International Journal of Advanced Engineering and Technology

Authors
Morteza Sadegh Amalnik

Abstract
Intelligent knowledge based system (IKBS) is developed for optimizing dry CNC turning process using Taguchi method, CNC Machine, EN19 steel as the work piece material, and Cutting Insert. Tool wear and spindle loading which the machining parameters, spindle speed, feed rate, and depth of cut, are optimized through the intelligent knowledge based system (IKBS). The experimental CNC turning machine is used to evaluate IKBS. IKBS is developed to determine the effect of the machining parameters such as tool wear and spindle loading. The simultaneous optimization is done by IKBS. Four levels of each machining parameter are used in experimental verification on Model PTC 600, CNC lathe machine tool of PRAGA. The experimental verification is designed based on Taguchi’s method is used to evaluate the effect of the machining parameters on individual responses of IKBS. The simultaneous optimization is done by intelligent knowledge based system. The optimization of complicated multi-performance characteristics is simplified through this approach. Tool wear and spindle loading are two characteristics on the basis of which the machining parameters, spindle speed, feed rate, loading and depth of cut, are optimized through IKBS.