Linked Data Exploration in Product Life-Cycle Management

Abstract : Product Life Cycle Management (PLM) strategies have been proven as recommended approach for handling, planning and decision making regarding all aspects of products different life cycle stages. As this domain includes number of actors, system platforms and technologies, gathering information and handling knowledge often emerges as challenging problem. In this paper we propose a methodology to support a PLM approach taking advantage from the emerging semantic web technologies and the underlying paradigm of Linked Data. The main purpose of this methodology is twofold. First, it aims at providing a semantic model for handling different data sources and data types, structuring thus information from all stages of a product life cycle. Second, it extends reasoning mechanisms offered by semantic technologies, to conduct comparative and in-depth data analysis based on data mining and pattern discovery.
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Vittal Prabhu; Marco Taisch; Dimitris Kiritsis. 20th Advances in Production Management Systems (APMS), Sep 2013, State College, PA, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-415 (Part II), pp.460-467, 2013, Advances in Production Management Systems. Sustainable Production and Service Supply Chains. 〈10.1007/978-3-642-41263-9_57〉
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Soumis le : lundi 30 janvier 2017 - 16:45:32
Dernière modification le : vendredi 1 décembre 2017 - 01:15:33

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Soumaya Kadiri, Ana Milicic, Dimitris Kiritsis. Linked Data Exploration in Product Life-Cycle Management. Vittal Prabhu; Marco Taisch; Dimitris Kiritsis. 20th Advances in Production Management Systems (APMS), Sep 2013, State College, PA, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-415 (Part II), pp.460-467, 2013, Advances in Production Management Systems. Sustainable Production and Service Supply Chains. 〈10.1007/978-3-642-41263-9_57〉. 〈hal-01449755〉

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