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.

Principal Component Analysis of Correlated WEDM Performance Characteristics during Machining ZC63/SiCP MMCs

2014 ◽  
Vol 14 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Thella Babu Rao ◽  
A. Gopala Krishna
Keyword(s):  
Principal Component Analysis ◽  
Quality Index ◽  
Optimization Problem ◽  
Principal Component ◽  
Component Analysis ◽  
Machining Process ◽  
Total Quality ◽  
Process Variables ◽  
Optimal Process ◽  
Pulse On Time

AbstractThe present investigation proposes the optimization of the wire electrical discharge machining process for machining ZC63/SiCP metal matrix composite. SiC particulate size and its percentage with the matrix are considered as the process variables along with the most significant WEDM variables such as pulse-on time, pulse-off time and wire tension. In view of quality cut, surface roughness, metal removal rate and kerf are considered as the process responses. Since, these responses are correlated with each other and they need to be optimized simultaneously. Therefore, the problem is treated as multi-response optimization problem. Principal component analysis (PCA) has been implemented to convert the multi-objective optimization problem in to single objective optimization problem by converting the multiple correlated responses in to the total quality index. Taguchi's robust optimization technique has been adopted to derive the set optimal process parameters which maximize the total quality index. The derived optimal process responses are confirmed with the experimental validation tests. ANOVA is conducted find the importance of the chosen process variables on the overall quality of the machined component. The practical possibility of the obtained optimal process performance is observed using SEM studies.

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.

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).

Optimizing parameters for continuous electrospinning of polyacrylonitrile nanofibrous yarn using the Taguchi method

2017 ◽  
Vol 48 (3) ◽  
pp. 559-579 ◽  
Author(s):  
Chang-Mou Wu ◽  
Ching-Hsiang Hsu ◽  
Ching-Iuan Su ◽  
Chun-Liang Liu ◽  
Jiunn-Yih Lee
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Flow Rate ◽  
Draw Ratio ◽  
Principal Component ◽  
Quality Characteristics ◽  
Optimal Parameters ◽  
Signal To Noise ◽  
Multiple Quality Characteristics ◽  
Nanofibrous Yarn

In this study, the Taguchi method, analysis of variance, and principal component analysis were used to design the optimal parameters with respect to different quality characteristics for the continuous electrospinning of polyacrylonitrile nanofibrous yarn. The experiment was designed using a Taguchi L9(34) orthogonal array. The Taguchi method is a unique statistical method for efficiently evaluating optimal parameters and the effects of different factors on quality characteristics. The experimental results obtained by this method are more accurate and reliable than one-factor-at-a-time experiments. The control factors discussed in this work include the draw ratio, nozzle size, flow rate, and draw temperature. The quality characteristics taken into consideration are fiber diameter, fiber uniformity, and fiber arrangement. The parameters to optimize the different quality characteristics were obtained from the main effect plot of the signal-to-noise ratios, after which analysis of variance and confidence intervals were applied to confirm that the results were acceptable. Multiple quality characteristics were analyzed by principal component analysis from the normalized signal-to-noise ratios and the principal component score. Combining the experimental and analysis results, the optimum parameters for multiple quality characteristics were found to be a draw ratio of 2.0, a nozzle number of 22 G, a flow rate of 7 ml/h, and a draw temperature 120℃.

COMBINING TAGUCHI METHOD, PRINCIPAL COMPONENT ANALYSIS AND FUZZY LOGIC TO THE TOLERANCE DESIGN OF A DUAL-PURPOSE SIX-BAR MECHANISM

2010 ◽  
Vol 34 (2) ◽  
pp. 277-293 ◽  
Author(s):  
Fu-Chen Chen ◽  
Yih-Fong Tzeng ◽  
Meng-Hui Hsu ◽  
Wei-Ren Chen
Keyword(s):  
Principal Component Analysis ◽  
Fuzzy Logic ◽  
Taguchi Method ◽  
Hybrid Approach ◽  
Principal Component ◽  
Component Analysis ◽  
Tolerance Design ◽  
Dual Purpose ◽  
Control Factors ◽  
Key Dimensions

A hybrid approach of combining Taguchi method, principal component analysis and fuzzy logic for the tolerance design of a dual-purpose six-bar mechanism is proposed. The approach is to firstly use the Taguchi orthogonal array to carry out experiments for calculating the S/N ratios of the positional errors to the angular error of the dual-purpose six-bar mechanism. The principal component analysis is then applied to determine the principal components of the S/N ratios, which are transformed via fuzzy logic reasoning into a multiple performance index (MPI) for further analysis of the effect of each control factors on the quality of the mechanism. Through the analysis of response table and diagram, key dimensional tolerances can be classified, which allows the decision of either to tighten the key tolerances to improve mechanism quality or to relax the tolerance of non-key dimensions to reduce manufacturing costs to be made.

scholarly journals Neural network design and feature selection using principal component analysis and Taguchi method for identifying wood veneer defects

2014 ◽  
Vol 2 (1) ◽  
pp. 291-308 ◽  
Author(s):  
Baris Yuce ◽  
Ernesto Mastrocinque ◽  
Michael Sylvester Packianather ◽  
Duc Pham ◽  
Alfredo Lambiase ◽  
...  
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Feature Selection ◽  
Taguchi Method ◽  
Network Design ◽  
Principal Component ◽  
Component Analysis ◽  
Wood Veneer
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