Revealing the benefits of Entropy weights method for multi-objective optimization in machining operations: a critical review

Raman Kumar, Sehijpal Singh, Paramjit Singh Bilga, Jatin, Jasveer Singh, Sunpreet Singh, Maria-Luminiţa Scutaru, Catalin Iulian Pruncu

Research output: Contribution to journalArticlepeer-review

Abstract

Machining operation optimization improves the quality of the product, reduces cost, enhances overall efficiency by reducing human error, and enables consistent and efficient operation. It is a vital decision-making process and achieves the best solution within constraints. It reduces reliance on machine-tool technicians and handbooks to identify cutting parameters, as a lack of awareness of the optimal combination of machining parameters leads to several machining inefficiencies. Subsequently, the optimization of the machining process is more useful for units of production, particularly machining units. In multi-objective optimization (MOO) problems, weights of importance are assigned, mostly identical. But, nowadays, the weights assignment techniques have received a lot of consideration from the professionals and researchers in MOO problems. Various techniques are developed to assign weights of significance to responses in MOO. The Entropy weights method (EWM) continues to work pleasingly across diverse machining operations to allocate objective weights. In this paper, a literature review is conducted to classify the articles on EWM applications in machining operations. The categorization proposal for the EWM reviews included 65 academic articles from different journals, books, and conferences since the year 2009. The EWM applications were separated into 18 categories of conventional and non-conventional machining operations. The implementation procedure of EWM is presented with an example along with method development. Scholarly articles in the EWM applications are further inferred based on (1) implementation of EWM in different machining operations, (2) MOO methods used with entropy weights in machining operations, (3) application of entropy weights by citation index and publication year, and (4) entropy weights applications in other fields. The review paper provided constructive insight into the EWM applications and ended with suggestions for further research in machining and different areas.
Original languageEnglish
Pages (from-to)1471-1492
Number of pages22
JournalJournal of Materials Research and Technology
Volume10
Early online date3 Jan 2021
DOIs
Publication statusE-pub ahead of print - 3 Jan 2021

Keywords

  • Entropy weights method
  • multi-objective optimization
  • literature review
  • application areas
  • machining operations
  • MCDM
  • MADM

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