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A Scoping Review on the Applications of MCDM Techniques for Parametric Optimization of Machining Processes

A Scoping Review on the Applications of MCDM Techniques for Parametric Optimization of Machining... Determination of the optimal input parameters for any of the machining processes plays a pivotal role in achieving the most suitable response values while fulfilling the requirements of both the manufacturers and end users. Among the present-day research community, different multi-criteria decision making (MCDM) techniques have become quite popular as effective multi-objective optimization tools to identify the most appropriate parametric combinations of different machining processes based on real-time experimental data. In this paper, more than 120 research articles (searched through Sciencedirect, Scopus and Web of Science) are reviewed while exploring the applications of different MCDM techniques in solving parametric optimization problems of turning, drilling and milling processes. This review paper would act as a knowledge-base to the decision making practitioners and process engineers in deciding the most appropriate experimental design plan to be deployed (Taguchi’s L9, L18 or L27 orthogonal array); difficult-to-cut advanced engineering materials to be machined (composites, and aluminum and titanium and their alloys); input parameters for turning, drilling and milling processes (cutting speed, feed rate and depth of cut), and corresponding responses (material removal rate and surface roughness) to study their interaction effects, MCDM tools (grey relational analysis and TOPSIS), and subjective (analytic hierarchy process) and objective (entropy method) criteria weighting techniques to be employed; and possibility of integration with other mathematical tools to deal with uncertain decision making environment. The essence of all the reviewed articles is concisely presented in succinct tabular forms, which would make this paper an asset to the researchers and practitioners. Future directions are also provided to help them in optimization of manufacturing processes leading to attainment of more pragmatic solutions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Computational Methods in Engineering Springer Journals

A Scoping Review on the Applications of MCDM Techniques for Parametric Optimization of Machining Processes

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References (180)

Publisher
Springer Journals
Copyright
Copyright © The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2022
ISSN
1134-3060
eISSN
1886-1784
DOI
10.1007/s11831-022-09731-w
Publisher site
See Article on Publisher Site

Abstract

Determination of the optimal input parameters for any of the machining processes plays a pivotal role in achieving the most suitable response values while fulfilling the requirements of both the manufacturers and end users. Among the present-day research community, different multi-criteria decision making (MCDM) techniques have become quite popular as effective multi-objective optimization tools to identify the most appropriate parametric combinations of different machining processes based on real-time experimental data. In this paper, more than 120 research articles (searched through Sciencedirect, Scopus and Web of Science) are reviewed while exploring the applications of different MCDM techniques in solving parametric optimization problems of turning, drilling and milling processes. This review paper would act as a knowledge-base to the decision making practitioners and process engineers in deciding the most appropriate experimental design plan to be deployed (Taguchi’s L9, L18 or L27 orthogonal array); difficult-to-cut advanced engineering materials to be machined (composites, and aluminum and titanium and their alloys); input parameters for turning, drilling and milling processes (cutting speed, feed rate and depth of cut), and corresponding responses (material removal rate and surface roughness) to study their interaction effects, MCDM tools (grey relational analysis and TOPSIS), and subjective (analytic hierarchy process) and objective (entropy method) criteria weighting techniques to be employed; and possibility of integration with other mathematical tools to deal with uncertain decision making environment. The essence of all the reviewed articles is concisely presented in succinct tabular forms, which would make this paper an asset to the researchers and practitioners. Future directions are also provided to help them in optimization of manufacturing processes leading to attainment of more pragmatic solutions.

Journal

Archives of Computational Methods in EngineeringSpringer Journals

Published: Oct 1, 2022

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