Manufacturing Technology Today

R. Ramanujam ¹, R. Raju ², N. Muthukrishnan ¹

Affiliations
1 Dept. of Mechanical Engg., Sri Venkateswara College of Engg., Pennalur, Sriperumbudur, IN
2 Dept. of Industrial Engineering, Anna University, Chennai, IN

Abstract

This paper presents a new approach for optimizing the machining parameters on turning Metal Matrix Composite (AI-SiC-MMC). Optimization of machining process parameters was done by an analysis called Weighted Principal Component Analysis (WPCA), which is a useful tool for optimizing multi-response problems. Based on Taguchi's L₂₇ orthogonal array, turning experiments were conducted for aluminium silicon carbide particulate reinforced metal matrix composite (A356/10/SiC_p) using polycrystalline diamond (PCD) fine grade insert. The machining process parameters such as cutting speed, feed rate and depth of cut are optimized by multi response considerations namely surface roughness and specific power. The optimum combination of process parameters was studied by extracting more than one principal component and integrating into multi-response performance index (MPI). Finally, the analysis of variance (ANOVA) was used to find out the most influential parameters for multi response criteria. As a result, optimization of the complicated multiple performance characteristics can be greatly simplified through this approach.

Keywords

MMC, Machining, Multi-Response Optimization, Weighted Principal Component Analysis.

Full Text

     

N. Muthukrishnan ¹, Varun Krishnakumar ², S. Kailash ³, K. Prahlada Rao ⁴, M. Murugan ⁵

Affiliations
1 Dept. of Mech. Engg., Sri Venkateswara College of Engineering, Sriperumbudur, IN
2 GTRE (DRDO), Bangalore, IN
3 XLRI, Jamshedpur, IN
4 JNTU College of Engineering, Anantapur, IN
5 BSA Crescent Engineering College, Chennai, IN

Abstract

Aluminium Silicon Carbide (Al.SiC) metal matrix composite (MMC) materials have a set of mechanical and physical properties that are ideally suited for applications in aerospace, automobile industries. Despite the superior set of mechanical and physical properties, the usage of MMC's in industry is still limited owing to difficulties in machining. To overcome this barrier, this paper performs a thorough study about the machinability of Al-SiC (MMC) with PCD insert tool to establish machining guidelines.The focus of the investigation is to determine the optimum machining conditions by adjusting the spindle speeds, depth of cut and feed, and observing the corresponding behaviour of cutting force, surface imperfections, power consumed, and MRR. The worn out tool is subjected to microscopic analysis to evaluate the wear on the tool.On completion of the experimental test, an artificial neural network (ANN) is used to validate the results obtained and also to predict the behaviour of the system under any condition within the operating range.

Full Text