Abstract
As product lifecycle management is starting to be a standard information system in most companies, a data manipulation issue starts to emerge. Indeed, the information contained in a system often needs to be accessible or even transferred to another one to exploit a new software’s functionalities. With the Big Data era, new methods of analysis start to emerge, and the graph visualisation of data enables a better human understanding of the data itself. We propose to address the PLM migration issues with a new approach based on analysis of information system and data topology. The data is passed onto a graph and bundles are made thanks to clustering algorithms; this bundling enables a better understanding of the data and ease migration. However, PLM has links between links which complicate the transition to graphs. Finally, the described use-case proves that data bundling eases the data migration and prevents some usual pitfalls and delays.
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Barrios, P., Loison, F., Danjou, C., Eynard, B. (2020). PLM Migration in the Era of Big Data and IoT: Analysis of Information System and Data Topology. In: Nyffenegger, F., Ríos, J., Rivest, L., Bouras, A. (eds) Product Lifecycle Management Enabling Smart X. PLM 2020. IFIP Advances in Information and Communication Technology, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-030-62807-9_55
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DOI: https://doi.org/10.1007/978-3-030-62807-9_55
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