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

2015 ◽  
Vol 758 ◽  
pp. 21-27 ◽  
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.

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

2012 ◽  
Vol 622-623 ◽  
pp. 45-50 ◽  
Author(s):  
Joydeep Roy ◽  
Bishop D. Barma ◽  
J. Deb Barma ◽  
S.C. Saha
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Arc Welding ◽  
Principal Component ◽  
Traverse Speed ◽  
Component Analysis ◽  
Submerged Arc Welding ◽  
Bead Geometry ◽  
Weighted Principal Component ◽  
Submerged Arc

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).

Multi-Objective Optimization of EDM Process Parameters using Taguchi Method, Principal Component Analysis and Grey Relational Analysis

2014 ◽  
Vol 4 (2) ◽  
pp. 29-46 ◽  
Author(s):  
U. Shrinivas Balraj ◽  
A. Gopala Krishna
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Electrical Discharge Machining ◽  
Principal Component ◽  
Component Analysis ◽  
Optimum Process ◽  
Relational Analysis ◽  
Grey Relational

This paper investigates multi-objective optimization of electrical discharge machining process parameters using a new combination of Taguchi method and principal component analysis based grey relational analysis. In this study, three conflicting performance characteristics related to surface integrity such as surface roughness, white layer thickness and surface crack density are considered in electrical discharge machining of RENE80 nickel super alloy. The process parameters considered are peak current, pulse on time and pulse off time. The experiments are conducted based on Taguchi method and these experimental results are used in grey relational analysis and weights of the corresponding performance characteristics are determined by principal component analysis. The weighted grey relational grade is used as a performance index to determine optimum process parameters and results of the confirmation experiments indicate that the combined approach is effective in determining optimum process parameters.

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

2011 ◽  
Vol 110-116 ◽  
pp. 790-798 ◽  
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.

Optimization of Tool Wear, Surface Roughness and Material Removal Rate in the Milling Process of Al 6061 Using Taguchi and Weighted Principal Component Analysis (WPCA)

2014 ◽  
Vol 493 ◽  
pp. 535-540 ◽  
Author(s):  
Laily Ulfiyah ◽  
Bambang Pramujati ◽  
Bobby Oedy Pramoedyo Soepangkat
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Principal Component ◽  
Milling Process ◽  
Performance Characteristics ◽  
Weighted Principal Component ◽  
End Milling Process

In the metal cutting industry, end milling has an important role in cutting metal to obtain the various required shapes and size. This study takes Al 6061 as working material and investigates three performance characteristics, i.e., tool wear (VB), surface roughness (Ra) and material removal rate (MRR), with Taguchi method and WPCA for determining the optimal parameters in the end milling process. The performance characteristic of MRR is larger-the-better while VB and Ra are having smaller-the-better performance characteristic. Based on Taguchi method, an L18 mixed-orthogonal array was chosen for the experiments. The optimization was conducted by using weighted principal component analysis (WPCA). As a result, the optimization of complicated multiple performance characteristics was transformed into the optimization of single response performance index. The most significant machining parameters which affected the multiple performance characteristics were type of milling operation, spindle speed, feed rate and depth of cut. Experimental result have also shown that machining performance characteristics of end milling process can improved effectively through the combination of Taguchi method and WPCA.

Optimization of Correlated Quality Characteristics in WEDM Process using Taguchi Approach Coupled with Principal Component Analysis

2013 ◽  
Vol 13 (3) ◽  
pp. 199-208 ◽  
Author(s):  
P.C. Padhi ◽  
S.S. Mahapatra ◽  
S.N. Yadav ◽  
D.K. Tripathy
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Optimization Problem ◽  
Principal Component ◽  
Component Analysis ◽  
Quality Characteristics ◽  
Confirmatory Test ◽  
Response Optimization ◽  
Pulse On Time ◽  
Wedm Process

AbstractIn the present work, an attempt has been made to solve the correlated multi-response optimization problem of wire electrical discharge machining (WEDM) of EN-31 steel. The experimental investigation have been carried out to evaluate the best process environment which could simultaneously satisfy multiple quality characteristics such as material removal rate (MRR), surface roughness (Ra) and dimensional deviation (DD). In view of the fact that traditional Taguchi method cannot solve a multi response optimization problem, weighted principal component analysis (WPCA) has been coupled with Taguchi method to overcome this limitation. The multiple responses are converted into a single response using principal component analysis so that influence of correlation among the responses can be eliminated. Values of individual principal components multiplied by their priority weight were added to calculate the composite principal component defined as multi-response performance index (MPI). MPI is used as response for optimization using Taguchi's L27 orthogonal array. From analysis of variance, pulse on time was found to be the most significant parameter. Finally, the optimal result obtained was verified through confirmatory test.

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