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Scrutinizing state-of-the-art I4.0 technologies toward sustainable products development under fuzzy environment

Abstract : To contribute to a growing global research interest that has evolved toward augmenting the economic, environmental, and societal values of Industry 4.0 in the manufacturing context, this study is intended to (1) survey the applicability of Industry 4.0 technologies in each of the triple bottom lines at the product level and (2) scrutinize the technologies based on product sustainability criteria using the application of the fuzzy Technique for Order of Preference by Similarity to Ideal Solution. Yet, there is a significant paucity of knowledge and uncertainty about the applicability of these technologies to developing sustainable products, hence providing an opportunity for innovative research. To be a sound assessment, this study investigates the perceptions of professional technologists, who play an important role as both internal and external stakeholders in addressing technological issues within organizations including multinationals. The findings obtained by the survey indicated the applicability level of six major technologies in contributing to product-level sustainability. The findings obtained by the fuzzy-based application revealed that 'Big Data Analytics' has the highest performance for developing sustainable products. Such an assessment, which is of critical importance to sustainable development, would be beneficial to policy-and decision-makers seeking to get a better understanding of the technologies and their applicability to sustainable products development.
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https://hal-emse.ccsd.cnrs.fr/emse-03837164
Contributor : Hamed Gholami Connect in order to contact the contributor
Submitted on : Thursday, November 3, 2022 - 9:17:58 AM
Last modification on : Saturday, November 19, 2022 - 3:30:07 AM

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Hamed Gholami, Ahmad Hashemi, Jocelyn Ke Yin Lee, Georges Abdul-Nour, Anas Salameh. Scrutinizing state-of-the-art I4.0 technologies toward sustainable products development under fuzzy environment. Journal of Cleaner Production, 2022, 377, pp.134327. ⟨10.1016/j.jclepro.2022.134327⟩. ⟨emse-03837164⟩

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