Industry 4.0 project prioritization by using q-spherical fuzzy rough analytic hierarchy process

Author:

Azim Ahmad Bin1,ALoqaily Ahmad23,Ali Asad1,Ali Sumbal1,Mlaiki Nabil2

Affiliation:

1. Department of Mathematics & Statistics, Hazara University, Mansehra, 21120 Pakistan

2. Department of Mathematics and Sciences, Prince Sultan University. Riyadh, 11586 Saudi Arabia

3. School of Computer, Data, and Mathematical Sciences, Western Sydney University, Australia-Sydney-2150

Abstract

<abstract> <p>The Fourth Industrial Revolution, also known as Industry 4.0, is attracting a significant amount of attention because it has the potential to revolutionize a variety of industries by developing a production system that is fully automated and digitally integrated. The implementation of this transformation, however, calls for a significant investment of resources and may present difficulties in the process of adapting existing technology to new endeavors. Researchers have proposed integrating the Analytic Hierarchy Process (AHP) with extensions of fuzzy rough sets, such as the three-dimensional q-spherical fuzzy rough set (q-SFRS), which is effective in handling uncertainty and quantifying expert judgments, to prioritize projects related to Industry 4.0. This would allow the projects to be ranked in order of importance. In this article, a novel framework is presented that combines AHP with q-SFRS. To calculate aggregated values, the new framework uses a new formula called the q-spherical fuzzy rough arithmetic mean, when applied to a problem involving the selection of a project with five criteria for evaluation and four possible alternatives, the suggested framework produces results that are robust and competitive in comparison to those produced by other multi-criteria decision-making approaches.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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