Multi Objective Optimization in Turning Parameters of Al 6463 using Principal Component Analysis

Authors

  • Suneel Kumar Rathore Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India
  • Jyoti Vimal Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India

Keywords:

CNC turning, material removal rate (MRR), machining time (MT), principal component analysis (PCA), ANOVA

Abstract

Abstract

In multi objective optimization, weight criterion of each objective is important for producing better and accurate solutions. Now a day, due to the growing requirement of the higher precision apparatus for its useful aspect, machining time (MT) and material removal rate (MRR) of a machined part plays a significant role in the modern manufacturing process. This study focuses on optimizing CNC turning parameters on Al 6463 based on principal component analysis (PCA). The experiments have been conducted using full factorial design (FFD) in the design of experiments (DOE) on computer numerical controlled (CNC) turning, with the combination of four machining parameters which are: spindle speed (SS), feed rate (FR), depth of cut (DOC) and coolant. PCA has been employed on performance parameters for simultaneous minimization of MT and maximization of MRR. It is used to change multiple objectives to a single objective. Further, the analysis of variance (ANOVA), response table and confirmation test was used to analyze the impact of process parameters during machining, to find out the optimal setting of process parameters for turning process. Hence, this confirms that the proposed approach in this study can be a useful tool to improve the turning performance of Al 6463 in CNC turning process.

Author Biographies

  • Suneel Kumar Rathore, Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India
    Department of Mechanical Engineering
  • Jyoti Vimal, Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India
    Department of Mechanical Engineering

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Published

2019-04-09

Issue

Vol. 7 No. 2 (2017)

Section

Articles

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