Tool life and wear prediction of HSS and PVD material using ANFIS system

Abstract

This paper proposes tool wear prediction of the cutting material using High Speed Steel (HSS) and Physical Vapor Deposition (PVD) coating using Adaptive Network-based fuzzy inference system (ANFIS) system. Even though machines have been studied and practiced for a long time, but quality and accuracy are still needed to improve at the factory level. Machinating data and cutting parameters are derived from the cutting tool manufacturing for recommendation and initial decision making. However, practical machining depends on the practitioners and specific cases of machining. Tool wear is a critical aspect for improvement of productivity. Unlike in the previous time, machinists were made decision by totally experiences whereas the modern technology provide usefully mathematical simulation. The advanced method is combining people’s experiences and computer system by heuristic rule based which is known as ANFIS system. Input membership functions are defined and fed into the MATLAB toolbox. The rules are captured by shop floor experts and created in the fuzzy inference system. It is found from the simulation that HSS tool effects extremely on the high cutting speed whereas the PVD is risky to occur the wear at the cutting speed and feed rate. It can conclude that the PVD can be used by the medium to high cutting speed whereas the HSS performs good at the low to medium cutting speed. However, the tool life prediction is limited to direct prediction, but it can be calculated by the Taylor tool life equation.