Journal of Primeasia
Integrative Disciplinary Research | Online ISSN 3064-9870 | Print ISSN 3069-4353
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Volume 4 Number 1 2023
RESEARCH ARTICLE (Open Access)
Industry 4.0 and Manufacturing Supply Chains: A Process-Oriented, Data-Driven Review
Md Sohel Masud 1*, Md. Fazle Alahi Bhuiyan 2
Journal of Primeasia 4 (1) 1-8 https://doi.org/10.25163/primeasia.4110842
Submitted: 29 May 2023 Revised: 07 August 2023 Accepted: 10 August 2023 Published: 14 August 2023
Abstract
Background: Manufacturing supply chains have long operated as loosely coordinated sequences of procurement, production, inventory, logistics, and distribution activities, often constrained by slow information flow and reactive decision-making. Industry 4.0 technologies, including the Internet of Things, artificial intelligence, big data analytics, cyber-physical systems, cloud computing, and digital twins, are reshaping this arrangement, though the manner and extent of that change is not always well specified in the literature.
Methods: This narrative review draws on peer-reviewed journal articles, conference papers, and academic reports published since 2018, retrieved from Scopus, Web of Science, IEEE Xplore, SpringerLink, and Google Scholar. A process-oriented analytical framework was used to map enabling technologies onto core supply chain functions, and findings were organized around four recurring performance dimensions: efficiency, flexibility, resilience, and sustainability.
Results: The reviewed evidence indicates that Industry 4.0 technologies meaningfully improve supply chain visibility, coordination, and forecasting accuracy. AI and machine learning strengthen demand planning, IoT and RFID enhance real-time tracking, and digital twins support scenario simulation and risk mitigation. These gains, however, are tempered by persistent barriers, including high implementation costs, cybersecurity exposure, interoperability challenges, and a shortage of adequately skilled workers, particularly among small and medium-sized enterprises.
Conclusion: Industry 4.0 is reorganizing manufacturing supply chains into more intelligent, adaptive systems, but realizing this potential appears to depend as much on organizational readiness, culture, training, and change management, as on the underlying technology itself. Future research would benefit from closer attention to scalable adoption pathways and sector-specific cybersecurity frameworks.
Keywords: Industry 4.0; Manufacturing Supply Chain; Data-Driven Decision-Making; Process-Oriented Framework; Smart Manufacturing
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