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Multi-Response Optimization of WEDM Process Parameters for Machining of Superelastic Nitinol Shape-Memory Alloy Using
Rakesh Chaudhari1, Jay J Vora2, S S Mani Prabu3
1Department of Mechanical engineering, School of Technology, Pandit Deendayal Petroleum University, Raisan, Gandhinagar 382007, India. chaudharirakesh5@gmail.com.
Materials (Basel, Switzerland)
|April 21, 2019
Summary
This study optimizes wire electrical discharge machining (WEDM) for Nitinol, a shape-memory alloy (SMA). The developed method successfully machines the alloy while preserving its crucial shape-memory properties.
Area of Science:
- Materials Science
- Manufacturing Engineering
- Metallurgy
Background:
- Nitinol (nickel-titanium) is a shape-memory alloy (SMA) with increasing applications.
- Conventional machining of Nitinol presents significant challenges.
- Wire electrical discharge machining (WEDM) is explored as an alternative.
Purpose of the Study:
- To optimize WEDM process parameters for machining Nitinol (Ni55.8Ti).
- To ensure the preservation of the shape-memory effect after machining.
- To develop a systematic approach for industrial viability.
Main Methods:
- Utilized response surface methodology (RSM) and a heat-transfer search (HTS) algorithm for parameter optimization.
- Considered pulse-on time, pulse-off time, and current as input parameters.
- Evaluated material removal rate (MRR), surface roughness, and micro-hardness as output responses.
- Performed validation trials and differential scanning calorimetry (DSC) tests.
Main Results:
- Developed robust mathematical models for WEDM process parameters using RSM and ANOVA.
- Identified optimal WEDM parameters through a multi-objective HTS algorithm, generating Pareto optimal solutions.
- Achieved negligible error between predicted and measured values during validation.
- Confirmed the intact shape-memory effect in the machined Nitinol using DSC.
Conclusions:
- The combined RSM and HTS approach effectively predicts and optimizes WEDM parameters for Nitinol.
- The optimized WEDM process successfully machines Ni55.8Ti SMA while retaining its shape-memory characteristics.
- This methodology offers a viable solution for the industrial machining of shape-memory alloys.
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