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Russian Conference on Artificial Intelligence

RCAI 2020: Artificial Intelligence pp 403–415Cite as

The Concept of Support for Laser-Based Additive Manufacturing on the Basis of Artificial Intelligence Methods

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12412))

Abstract

A general concept of software and information support for laser-based additive manufacturing of metal parts from powder compositions is proposed. It is based on an ontological two-level approach to the formation of knowledge about the processes of laser additive manufacturing. For such an approach, the ontology is clearly separated from the knowledge base. So, domain specialists can create and maintain knowledge without intermediaries in terms and representation that they understand. The conceptual architecture of the decision support software for laser-based additive manufacturing processes is presented. Its information and software components are described. Information components are ontologies, databases of laser-based additive manufacturing system components, databases of materials for additive manufacturing, knowledge base and case database. The knowledge base contains formalized information on the settings of laser-based additive manufacturing modes that ensure compliance of the obtained metal parts with the requirements of the current industry-specific guidelines. The case database contains a structured description of the protocols for using laser technological equipment for additive manufacturing of metal parts from powder compositions. Software components are editors for creating and maintaining data and knowledge bases, decision support system based on both knowledge and cases and tool for cases structuring. There are also external tools for mathematical modelling of directed energy deposition physico-chemical processes. When making decisions, it is proposed to use a hybrid approach that combines knowledge engineering methods and case-based search by analogy. The feature of the approach is the continuous updating of the knowledge base due to its improvement by experts and due to its verification in the process of accumulating cases.

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Notes

  1. 1.

    This (and all the following) figure shows the interface of the IACPaaS cloud platform tool "Ontology Editor", which is used for creating ontologies in the platform's Fund [24].

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Acknowledgments

This work was partially supported by the Russian Foundation for Basic Research (project numbers 20-01-00449, 19-07-00244).

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Authors and Affiliations

  1. IACP FEB RAS, Vladivostok, Russian Federation

    Valeria Gribova, Yuriy Kulchin, Alexander Nikitin & Vadim Timchenko

Authors
  1. Valeria Gribova
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  2. Yuriy Kulchin
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  3. Alexander Nikitin
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  4. Vadim Timchenko
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Corresponding author

Correspondence to Vadim Timchenko .

Editor information

Editors and Affiliations

  1. National Research University Higher School, Moscow, Russia

    Sergei O. Kuznetsov

  2. Moscow Institute of Physics and Technology, Dolgoprudny, Russia

    Aleksandr I. Panov

  3. Federal Research Center Computer Science and Control, Moscow, Russia

    Konstantin S. Yakovlev

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Gribova, V., Kulchin, Y., Nikitin, A., Timchenko, V. (2020). The Concept of Support for Laser-Based Additive Manufacturing on the Basis of Artificial Intelligence Methods. In: Kuznetsov, S.O., Panov, A.I., Yakovlev, K.S. (eds) Artificial Intelligence. RCAI 2020. Lecture Notes in Computer Science(), vol 12412. Springer, Cham. https://doi.org/10.1007/978-3-030-59535-7_30

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  • DOI: https://doi.org/10.1007/978-3-030-59535-7_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59534-0

  • Online ISBN: 978-3-030-59535-7

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