An Investigation of the Micro-Electrical Discharge Machining of Nickel-Titanium Shape Memory Alloy Using Grey Relations Coupled with Principal Component Analysis

• Published in: Metals (Basel ) 2017-11, Vol.7 (11), p.486
• Main Authors: Abidi, Mustufa, Al-Ahmari, Abdulrahman, Siddiquee, Arshad, Mian, Syed, Mohammed, Muneer, Rasheed, Mohammed
• Format: Article
• Language: English
• Subjects: Alloys; Capacitance; EDM electrodes; Elastic properties; Electric discharge machining; Electric potential; Electrode materials; Electrodes; Grey relational analysis; High aspect ratio; micro-EDM; micro-machining; Micromachining; multi-response optimization; Ni-Ti shape memory alloy; Nickel base alloys; Optimization; Principal components analysis; Process parameters; Shape effects; Shape memory alloys; Surface finish; Surface roughness; Taguchi methods; Titanium base alloys; Variance analysis
• ISSN: 2075-4701; 2075-4701
• DOI: 10.3390/met7110486

Shape memory alloys (SMAs) are advanced engineering materials which possess shape memory effects and super-elastic properties. Their high strength, high wear-resistance, pseudo plasticity, etc., makes the machining of Ni-Ti based SMAs difficult using traditional techniques. Among all non-conventional processes, micro-electric discharge machining (micro-EDM) is considered one of the leading processes for micro-machining, owing to its high aspect ratio and capability to machine hard-to-cut materials with good surface finish.The selection of the most appropriate input parameter combination to provide the optimum values for various responses is very important in micro-EDM. This article demonstrates the methodology for optimizing multiple quality characteristics (overcut, taper angle and surface roughness) to enhance the quality of micro-holes in Ni-Ti based alloy, using the Grey-Taguchi method. A Taguchi-based grey relational analysis coupled with principal component analysis (Grey-PCA) methodology was implemented to investigate the effect of three important micro-EDM process parameters, namely capacitance, voltage and electrode material.The analysis of the individual responses established the importance of multi-response optimization. The main effects plots for the micro-EDM parameters and Analysis of Variance (ANOVA) indicate that every parameter does not produce same effect on individual responses, and also that the percent contribution of each parameter to individual response is highly varied. As a result, multi-response optimization was implemented using Grey-PCA. Further, this study revealed that the electrode material had the strongest effect on the multi-response parameter, followed by the voltage and capacitance. The main effects plot for the Grey-PCA shows that the micro-EDM parameters “capacitance” at level-2 (i.e., 475 pF), “discharge voltage” at level-1 (i.e., 80 V) and the “electrode material” Cu provided the best multi-response.