Multi objective optimization of high speed end milling of AISI D2 using meta heuristic approach - Seder, Amin M. F. (Kulliyyah of Engineering, International Islamic University Malaysia, 2016)
Cutting of hard steel materials is presently capturing the attention of researchers as a tolerable alternative for the traditional processes of heat treatment and grinding particularly in moulds and dies production. Hard machining has several advantages such as shorter cycle time, less machining procedure, fewer manufacturing cost, high flexibility as well as reduction of environmentally hazardous machining fluids. For illustration of its viability, it is very significant to make the hard milling machining operation to work with optimum parameters in accordance with predetermined objectives and fixed constraints. Thus, an attempt has been made in this research to optimize the high speed hard end milling of AISI D2 cold hardened steel. Accurate empirical regression models to predict the flank wear rate, surface roughness and normal cutting force F(x) are developed utilizing experimental data through employing a systematic methodology that is Central Composite Design (CCD) of Response Surface Methodology (RSM). Thus, one of the meta-heuristic evolutionary approaches called Multi Objective Genetic Algorithm (MOGA) is adopted. The main target of the study is to investigate the effect of cutting speed (Vc), feed rate (f) and depth of cut (DOC) on end milling of AISI D2 hardened steel (58-62 HRC) through utilizing uncoated carbide cutters on a Vertical Machining Center (VMC). Design-expert software (DOE) was used to specify the experimental machining conditions ranges. There are three outputs for the minimal flank wear rate, minimal surface roughness and minimal normal cutting force F(x) and there is a tradeoff between them. Firstly, the flank wear rate and surface roughness are with values of 0.00342 mm/min and 0.3439 μm respectively and the normal cutting force F(x) is 124.88 N. Secondly however, it is seen that the result of surface roughness is enhanced in comparison to the first output by decreasing to 0.2964 μm but the result of flank wear rate increasing to 0.0055 mm/min while the normal cutting force F(x) is 100.29 N. Thirdly, there is a decrement in the flank wear rate to the value of 0.0018 mm/min, however the value of surface roughness increased to the value of 0.3771 and normal cutting force F (x) equals 136.6355 N. Lastly, the final results of this dissertation can become a reliable database and information in the machinability area and cutting features in high speed hard end milling of AISA D2 steel. The proposed outcomes of this research are predicted for contributing generally in hard cutting operation involving process planning decisions or enhancement and particularly in the state-of-art industry of mould and dies manufacturing.