Optimization of correlated multiple quality characteristics robust design using principal component analysis

2004 ◽  
Vol 23 (4) ◽  
pp. 337
Keyword(s):  
Principal Component Analysis ◽  
Robust Design ◽  
Principal Component ◽  
Component Analysis ◽  
Quality Characteristics ◽  
Multiple Quality Characteristics

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℃.

Super-Efficiency DEA Approach for Optimizing Multiple Quality Characteristics in Parameter Design

2010 ◽  
Vol 1 (2) ◽  
pp. 58-71 ◽  
Author(s):  
Abbas Al-Refaie
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Quality Characteristics ◽  
Performance Measure ◽  
Parameter Design ◽  
Data Envelopment ◽  
Super Efficiency ◽  
Multiple Quality Characteristics ◽  
Decision Making Unit ◽  
Manufacturing Applications

This paper proposes an efficient approach for optimizing the multiple quality characteristics (QCHs) in manufacturing applications on the Taguchi method using the super efficiency technique in data envelopment analysis (DEA). Each experiment in Taguchi’s orthogonal array (OA) is treated as a decision making unit (DMU) with multiple QCHs set as inputs or outputs. DMU’s efficiency is measured then adopted as a performance measure to identify the combination of optimal factor levels. Three real case studies were employed for illustration in which the proposed approach provided the largest total anticipated improvements in multiple QCHs among other techniques such as principal component analysis (PCA) and DEA based ranking (DEAR) approach. Analysis of variance is finally employed to decide significant factor effects and to predict performance.

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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