343
Views
29
CrossRef citations to date
0
Altmetric
Articles

Surface integrity analysis of Nitinol-60 shape memory alloy in WEDM

&
Pages 1091-1102 | Received 13 Nov 2018, Accepted 29 May 2019, Published online: 17 Jun 2019
 

ABSTRACT

Nitinol-60, which belongs to the group of Nickel-Titanium based Shape Memory Alloys, offers remarkable properties like high wear resistance, high strength, shape memory, and super-elasticity; thereby making it convenient for use in aircraft and biomedical applications. However, these properties make Nitinol a ‘difficult-to-machine’ material during the traditional machining processes. Hence an experiment based study on Wire Electrical Discharge Machining of Nitinol-60 has been executed based on the parametric effects. This study attempts to provide the quantitative details of the machined surfaces in terms of maximum peak to valley height, the average peak to valley height, recast layer thickness, and surface crack density. In addition, Response Surface Methodological models of these surface parameters along with the cutting rate have been developed. Monte Carlo simulation of the generated regression equations is carried out to study the behavior of the models using randomly generated data. The results show that the developed models are in agreement with the experimental data; which further indicates that the optimal parameters are suitable for mass production.

Additional information

Funding

This project was supported by the Science and Engineering Research Board (SERB), Govt. of India [ECR/2017/000807];

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 561.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.