The use of the Taguchi method with grey relational analysis and a neural network to optimize a novel GMA welding process

Lin, Hsuan-Liang

doi:10.1007/s10845-010-0468-2

Cited by 61 publications

(26 citation statements)

References 16 publications

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“…In the current model, all the abrasives are considered to be identical in shape and size [19,28,64,68,69,70]. An abrasive particle is considered to be spherical but with local spherical bulges as shown in figure 3 The abrasive particles are characterized by the average grit diameter, d g [37,59,65,69,71,72].…”

Section: Traditional Ultrasonic Machiningmentioning

confidence: 99%

“…4 shows the interaction between the abrasive grit and the work-piece and tool. As the indentation proceeds, the contact zone between the abrasive grit and work-piece is established and the same grows [15,37,48,68,69,70,73]. The contact zone is circular in nature and is characterized by its diameter '2x'.…”

Section: Traditional Ultrasonic Machiningmentioning

confidence: 99%

“…The color of the glass is changed by adding some ingredient like metallic salt, zinc etc. [68,70,71]. These type of colored glass is used in manufacturing the art object, stained glass window, color glass window and many more applications.…”

Section: Type Of Glass and Applicationmentioning

confidence: 99%

“…If the enough energy is taken from the bullet, it will eventually stop it from passing through [69]. Some important properties of these material make them so famous and the utility of these materials are increased in present era [69,70,71,90,94,95,96,97,98]. Figure 10 shoes the acrylic heat resistant glass material.…”

Section: Polycarbonate and Acrylic Glassmentioning

confidence: 99%

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Mathematical Modeling for Material Removal and Optimization of Ultrasonic Drilling of Polycarbonate and Acrylic Glass for Surface Roughness by GRA Approach

Singh¹

2017

IJMEA

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Abstract:Polycarbonate bullet proof and acrylic heat resistant glasses are used as the functional material in many industrial application. In automobile industries, banks and cabins, polycarbonate bullet proof glass has been used for security purpose. Similarly, acrylic heat resistant glass is used in furnace, microwaves, space craft and airplane applications. In this experimental research paper, Taguchi modal and Grey relational analysis are utilized for the ultrasonic drilling in these materials. For experimentation, input parameters are concentration, abrasive, grit size, power rating, hydrofluoric acid and tool materials. Output parameters are material removal rate, tool wear rate and surface roughness. In which, surface roughness is most significant output parameter, because it describe accuracy of the process. Through optimization analysis, Taguchi modal suggest that 40% abrasive concentration, mixture of (Alumina, Silicon carbide and Boron carbide) abrasive in 1:1:1, 600 grit of abrasive and 1.5% hydrofluoric acid gives best results for drilling in polycarbonate bullet proof glass material. Similarly, in acrylic heat resistant glass, mixture of Silicon carbide and Boron carbide (1:1), 600 grit abrasive and 1% hydrofluoric acid gives the optimum results. Concentration of slurry, abrasive grit size and hydrofluoric acid are the most significant parameters for ultrasonic drilling in both materials. Through Grey relational analysis the surface roughness is improved by 40% and 48% in polycarbonate (UL-752) and acrylic (BS-476) glass respectively.

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Section: Traditional Ultrasonic Machiningmentioning

confidence: 99%

Section: Traditional Ultrasonic Machiningmentioning

confidence: 99%

Section: Type Of Glass and Applicationmentioning

confidence: 99%

Section: Polycarbonate and Acrylic Glassmentioning

confidence: 99%

See 2 more Smart Citations

Mathematical Modeling for Material Removal and Optimization of Ultrasonic Drilling of Polycarbonate and Acrylic Glass for Surface Roughness by GRA Approach

Singh¹

2017

IJMEA

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“…In this study, the Mahalanobis-Taguchi System (MTS) was employed to improve tablet PC product-testing processes. Data were collected and analyzed, and scientific verification methods were employed to elucidate the product characteristics and construct meaningful models [5][6][7][8]. After the rationality of the tablet PC product testing items was evaluated, those that made small contributions were removed to facilitate accurate and rapid product testing.…”

Section: Introductionmentioning

confidence: 99%

Applying the Mahalanobis–Taguchi System to Improve Tablet PC Production Processes

Peng

Tsai

et al. 2017

Sustainability

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Product testing is a critical step in tablet PC manufacturing processes. Purchases of testing equipment and on-site testing personnel increase overall manufacturing costs. In addition, to improve manufacturing capabilities, manufacturers must also produce products with higher quality and at a lower cost than their competitors if they are to attract consumers and gain a competitive edge in their industry. The Mahalanobis-Taguchi System (MTS) is a novel technique proposed by Genichi Taguchi for performing diagnoses and forecasting with multivariate data. The MTS can be used to select important factors and has been applied in numerous engineering fields to improve product and process quality. In the present study, the MTS, logistic regression, and a neural network were used to improve the tablet PC product testing process. The results indicated that the MTS attained 98% predictive power after insignificant test items were eliminated. The MTS performance was superior to those of the conventional logistic regression and neural network, which attained 93.3% and 94.7% predictive power, respectively. After the testing process was improved using the MTS, the number of test items in the tablet PC product testing process was reduced from 56 to 14. This facilitated the development of more stable test site configurations and effectively reduced the testing time, number of testers required, and equipment costs.

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An improved artificial neural network for laser welding parameter selection and prediction

Zhong

Xue

Shi

2013

Int J Adv Manuf Technol

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The use of the Taguchi method with grey relational analysis and a neural network to optimize a novel GMA welding process

Cited by 61 publications

References 16 publications

Mathematical Modeling for Material Removal and Optimization of Ultrasonic Drilling of Polycarbonate and Acrylic Glass for Surface Roughness by GRA Approach

Mathematical Modeling for Material Removal and Optimization of Ultrasonic Drilling of Polycarbonate and Acrylic Glass for Surface Roughness by GRA Approach

Applying the Mahalanobis–Taguchi System to Improve Tablet PC Production Processes

An improved artificial neural network for laser welding parameter selection and prediction

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