Abstract
Industry 4.0 is the fourth industrial revolution that refers to the digital transformation of supply chains, operations, factories and customers with the aim of being digitally interconnected. An important aspect of Industry 4.0 is to use all the information that can be extracted from a supply chain to try to optimise all aspects of its operation. This interconnection is coupled with advanced automation driven by technologies, such as robotics, cloud computing, artificial intelligence and big data, in which these technologies are converging to provide digital solutions. This article offers a preliminary literature review of optimisation and big data in supply chain 4.0. A classification of the reviewed literature is presented based on the following criteria: research methodology, modelling approach, software tool, digital technology and problem type. Finally, some future research guidelines are provided.
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Acknowledgments
This research received funding from the i4OPT project (Ref. PROMETEO/2021/065) granted by the Valencian Regional Government and from the CADS4.0-II project (Ref. PDC2022-133957-I00) funded by MCIN/AEI /10.13039/501100011033 and by European Union Next Generation EU/PRTR.
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Fateh, A., Mula, J., Diaz-Madroñero, M. (2024). An Overview on Optimisation and Big Data in Supply Chain 4.0. In: Bautista-Valhondo, J., Mateo-Doll, M., Lusa, A., Pastor-Moreno, R. (eds) Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023). CIO 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 206. Springer, Cham. https://doi.org/10.1007/978-3-031-57996-7_87
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