A study of multi-quality processing parameter optimization for sueded fabric

2016 ◽  
Vol 87 (4) ◽  
pp. 389-398 ◽  
Author(s):  
Chung-Feng Jeffrey Kuo ◽  
Wen-Tsung Lin
Keyword(s):  
Taguchi Method ◽  
Color Difference ◽  
Processing Parameters ◽  
Quality Characteristics ◽  
Gray Relational Analysis ◽  
Processing Parameter ◽  
Optimum Processing ◽  
Multiple Quality Characteristics ◽  
Response Table ◽  
Fabric Surface

Sueded fabric quality control depends on the processing parameter settings. The quality characteristics considered in this study are surface softness and color difference. The Taguchi method was combined with gray relational analysis (GRA) to optimize the multi-quality sueding processing parameter combinations. First, an orthogonal array is designed by using the design of experiments of the Taguchi method for the major processing parameters of the sueding machine. The signal/noise ratio and analysis of variance are calculated from the measured fabric surface softness and color difference data, significant factors influencing the quality characteristics obtained, and GRA used to remedy the deficiency in the Taguchi method, which is only applicable to single-quality characteristics. The optimum processing parameters of multiple-quality characteristics are obtained from the response table and response diagram of GRA. The quality of suede fabric can be controlled effectively by using the optimum processing parameters to set the processing parameters, and the 95% confidence interval validates the reliability and reproducibility of the experiment.

Multi-Objective Optimization of Thermo-Ultrasonic Flip-Chip Bonding Process for High-Brightness Light Emitting Diodes

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Chung-Feng Jeffrey Kuo ◽  
Hui-Ta Chen ◽  
Te-Li Su ◽  
Jr-Da Huang
Keyword(s):  
Taguchi Method ◽  
Flip Chip ◽  
Processing Parameters ◽  
Quality Characteristics ◽  
Gray Relational Analysis ◽  
Light Emitting ◽  
Relational Analysis ◽  
Optimal Processing ◽  
Multiple Quality Characteristics ◽  
Flip Chip Bonding

Flip-chip bonding is a kind of chip packaging technology, which can make fabricated chips lighter and smaller. Thermo-ultrasonic flip-chip bonding is a technology that directly joins gold pad and gold bump. This study combines principle component analysis and gray relational analysis to determine the optimal processing parameters for multiple quality characteristics of light emitting diodes (LEDs). The quality characteristics of this experiment include the candle light, forward voltage, and leakage current of LED and thrust value. First, this study determines the processing parameters that may affect the thermo-ultrasonic flip-chip bonding with the L18 orthogonal array, including substrate temperature, bonding downforce, ultrasonic working time, ultrasonic power, and rising and delay time of tool head bonding. Then, the gray relational analysis is applied to indicate the optimal processing parameters for the multiple quality characteristics of LED. Since the Taguchi method only takes one single quality characteristic into consideration, this study applies the Taguchi method to reduce the number of thermo-ultrasonic flip-chip bonding experiments. The experimental results prove that the optimal LED has good integral quality, which is above industrial standard.

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℃.

scholarly journals Grey-Taguchi-Based Optimization of Wire-Sawing for a Slicing Ceramic

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1602
Author(s):  
Yao-Yang Tsai ◽  
Jihng-Kuo Ho ◽  
Wen-Hao Wang ◽  
Chia-Chin Hsieh ◽  
Chung-Chen Tsao ◽  
...  
Keyword(s):  
Taguchi Method ◽  
Removal Rate ◽  
Mesh Size ◽  
Quality Characteristics ◽  
Machined Surface ◽  
Wire Tension ◽  
Slurry Concentration ◽  
Multiple Quality Characteristics ◽  
The Wire ◽  
Grey Taguchi

