Taguchi-fuzzy multi output optimization (MOO) in high speed CNC turning of AISI P-20 tool steel

  • Authors:

  • Anil Gupta;Hari Singh;Aman Aggarwal

  • Affiliations:

  • Mechanical and Automation Engineering Department, Maharaja Agrasen Institute of Technology, Rohini, Delhi 110086, India;Department of Mechanical Engineering, National Institute of Technology, Kurukshetra 136119, India;Mechanical and Automation Engineering Department, Maharaja Agrasen Institute of Technology, Rohini, Delhi 110086, India

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

This paper presents the application of Taguchi method with logical fuzzy reasoning for multiple output optimization of high speed CNC turning of AISI P-20 tool steel using TiN coated tungsten carbide coatings. The machining parameters (cutting speed, feed rate, depth of cut, nose radius and cutting environment) are optimized with considerations of the multiple performance measures (surface roughness, tool life, cutting force and power consumption). Taguchi's concepts of orthogonal arrays, signal to noise (S/N) ratio, ANOVA have been fuzzified to optimize the high speed CNC turning process parameters through a single comprehensive output measure (COM). The result analysis shows that cutting speed of 160m/min, nose radius of 0.8mm, feed of 0.1mm/rev, depth of cut of 0.2mm and the cryogenic environment are the most favorable cutting parameters for high speed CNC turning of AISI P-20 tool steel.