An ontology-based framework for the management of machining information in a data mining perspective. Issue 11 (2018)

• Record Type: Journal Article
• Authors: Ostermeyer, Emeric; Danjou, Christophe; Durupt, Alexandre; Duigou, Julien Le
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 11(2018)
• Page Start: 302
• Page End: 307
• Publication Date: 2018
• Subjects: Manufacturing -- KBE -- OntoSTEP-NC -- CNC -- Ontology; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.08.300
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The advent and fast development of data mining techniques induced, in every field, interest for the data produced and stored. Machining process planning is no exception to this rule, and, with the important amount of related data that is stored in the enterprise information system, the application of data mining seems promising. However, the strong heterogeneity in data, and the distribution of information throughout several different documents, may hinder the application of data-mining methods and machine learning tools. This paper will introduce a knowledge-based engineering framework which can be used as an information system able to query consistent, correct and complete data from the heterogeneous corpus of documents used in process planning of machined parts.