IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v14y2023i3d10.1007_s13198-023-01916-1.html
   My bibliography  Save this article

Optimization of wire electro discharge machining parameters using principal component analysis

Author

Listed:
  • C. Senthilkumar

    (University College of Engineering)

  • C. Nandakumar

    (MIT Campus, Anna University)

Abstract

Titanium and its alloys are commonly utilized in the aerospace and automobile sectors, because of its superior corrosion resistance, chemical inertness, strength properties. Machining of Titanium alloys using traditional method is extremely challenging task due to it has low thermal conductivity, poor electrical conductivity, quick strain hardening, high cutting tool temperatures, poor surface quality, and built-up edge formation. Hence, Nontraditional machining methods, like WEDM, can overcome these technical challenges and produce complicated part forms with good surface polish with high precision. Hence, the current study focuses on how process variables affect the responses like rate of removal (RR) and roughness (Ra). Because WEDM is an extremely complicated stochastic process, even an incidental variations in one of control factors can cause the responses to change, choosing an appropriate process parameter combination is vital. As a result, to cater the needs of today's industrial technology and customers, a thorough investigation into the choosing appropriate process parameters and solutions is required. So, multi-objective optimization based on principal component analysis (PCA) was used to optimize the process parameters.

Suggested Citation

  • C. Senthilkumar & C. Nandakumar, 2023. "Optimization of wire electro discharge machining parameters using principal component analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(3), pages 1040-1048, June.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:3:d:10.1007_s13198-023-01916-1
    DOI: 10.1007/s13198-023-01916-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-023-01916-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-023-01916-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ahmed A. A. Alduroobi & Alaa M. Ubaid & Maan Aabid Tawfiq & Rasha R. Elias, 2020. "Wire EDM process optimization for machining AISI 1045 steel by use of Taguchi method, artificial neural network and analysis of variances," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1314-1338, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Manikandan Natarajan & Thejasree Pasupuleti & Mahmood M. S. Abdullah & Faruq Mohammad & Jayant Giri & Rajkumar Chadge & Neeraj Sunheriya & Chetan Mahatme & Pallavi Giri & Ahmed A. Soleiman, 2023. "Assessment of Machining of Hastelloy Using WEDM by a Multi-Objective Approach," Sustainability, MDPI, vol. 15(13), pages 1-16, June.

    More about this item

    Keywords

    Removal rate; Ra; PCA;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:14:y:2023:i:3:d:10.1007_s13198-023-01916-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.