MUTIL-OBJECTIVE OPTIMIZATION – A TOPSIS APPROACH FOR OF EDM MACHINING OF BIOMATERIALS
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 3, Pages 4951-4960
AbstractThe increasing requirement for less wear and corrosive materials in biomedical, medical equipments application drives the development of new advanced smart metal matrix composites (SMMC). It is important to enhance the performances, life cycle and reliability of the biomedical and medical devices. A new, shape memory alloy is used as the reinforcement for making smart composite materials, to augment the properties such as ductility and toughness without compromisingthe corrosion resistance. The aluminium and NiTi is used to fabricate NiTi reinforced aluminum smart composites via powder metallurgy (PM) process. To understand the fundamental effect of NiTi on aluminum, the composites are fabricated for varying compositions. To disclose the efficacy of the fabrication process, the composites tested for physical and mechanical properties. The following basic terms density, porosity, hardness, and compression strength is studied and discussed. The augmentation of NiTi gains the compressive strength of the smart composites to certain extent which is significantly higher than pure aluminum. The density of the composites is slightly increased compared to pure aluminum; porosity is less than 5% irrespective of the reinforcement level. The problem persists with smart composite material is, it is very difficult to make into final shape by traditional machining process. In this work smart composites are machined to understand the machinability characteristics and investigates the influence of various Electric Discharge Machine (EDM) process parameters on machining quality such as Surface Roughness (Ra) and material removal rate (MRR). TOPSIS method is used to model the process and output of the same is presented.
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