parameters ◽

Arc Welding ◽

Principal Component ◽

Integrated Approach ◽

Submerged Arc Welding ◽

Quality Indices ◽

Grey Relational ◽

Submerged Arc ◽

Grey Taguchi

Submerged arc welding (SAW) is an important metal fabrication technology specially applied to join metals of large thickness in a single pass. In order to obtain an efficient joint, several process parameters of SAW need to be studied and precisely selected to improve the bead quality. Many methodologies have been proposed in the past research to address this issue. However, a good number of past works seek to optimize SAW process parameters with only one response. In practical situations, not only influence of process parameters and their interactive effects on output responses are to be critically examined but also attempt is to be made to optimize more than one response simultaneously. To this end, the present study considers four process control parameters viz. voltage (OCV), wire feed rate, traverse speed and electrode stick-out. The selected weld quality characteristics related to features of bead geometry are depth of penetration, reinforcement and bead width. An integrated approach capable of overcoming the drawbacks of traditional optimization approaches has been suggested and results thereof analyzed. The proposed approach explores Orthogonal Array (OA) experiments for adaptation to grey-Taguchi method. Principal Component Analysis (PCA) has been used to convert correlated response values into uncorrelated quality indices called principal components. Based on desirability loss, grey relational coefficients of each quality indices have been calculated. These coefficients have been further accumulated to calculate overall grey relational grade. Individual response weights have been calculated using entropy measurement technique. Finally, Taguchi method has been adopted for optimization purpose. The study finally demonstrates the robustness and flexibility of the integrated approach in solving multi-criteria optimization problem in SAW process.

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The Use of Taguchi Method Based on Desirability Function Approach for Optimization of Process Parameters in Submerged Arc Welding

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.622-623.319 ◽

2012 ◽

Vol 622-623 ◽

pp. 319-322

Author(s):

Joydeep Roy ◽

John Deb Barma ◽

Subhash Chandra Saha

Keyword(s):

Taguchi Method ◽

Process Parameters ◽

Arc Welding ◽

Desirability Function ◽

Traverse Speed ◽

Submerged Arc Welding ◽

Function Approach ◽

Confirmatory Test ◽

Submerged Arc ◽

Desirability Function Approach

In this paper, the Taguchi method coupled with desirability function approach is used for the optimization of response parameters in submerged arc welding (SAW). Desirability function (DF) approach has been introduced to convert the multi- response objective to single objective. Weld quality is greatly influenced by the weld parameters which directly or indirectly affect the response parameters. In the present investigation three process variables viz. Wire feed rate (Wf), stick out (So) and traverse speed (Ts) have been considered and the response parameters are hardness (H), tensile strength (TS), toughness (IS). Finally a confirmatory test has been carried out with the optimal process parameters for validation of the experiment.

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Multiple Performance Characteristics Optimization in the WEDM Process of SKD61 Tool Steel Using Taguchi Method Combined with Weighted Principal Component Analysis (WPCA)

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.758.21 ◽

2015 ◽

Vol 758 ◽

pp. 21-27 ◽

Cited By ~ 1

Author(s):

Bobby O.P. Soepangkat ◽

H.C. Kis Agustin

Keyword(s):

Principal Component Analysis ◽

Taguchi Method ◽

Tool Steel ◽

Electrical Discharge Machining ◽

Principal Component ◽

Component Analysis ◽

Performance Characteristics ◽

Machining Parameters ◽

Weighted Principal Component ◽

Wedm Process

This paper presents the optimization of a wire electrical discharge machining (WEDM) process of SKD61 tool steel (AISI H13). The use of the Taguchi method coupled with weighted principal component analysis (WPCA) has been applied. The WEDM machining parameters (arc on time, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., recast layer thickness (RL) and surface roughness (SR). The quality characteristics of both RL and SR were smaller-is-better. WPCA was applied to eliminate response correlation and to convert correlated responses into equal or less number of uncorrelated quality indices called principal components. Experimental results have shown that machining performance of the WEDM process can be improved effectively through the combination of Taguchi method and WPCA.

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