scispace - formally typeset
Open AccessJournal ArticleDOI

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

Reads0
Chats0
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

Citations
More filters
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, +2 more
- 09 Dec 2022 - 
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.
Journal ArticleDOI

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.
References
More filters
Journal ArticleDOI

A mathematical theory of communication

TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Book

Decision analysis and behavioral research

TL;DR: In this article, the authors present an integrative presentation of the principles of decision analysis in a behavioral context, including sensitivity analysis, value-utility distinction, multistage inference, attitudes toward risk, and attempt to make intuitive sense out of what have been treated in the literature as endemic biases and other errors of human judgement.
Book

GIS and Multicriteria Decision Analysis

TL;DR: This book discusses Geographical Data, Information, and Decision Making, and Multicriteria Decision Analysis, as well as Spatial Decision Support Systems, which addresses the role of spatial data and information in decision making.
Book ChapterDOI

Methods for Multiple Attribute Decision Making

TL;DR: There are some classical decision rules such as dominance, maximin and maximum which are still fit for the MADM environment but they do not require the DM’s preference information, and accordingly yield the objective (vs. subjective) solution.
Journal ArticleDOI

Review on multi-criteria decision analysis aid in sustainable energy decision-making

TL;DR: In this article, the authors reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation.
Related Papers (5)