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Related Experiment Video

Updated: Sep 13, 2025

Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation
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EDM-based analysis of Fe-based shape memory alloys using Cu-W electrodes with multiple output optimization and

Ranjit Singh1, Sambit Satpathy2, Dhirendra Kumar Shukla3

  • 1Department of Industrial and Production Engineering, NIT Jalandhar, Jalandhar, 144027, Panjab, India.

Scientific Reports
|August 2, 2025
PubMed
Summary
This summary is machine-generated.

Electrical Discharge Machining (EDM) optimizes the processing of Shape Memory Alloys (SMAs). This study identifies key parameters to improve machining efficiency and surface quality for Fe-based SMAs.

Keywords:
CCDDesirabilityEDMRSMSEMSMAWOTEWOW

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Area of Science:

  • Materials Science
  • Manufacturing Engineering

Background:

  • Shape Memory Alloys (SMAs) offer unique properties for aerospace, biomedical, and military applications.
  • Traditional machining of SMAs is challenging, leading to high costs and poor surface finish.

Purpose of the Study:

  • To investigate the effects of Electrical Discharge Machining (EDM) parameters on Fe-based SMAs.
  • To optimize EDM for improved machinability and surface integrity of SMAs.

Main Methods:

  • Response Surface Methodology (RSM) with Central Composite Design (CCD) was employed.
  • Key parameters: pulse on time (Ton), pulse off time (Toff), peak current (Ip), and gap voltage (GV).
  • Fe-based SMAs were machined using a Cu-tungsten electrode; wear rates and surface integrity were analyzed via SEM.

Main Results:

  • Workpiece Material Removal Rate (WOW) ranged from 11.30 to 65.17 mm³/min.
  • Tool Wear Rate (WOTE) varied from 0.0062 to 0.01127 g/min.
  • SEM revealed surface features like craters, micro-cracks, and recast layers, correlating with process parameters.

Conclusions:

  • Multi-objective optimization using desirability approach balanced machining efficiency and surface quality.
  • The study provides insights into EDM for Fe-based SMAs, enabling enhanced machinability and broader industrial use.