Multi-Attribute Optimisation of PMEDM Process Parameters for Machining Ti6Al7Nb—a Biocompatible Alloy

Titanium alloys have significantly contributed to the manufacturing industries in recent years. They have found wide application in the automobile, aerospace, and biomedical industries. The mechanical and thermal properties—like a good strength-to-weight ratio, lower modulus of elasticity, greater resistance to fatigue and creep, excellent corrosion resistance, and good biocompatibility—give more advantages for their application in these fields. Application of titanium alloys in biomedical industries requires shaping the material on micro-scales involving high accuracy and precision. The high strength and rigidity possessed by titanium alloys make them extremely difficult to machine by conventional machining operations. Electrical Discharge Machining (EDM) has been globally established as a benchmark machining option to produce complex shapes in exotic materials for the manufacturing of dies, surgical instruments, and in biomedical applications. Researchers have focused on different EDM processes, varying electrode materials, and using different dielectrics to optimise process variables and obtain better material removal rate, tool wear rate, surface roughness, and surface characteristics. Often, multi-attribute decision-making techniques have been used to optimise the process parameters for EDM and its variants. Powder-mixed EDM is a development of the process of EDM where conductive powders are added to the dielectric to improve the machining capabilities and surface characteristics of EDM. The demand for biocompatible materials is increasing by the day due to the increased number of implant surgeries and failures of such implants in the long run. To enhance the performance of such materials, a suitable machining method is required, enhancing the dimensional accuracy and surface properties. In PMEDM, the additives form a coating on the machined surface, improving the surface quality. Considering all these factors, the present study was performed where the major aim is to machine a biocompatible material, Ti6Al7Nb, and optimise the process parameters like the powder concentration (C p ), peak current (I p ), on-time (T on ), duty cycle (DC), and gap voltage (V g ) to achieve better material removal rate (MRR), lower tool wear rate (TWR), electrode wear rate (EWR), and low surface roughness (SR). The powder-type selected is silicon carbide, having a grain size less than 53 µm. It is used as an additive suspended in the dielectric for conducting the tests. Technique for order of preference by similarity to ideal solution (TOPSIS) is used as the multi-attribute decision-making technique along with Taguchi&s;s design and optimisation to boost the performance of the process. An improvement of 0.2137 in the preference value is achieved through the confirmatory testing. The suggested set of parameters for improved results ishelp_outlineAQ: Note that bold emphases are not allowed per style. Please confirm if the bold text be changed to italics. C p1 I p3 T on3 DC 3 V g3 .