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 I. Pruncu,Catalin I. Pruncu +8 more
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TLDR
In this article, a literature review is conducted to classify the articles on EWM applications in machining operations, which included 65 academic articles from different journals, books, and conferences since the year 2009.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.read more
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Journal ArticleDOI
Metal Machining—Recent Advances, Applications, and Challenges
TL;DR: The machining process remains alive and up-to-date in this context, always presenting itself as a manufacturing process with several variants and allowing for high dimensional accuracy and high levels of surface finish as discussed by the authors.
Journal ArticleDOI
Multi-Objective Task Scheduling of Circuit Repair
Sheng Liu,Xiaogang Qi,Lifang Liu +2 more
TL;DR: In this article , the authors proposed three rest strategies and considered the scheduling optimization of flexible rest for repair teams, for the first time, and built a more scientific and comprehensive mathematical model for the task scheduling of circuit repair, which aims to maximize benefits and minimize risks during scheduling up to a certain moment, taking into account constraints, such as geographic information, resources, etc.
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Multi-objective optimization of rotary EDM of aerospace nickel super alloy using Taguchi-entropy weight-based grey relational analysis
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Machining of shape-memory alloys using electrical discharge machining with an elaborate study of optimization approaches: a review
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Research on Stratum Identification Method Based on TBM Tunneling Characteristic Parameters
TL;DR: In this article , the authors used the entropy weight method to improve the stratum recognition rate in TBM tunneling, and the results showed that the K-nearest neighbor model has a better recognition effect for the interval with single stratum distribution, which provides an effective method to obtain stratum information by using tunneling characteristic parameters.
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