Optimization of Tool Wear Using Coupled RSM-GA Approach in Turning of Stainless Steel AISI 304 with Magnetic Damping of Tool Shank

Abstract

Tool wear, especially flank wear, is a major concern in the manufacturing industry. Increased tool wear is caused by chatter and leads to increased surface roughness, reduced productivity and higher operating costs. It is more pronounced in the machining of difficult to cut materials such as stainless steel, tool steel, Inconel and hardened Ti alloys. Additionally, unpredictable tool wear can lead to frequent shutdowns of the machining process making it difficult for full automation. Therefore, to increase productivity and to reduce costs associated with increased and unpredictable tool wear, numerous research studies have been carried out. In this research, two permanent ferrite bar magnets of 1500 Gauss strength were used to dampen the vibration of the tool shank in the turning of stainless steel AISI 304 using titanium nitride (TiN) coated carbide inserts. Mild steel fixtures were used to place the magnets beside and below the tool shank in the carraige of a Harrison M390 engine lathe. The tool overhang was kept constant at 120 mm. A small central composite design (CCD) approach in response surface methodology (RSM) was used to model the tool wear as a response of the three primary cutting parameters: cutting speed, feed, and depth of cut. Design Expert software (version 6) was used to generate the 14 experimental runs needed to develop and verify the empirical mathematical model of tool flank wear. The resultant tool flank wear was measured using both optical and scanning electron microscopes (SEM). Finally, an empirical quadratic mathematical model of tool wear was found. This model was then used as the objective function in the optimization of tool wear using genetic algorithms (GA). The optimization results predicted that the minimum tool wear was 0.0427 mm. This prediction was subsequently validated experimentally.