| Title: | Sustainable manufacturing in industry 4.0 by artificial intelligent and internet of things, a review |
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| Authors: | ID Soori, Mohsen (Author)
ID Arezoo, Behrooz (Author) |
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| Files: |  Soori_Sustainable_2025.pdf (850,54 KB)
MD5: C879EDF8D8103967EF03D9BDACB6D892
 https://reference-global.com/article/10.2478/jlst-2025-0007
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FL - Faculty of Logistic
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| Abstract: | Artificial Intelligent (hereafter: AI), Internet of Things (hereafter: IoT) and data analytics are used to provide real-time resource utilization monitoring and optimization within Industry 4.0 era. As a result, waste is decreased and resource efficiency is improved which can minimize environmental impact and supports sustainability goals. By growing concerns of environmental issues, sustainability was converted to fundamental prerequisite of contemporary industrial systems. In order to present advanced models and methodologies of AI and IoT applications in sustainability enhancement of part manufacturing within Industry 4.0, the review of recent developments is presented in the study. It analyzes the applications of AI, IoT and data analytics in terms of resource optimization and decision-making regarding sustainability concerns of part manufacturing procedures. This study investigates how Industry 4.0 can be applied for sustainable manufacturing by improving resource efficiency, integrating renewable energy, allowing circular economy practices and promoting supply chain transparency. The study synthesizes data from recent research works in order to explain the contributions of smart manufacturing, predictive maintenance, virtual machining and blockchain supported supply chain management in terms of waste, energy usage and environmental impact minimization of advanced manufacturing. The article also discusses AI and IoT technology applications in terms of enhancing traceability, visibility, and efficiency within supply chain management processes. Applications of decentralized manufacturing, human-centric design, and collaborative industrial ecosystems are also presented and discussed. Also, key challenges including rising e-waste, data privacy threats, talent shortages and the demand of supporting legislative frameworks and resilient digital infrastructures are discussed in the study. Moreover, to provide the potential future research directions from AI and IoT applications in achieving sustainability within industry 4.0 paradigm, novel ideas are presented and discussed. As a result, the study provides practical insights and recommendations which enable researchers, industry stakeholders and lawmakers to analyze and develop sustainability strategies inside industrial contexts within Industry 4.0 era. |
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| Keywords: | industry 4.0, sustainable manufacturing, artificial intelligent, internet of things |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 29.04.2025 |
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| Publication date: | 26.01.2026 |
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| Publisher: | Fakulteta za logistiko Univerze v Mariboru, De Gruyter Poland |
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| Year of publishing: | 2025 |
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| Number of pages: | Str. 19-40 |
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| Numbering: | Letn. 16, št. 2 |
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| PID: | 20.500.12556/DKUM-97045  |
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| UDC: | 004.8 |
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| ISSN on article: | 2784-7497 |
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| COBISS.SI-ID: | 267317763 |
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| DOI: | 10.2478/jlst-2025-0007 |
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| Publication date in DKUM: | 13.02.2026 |
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| Views: | 160 |
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| Downloads: | 5 |
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| Metadata: |    |
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| Categories: | Misc.
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