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Performance optimization of wire EDM of Nitinol shape memory alloy using BBD RSM and TLBO with alumina nano graphene and MWCNT Powder mixed dielectric
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  • Published: 18 February 2026

Performance optimization of wire EDM of Nitinol shape memory alloy using BBD RSM and TLBO with alumina nano graphene and MWCNT Powder mixed dielectric

  • Inam Ur Rehman1,
  • Rakesh Chaudhari1,
  • Jay Vora1,
  • Vivek Patel1,
  • Sakshum Khanna2,3 &
  • …
  • Subraya Krishna Bhat4 

Scientific Reports , Article number:  (2026) Cite this article

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  • Engineering
  • Materials science
  • Nanoscience and technology

Abstract

The present study investigated the performance optimization of Wire Electrical Discharge Machining (WEDM) of Nitinol Shape Memory Alloy (SMA) using a hybrid design approach combining Box-Behnken design and Teaching–Learning based optimization (TLBO). A comparative study of three nano-powders, namely, alumina, nano-graphene, and multi-walled carbon nanotubes (MWCNTs), was conducted to investigate their effect on material removal rate (MRR), surface roughness (SR), and surface morphology. The influence of key process parameters, discharge current (Ip), pulse-off time (Toff), and pulse-on time (Ton) has been systematically evaluated through experimental trials. Non-linear regression models were developed for both MRR and SR responses, and their statistical adequacy was validated using ANOVA and R² values, all exceeding 96%, confirming strong model accuracy. ANOVA further identified discharge current as the most significant factor, with the highest F-values for MRR and SR. Among all powders, MWCNTs consistently outperformed, achieving the highest MRR (3.6353 g/min) and lowest SR (2.12 μm) due to superior spark stability and thermal conductivity. The simultaneous optimization for MWCNT-based WEDM process has given the optimal parametric settings of Ip of 4 A, Toff of 20 µs, and Ton of 42 µs with the response values of MRR and SR as 2.8144 g/min and 3.06 μm, respectively. Additionally, a comparative experimental at optimized variables revealed that MWCNT-assisted WEDM yielded a 60.57% increase in MRR and a 75.81% reduction in SR over conventional WEDM. SEM analysis further shown that MWCNT-based machining produced the smoothest surfaces with minimal defects, while conventional EDM exhibited extensive pitting and re-solidified debris. This integrated experimental and optimization study provides a robust framework for improving the machinability and surface integrity of Nitinol SMA using advanced nano-powder-assisted WEDM.

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors humbly thank Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, and Pandit Deendayal Energy University, Gandhinagar, for the institutional support to carry out this work.

Funding

Open access funding provided by Manipal Academy of Higher Education, Manipal. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Mechanical Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, 382007, Gujarat, India

    Inam Ur Rehman, Rakesh Chaudhari, Jay Vora & Vivek Patel

  2. School of Technology, Pandit Deendayal Energy University, Gandhinagar, 382007, Gujarat, India

    Sakshum Khanna

  3. Relx Pvt Ltd, Gurugram, 122002, Haryana, India

    Sakshum Khanna

  4. Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

    Subraya Krishna Bhat

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Contributions

Inam Ur Rehman conducted the experimental study, Rakesh Chaudhari conceptualized the work, Jay Vora, Vivek Patel, and Sakshum Khanna performed the data analysis and created visualizations. Rakesh Chaudhari and Subraya Krishna Bhat supervised the work, interpreted the results, and revised the manuscript. All authors contributed to the manuscript preparation, and agree with its contents.

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Correspondence to Rakesh Chaudhari or Subraya Krishna Bhat.

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Rehman, I.U., Chaudhari, R., Vora, J. et al. Performance optimization of wire EDM of Nitinol shape memory alloy using BBD RSM and TLBO with alumina nano graphene and MWCNT Powder mixed dielectric. Sci Rep (2026). https://doi.org/10.1038/s41598-026-40446-1

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  • Received: 01 September 2025

  • Accepted: 12 February 2026

  • Published: 18 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-40446-1

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Keywords

  • Nitinol
  • Shape Memory Alloy
  • Wire Electrical Discharge Machining (WEDM)
  • Manufacturing Optimization
  • Alumina, Nano-graphene, MWCNT
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