Abstract
Currently, collaborative SC planning driven by lean Industry 4.0 technologies is helping manufacturers to be more agile and efficient in their operations. This paper addresses the problem of information sharing among supply network partners in the footwear industry for the computational optimisation of SC planning. The methodology called C2NET is used for model input data through standardised tables (STables). The results show a simplified database relational diagram, which can be applied by different companies from this industrial sector, as well as researchers for their mathematical optimisation developments.
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Acknowledgements
The research that has led to the present results has received funding from: the European Union H2020 Programme, with grant agreement No. 958205 “Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)”; the MCIN/AEI/10.13039/501100011033 and by European Union Next GenerationEU/PRTR with grant agreement PDC2022–133957-I00); the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana, entitled "Industrial Production and Logistics Optimization in Industry 4.0" (i4OPT) (Ref. PROMETEO/2021/065); ‘Resilient, Sustainable and People-Oriented Supply Chain 5.0 Optimization Using Hybrid Intelligence’ (RESPECT) (Ref. CIGE/2021/159); a PhD grant from the Technical of Ambato University.
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Reyes, J., Mula, J., Díaz-Madroñero, M., Andres, B. (2024). Normalised Data Model for Cloud Collaborative Manufacturing: Applied to the Footwear Industry. 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_70
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