Machining of Ti-6Al-4V biomedical alloy by WEDM: investigation and optimization of MRR and R_z using grey-harmony search

Abstract

Purpose The purpose of this paper is to investigate the optimized setting of wire-cut electrical discharge machining (WEDM) parameters at which material removal rate (MRR) and mean roughness depth (Rz) set a compromise. The problem in the processing of Ti-6Al-4V by conventional processes is a high strength, high hardness, high tool wear. Due to which WEDM is adopted to machine Ti-6Al-4V biomedical alloy. Ti-6Al-4V alloy has a number of applications in the engineering and medical industries due to its high strength biocompatibility. Design/methodology/approach The effect of control factors (i.e. pulse on-time: Pon; pulse off-time: Poff; servo voltage: SV) on the MRR and Rz is investigated in the present research. The planning of experiments is done using a Taguchi-based L9 orthogonal array. The percentage influence of each factor on responses is also evaluated. The multi-objective optimization is done using the grey approach initially. After that, the results were also calculated using harmony search (HS). Therefore, a hybrid approach of grey and HS is used to find the optimized values of MRR and Rz. Findings The maximum value of grade calculated by grey-HS is 0.7879, while in the case of the experimental run the maximum value of grey grade is 0.7239. The optimized setting after improvisation at this grade value is Pon: 130 µs; Poff: 45 µs and SV: 70 V for MRR and Rz collectively. The validation of the suggested setting is completed by experimentation. The values of MRR and Rz are coming out to be 6.4 mm3/min and 13.84 µm, which represents improvised results after the implementation of the HS algorithm. Originality/value The integration of the grey approach with the HS principle in the manufacturing domain is yet to be explored. Therefore, in the present research hybrid approach of grey-HS is implemented in the manufacturing domain having applications in medical industries.

Effect of Wiper Edge Geometry on Machining Performance While Turning AISI 1045 Steel in Dry Conditions Using the VIKOR-ML Approach

“…It was evident from the responses that out of seven, six (R a , F r , F f , F c , R, Temp) were of the lower-the-better type, while one (MRR) was a larger-the-best type quality attribute. This made the present problem a Multi-Criteria Decision Making (MCDM) problem [40,41]. Thus, to solve this, the MCDM approach of VIKOR-ML was adopted.…”

“…The Ra value was measured perpendicular to the axis of cutting. The surface was cleaned with acetone before it was measured, and an average of three readings were selected in the present work for analysis purposes [39,40]. The process flow in the current research is represented in Figure 3.…”

A contrastive characterization of pure Mg and AZ91D alloy based on the testing of mechanical, corrosion, wear, and erosion properties

“…Oxide layers formed on worn surfaces at sliding speeds, which helped to reduce material weight loss [22,26]. The contact heat was evidently caused by the sliding speed under a constant load, as the majority of the friction energy produced during the sliding wear could be transformed into thermal energy [27]. Over time, the oxide films detach themselves from the deteriorated surface and transform into particulate matter.…”

Multi-Objective Optimization of AISI P20 Mold Steel Machining in Dry Conditions Using Machine Learning—TOPSIS Approach

“…Previous research has detailed the machining of different type of steels and parametric optimization [22][23][24][25][26][27][28]. However, it is evident from the literature that limited work has been published on the milling of P20 mold steel.…”