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RISS 인기검색어
- 검색키워드
- 저자 : Nadeem Ahmad Mufti1 (검색결과 2 건)
- 무료
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Adeel Ikram,Nadeem Ahmad Mufti1,Muhammad Qaiser Saleem,Ahmed Raza Khan 대한기계학회 2013 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.27 No.7
This paper reports the effect and optimization of eight control factors on material removal rate (MRR), surface roughness and kerf in wire electrical discharge machining (WEDM) process for tool steel D2. The experimentation is performed under different cutting conditions of wire feed velocity, dielectric pressure, pulse on-time, pulse off-time, open voltage, wire tension and servo voltage by varying the material thickness. Taguchi’s L18 orthogonal array is employed for experimental design. Analysis of variance (ANOVA) and signal-tonoise (S/N) ratio are used as statistical analyses to identify the significant control factors and to achieve optimum levels respectively. Additionally, linear regression and additive models are developed for surface roughness, kerf and material removal rate (MRR). Results of the confirmatory experiments are found to be in good agreement with those predicted. It has been found that pulse on-time is the most significant factor affecting the surface roughness, kerf and material removal rate.
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Investigation of Cutting Parameters Effect for Minimization of Surface Roughness in Internal Turning
Muhammad Munawar,Joseph Ching-Shihn Chen,Nadeem Ahmad Mufti1 한국정밀공학회 2011 International Journal of Precision Engineering and Vol. No.
Minimizing the surface roughness is one of the primary objectives in most of the machining operations in general and in internal turning in particular. Poor control on the cutting parameters due to long boring bar generates non conforming parts which results in increase in cost and loss of productivity due to rework or scrap. In this study, the Taguchi method is used to minimize the surface roughness by investigating the rake angle effect on surface roughness in boring performed on a CNC lathe. The control parameters included besides tool rake angle were insert nose radius, cutting speed, depth of cut, and feedrate. Slight tool wear was included as a noise factor. Based on Taguchi Orthogonal Array L18, a series of experiments were designed and performed on AISI 1018 steel. Analysis of variance, ANOVA, was employed to identify the significant factors affecting the surface roughness and S/N ratio was used to find the optimal cutting combination of the parameters. It was concluded that tool with a high positive rake angle and smaller insert nose radius produced lower surface roughness value in an internal turning operation. It was also concluded that high feedrate and low cutting speed has produced the lowest surface roughness.
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