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.

Design of an optical lens for LED lighting using a hybrid principal components analysis–Taguchi method

2018 ◽  
Vol 51 (5) ◽  
pp. 788-802 ◽  
Author(s):  
WS Yip ◽  
S To ◽  
WK Wang
Keyword(s):  
Taguchi Method ◽  
Principal Components ◽  
Principal Component ◽  
Quality Characteristics ◽  
Quality Characteristic ◽  
Optical Lens ◽  
Light Emitting ◽  
Multiple Quality Characteristics ◽  
Optimum Parameters ◽  
Components Analysis

Optical lenses are extensively used to enhance the performance of light-emitting diodes. Both uniformity and efficiency are important performance indicators in lens design; however, improving uniformity always lowers efficiency. In this study, the Taguchi method and principal component analysis (PCA) are integrated to optimise the lens shape for two quality objectives, namely, uniformity and efficiency. The Taguchi method was conducted twice to establish the signal/noise ratio of the two quality characteristics for calculating the principal components in PCA. Then, the optimum parameters obtained by the Taguchi method were processed by PCA. The correlated individual responses were converted to the principal components which explained most of the dataset and were considered as the single quality characteristic for the optimisation. The combined method resolved the difficulties of optimising multiple quality characteristics without sacrificing any particular quality characteristic while the traditional Taguchi method can only be applied to the single quality characteristic. A LED light source fitted with a secondary lens designed by the proposed method showed over 92% light efficiency and an improvement in uniformity.

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.

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).

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.

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