OPTIMISATION OF MACHINING PARAMETERS ON CUTTING FORCE DURING END MILLING OF AISI D2 TOOL STEEL USING GENETIC ALGORITHM
In the current scenario, there is a great demand of machining of hard material for today's dies and moulds manufacturing industries. D grade tool steels are widely used as work material due to its extremely high wear resisting properties as well as high corrosion resisting properties. Nowadays coated tools are widely used for machining of hard materials due to its high wear resistance properties. Cutting force is important factor to reduce tool wear rate during machining of hard material. This research work presents experimental investigation and optimization of machining parameters namely cutting speed, feed, depth of cut and width of cut on cutting force during milling of AISI D2 tool steel using AlCrN coated end mill tool. Design of experiment plan was developed to measure cutting force using response surface methodology (RSM) central composite design method. From experimental analysis, it has been found that cutting speed and width of cut are two dominant cutting parameters that affect the cutting force (Fz) Genetic algorithm was used to optimization of machining parameters to reduce cutting force during end milling. Lowest response reading was measured using GA and also validated it using experimentally.