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Digital Technologies Selection under Hesitant Fuzzy Information: The Case of the Automotive Sector

Maryam Gallab, Youssef Lamrani, Hafida Bouloiz, Mario Di Nardo, Mohamed Tkiouat, Sara Jebbor, Adil Elfakir

Year
2023
Citations
2
Access
Open access

Abstract

With advances in information technology, big data, mobile communications, and robotics, digital technologies are increasingly being used in factories around the world. This digital transformation is named industry 4.0. Today, industrial companies are looking at how to adopt this era and implement these technologies 4.0 while improving their performance and generating more profits. The objective of this paper is to help companies to better choose the appropriate digital technologies according to their activities using a multi-experts-multi-criteria decision-making approach under hesitant fuzzy information. The proposed model is a generic model based on Multi-Agent Systems allowing to have an idea of the parameters necessary to apply the adopted approach. The adopted approach allows a better representation of uncertainty and subjectivity of experts’ judgments. It would be of great interest, especially, when exact quantitative data are not available. A real case company example is exposed (automotive company) towards putting into practice the proposed approach.

Keywords

Automotive industryDigital transformationComputer scienceFuzzy logicRoboticsRepresentation (politics)Selection (genetic algorithm)Big dataIndustry 4.0Information technology

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