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A Hierarchical Product-Property Model to Support Product Classification and Manage Structural and Planning Data

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Enterprise Information Systems (ICEIS 2009)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 24))

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Abstract

Mass customization is one of the main challenges that managers face since it results in a proliferation of product data within the various organizational areas of an enterprise and across different enterprises. Effective solutions to this problem have resorted to generic bills of materials and to the grouping of product variants into product families, thus improving data management and sharing. However, issues like product family identification and formation, as well as data aggregation have not been dealt with by this type of approach. This contribution addresses these challenges and proposes a hierarchical data model based on the concepts of variant, variant set and family. It allows managing huge amounts of structural and non-structural information in a systematic way, with minimum replication. Besides, it proposes an unambiguous criterion, based on the properties of variants, for identifying families and variant sets. Finally, the approach can explicitly handle aggregated data which is intrinsic to generic concepts like families and variant sets. A case study is analyzed to illustrate the representation capabilities of this approach.

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References

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© 2009 Springer-Verlag Berlin Heidelberg

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Giménez, D.M., Henning, G.P., Leone, H.P. (2009). A Hierarchical Product-Property Model to Support Product Classification and Manage Structural and Planning Data. In: Filipe, J., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2009. Lecture Notes in Business Information Processing, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01347-8_53

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  • DOI: https://doi.org/10.1007/978-3-642-01347-8_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01346-1

  • Online ISBN: 978-3-642-01347-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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