Optimization of Thermal Friction Drilling Using Grey Relational Analysis

Abstract:

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The main purpose of this research is to study the optimal machining parameters for a novel process of thermal friction drilling on SUS 304 stainless steel. The experiments were conducted according to an L9 orthogonal array based on Taguchi experimental designs method, and the multiple performance characteristics correlated with surface roughness (SR) and bush length (BL) was investigated by grey relational analysis systematically and comprehensively. Moreover, the significant machining parameters that most intensively affected the multiple performance characteristic and the optimal combination levels of machining parameters associated with the thermal friction drilling on SUS 304 stainless steel were determined through the analysis of variance (ANOVA) and the response graph of grey relational grade. The main machining parameters of the thermal friction drilling such as friction angle, friction contact area ratio, feed rate, and drilling speed were selected to evaluate the effects on SR and BL. The experimental results show that the thermal friction drilling revealed beneficial effects on SR and BL for drilling processes. Moreover, the optimal machining parameters for multiple performance characteristics associated with SR and BL were attained. The developed thermal friction drilling avoids serious tool wears, enhances the surface quality of the machined hole, and prolongs the tool life significantly.

Info:

Periodical:

Advanced Materials Research (Volumes 154-155)

Edited by:

Zhengyi Jiang, Xianghua Liu and Jinglong Bu

Pages:

1726-1738

DOI:

10.4028/www.scientific.net/AMR.154-155.1726

Citation:

W. L. Ku et al., "Optimization of Thermal Friction Drilling Using Grey Relational Analysis", Advanced Materials Research, Vols. 154-155, pp. 1726-1738, 2011

Online since:

October 2010

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Price:

$35.00

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