Slicing ceramic (SC) is well-known as difficult-to-cut material. It is a hard and brittle material. The Grey-Taguchi method, which converts multiple response problems into a single response, is used to determine the effect of the process parameters for wire-sawing on multiple quality characteristics. The wire-sawing parameters include the wire tension (T), the slurry concentration (C), mixed grains mesh size (G), the wire speed (S), and the working load (P). The machining quality characteristics include a material removal rate (MRR), machined surface roughness (SR) of SC, kerf width (KW), wire wear (WW), and flatness (FT). An analysis of variance (ANOVA) is used to identify the mixed grains and slurry concentration that have a significant effect on multiple quality characteristics. The results of the ANOVA using the Grey-Taguchi method show that the optimum conditions are T2C1G1S2P1 (wire tension of 24 N, slurry concentration of 10% wt., mixed grains of #600 + #1000 mesh size, wire speed of 2.8 m/s, and working load of 1.27 N). The respective improvement in MRR, machined SR of SC, KW, WW, and FT is 2.43%, 2.36%, 1.08%, 2.33%, and 14.27%. The addition of #600 + #1000 mixed grains mesh size to the slurry improves the machined SR of SC, KW, and WW. An increase in wire speed and working load and the use of appropriate mixed grains mesh size and slurry concentration increases the MRR for wire-saw machining.

Processing Parameters Optimization for Stagger Spinning of Trapezoidal Inner Gear

2011 ◽  
Vol 189-193 ◽  
pp. 2754-2758 ◽  
Author(s):  
Xiu Quan Cheng ◽  
Ling Yan Sun ◽  
Qin Xiang Xia
Keyword(s):  
Gear Tooth ◽  
Orthogonal Experiment ◽  
New Technology ◽  
Dimensional Accuracy ◽  
Processing Parameters ◽  
Parameters Optimization ◽  
Gray Relational Analysis ◽  
Processing Parameter ◽  
Forming Quality

Spin-forming of trapezoidal inner gear is a new technology of the near-net forming in gear manufacturing field. Processing parameters, such as the initial thickness of blank and radial reductions of each roller, greatly influence the forming quality of spun part. The forming quality of trapezoidal inner gear involves the filling status of gear tooth and dimensional accuracy of root circle. An approach for processing parameter optimization of the forming quality of the trapezoidal inner gear stagger spinning is proposed. The proposed approach integrates the orthogonal experiment design, gray relational analysis, and analysis of variance (ANOVA). The experiment result indicates that the proposed approach is effective in determining the optimized processing parameters for the stagger spinning of trapezoidal inner gear.

scholarly journals Practical Applications of Taguchi Method for Optimization of Processing Parameters for Plastic Injection Moulding: A Retrospective Review

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Ng Chin Fei ◽  
Nik Mizamzul Mehat ◽  
Shahrul Kamaruddin
Keyword(s):  
Taguchi Method ◽  
Injection Moulding ◽  
Principal Component ◽  
Processing Parameters ◽  
Great Success ◽  
Processing Parameter ◽  
Practical Applications ◽  
Multiple Parameters ◽  
Plastic Injection Moulding ◽  
Plastic Injection

Determining the optimal processing parameter is routinely performed in the plastic injection moulding industry as it has a direct and dramatic influence on product quality and costs. In this volatile and fiercely competitive market, traditional trial-and-error is no longer sufficient to meet the challenges of globalization. This paper aims to review the research of the practical use of Taguchi method in the optimization of processing parameters for injection moulding. Taguchi method has been employed with great success in experimental designs for problems with multiple parameters due to its practicality and robustness. However, it is realized that there is no single technique that appears to be superior in solving different kinds of problem. Improvements are to be expected by integrating the practical use of the Taguchi method into other optimization approaches to enhance the efficiency of the optimization process. The review will shed light on the standalone Taguchi method and integration of Taguchi method with various approaches including numerical simulation, grey relational analysis (GRA), principal component analysis (PCA), artificial neural network (ANN), and genetic algorithm (GA). All the features, advantages, and connection of the Taguchi-based optimization approaches are discussed.

Sign in / Sign up

Export Citation Format

Share Document