Here the End milling is studied for optimization of responses such as surface roughness and tool wear while machining HCHCr. These two conflicting responses decide the quality of process; therefore the multiobjective optimization technique is used. The Response Surface Optimizer (RSMO) and Multiobjective Genetic Algorithm (MOGA) were used as the multiobjective optimization techniques. The PVD coating of 2.5 micron AlCrN was used on four flute HSS End milling cutter. Input machining parameters were cutting speed, feed rate, depth of cut and percentage concentration of the solid lubricant MoS2 mixed with SAE-20 base oil. The experimentation was carried out using two level full factorial design concept while ANOVA technique has been used to verify the adequacy of mathematical model. It was found that the cutting speed (V) is having most dominant role on surface roughness and tool wear. The sensitivity analysis was carried out for studying sensitivity of input parameters for the responses.
- Manufacturing Engineering Division
Multiobjective Optimization of End Milling HCHCr Using AlCrN PVD Coated Cutters With MOGA and RSMO
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Biradar, SK, & Lathkar, GS. "Multiobjective Optimization of End Milling HCHCr Using AlCrN PVD Coated Cutters With MOGA and RSMO." Proceedings of the ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference. Volume 2: Processing. Detroit, Michigan, USA. June 9–13, 2014. V002T02A053. ASME. https://doi.org/10.1115/MSEC2014-4185
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