INVESTIGATION ON THE ELECTRICAL DISCHARGE MACHINING OF Cu-SHAPE MEMORY ALLOY: A STUDY ON MACHINABILITY AND SURFACE TOPOGRAPHY ASPECTS

Ranjit Singh, Ravi Pratap Singh and Rajeev Trehan
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Ranjit Singh: Department of Industrial & Production Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India
Ravi Pratap Singh: ��Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, Haryana-136119, India
Rajeev Trehan: Department of Industrial & Production Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

Surface Review and Letters (SRL), 2023, vol. 30, issue 03, 1-22

Abstract: Shape memory alloys (SMAs) are an excellent material for producing components for a wide range of industrial applications, such as orthopedic implacers, micro-equipment, actuators, fittings, and screening components, as well as military equipment, aerospace components, bio-medical equipment, and fabrication requirements. Despite its remarkable qualities, the production of SMAs is a problem for investigators all over the globe. The purpose of this research is to evaluate the effects of altering the Ton, Toff, Ip, and GV while processing copper-based SMA in an electrical discharge machining process on the material removal rate (MRR) and surface roughness (SR). The major runs were designed using a central composite design. SEM was also utilized to examine the micro-structure of EDM-processed electrode tools and work samples. SEM scans indicated the presence of debris, micro-cracks, craters, and a newly formed recast layer on the electrode tool and workpiece surface. High Ip and prolonged Ton provide huge spark energy simply at the work sample-tool contact, resulting in debris production. The experimental results reveal that the least and highest MRR values are 10.333 and 185.067mm3/min, respectively, while the minimum and maximum SR values are 3.07 and 7.15μm. The desirability technique, teacher learning based optimization (TLBO), and the Jaya algorithm were also utilized to optimize the studied solutions (i.e. MRR and SR) on a single and multi-objective basis. The best MRR and SR were determined using the desirability approach, the Jaya Algorithm, and the TLBO to be 152.788mm3/min and 4.764μm; 240.0256mm3/min and 1.637μm; and 240.0257mm3/min and 1.6367μm.

Keywords: EDM; MRR; RSM; CCD; SEM; TLBO; SMA; Cu-based SMA (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0218625X23500105

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