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

GALLAB, Maryam, LAMRANI, Youssef, BOULOIZ, Hafida, DI NARDO, Mario, TKIOUAT, Mohamed, JEBBOR, Sara and ELFAKIR, Adil (2023). Digital Technologies Selection under Hesitant Fuzzy Information: The Case of the Automotive Sector. [Pre-print] (Unpublished)

Preprints have not been peer-reviewed. They should not be relied on to guide clinical practice or health related behaviour and should not be regarded as conclusive or be reported in news media as established information.
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<jats:p>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. &amp;#x0D; 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. &amp;#x0D; 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.</jats:p>

Item Type: Pre-print
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SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 18 Aug 2023 14:49
Last Modified: 18 Aug 2023 14:49

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