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3D Research

, 9:46 | Cite as

Modeling and Optimization of Tool Wear and Surface Roughness in Turning of Al/SiCp Using Response Surface Methodology

  • Rashid Ali Laghari
  • Jianguang Li
  • Zhengyou Xie
  • Shu-qi Wang
3DR Express
Part of the following topical collections:
  1. Modeling

Abstract

Nowadays metal matrix composites are widely utilized in major industries such as aerospace and automotive because of their excellent properties in association with non-reinforced. This research work is attempted to analyze the consequence of cutting parameters on tool life and surface quality. The experimental work is consist of turning Al/SiCp (45%SiCp) weight with uncoated Carbide tools and the effect of three machining parameters including depth of cut, feed, and speed. Tool life and surface roughness have considered as process response for investigation. The predictive model has been developing to optimize the machining parameters in accordance to Box–Behnken design in Minitab 17, the contour plots the surface plot and response optimizer have made to study the influence of machining parameters and their interactions. ANOVA was carried out to identify the key factor affecting the tool life and surface roughness. The maximum tool life is 10.511 (min) and least surface roughness was observed 0.044 μm. The abrasion and adhesive have the principle wear mechanism observed in machining process. Response surface methodology (RSM) approach have used to optimize the machining parameters, and the RSM model found more than 95% confidence level.

Keywords

Al/SiCp metal matrix composite Tool life Surface roughness ANOVA Response surface methodology Modeling and optimization 

List of symbols

MMC

Metal matrix composite

RSM

Response surface methodology

ANOVA

Analysis Of Variance

d

Depth of cut (mm)

f

Feed rate (mm/r)

Vc

Cutting speed, m/min

Tl

Tool life (min)

wt

Weight

SiCp

Silicon carbide particles

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Copyright information

© 3D Research Center, Kwangwoon University and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Rashid Ali Laghari
    • 1
  • Jianguang Li
    • 1
  • Zhengyou Xie
    • 1
  • Shu-qi Wang
    • 1
  1. 1.School of Mechatronics EngineeringHarbin Institute of TechnologyHarbinChina

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