Model-based engineering for the integration of manufacturing systems with advanced analytics

David Lechevalier, Anantha Narayanan, Sudarsan Rachuri, Sebti Foufou, Y. Tina Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This paper presents the domain-specific knowledge that the approach should employ, the formal workflow of the approach, and a milling process use case to illustrate the proposed approach. We also discuss potential extensions of the approach.

Original languageEnglish (US)
Title of host publicationProduct Lifecycle Management for Digital Transformation of Industries - 13th IFIP WG 5.1 International Conference, PLM 2016, Revised Selected Papers
EditorsBenoit Eynard, Abdelaziz Bouras, Alain Bernard, Louis Rivest, Ramy Harik
PublisherSpringer New York LLC
Pages146-157
Number of pages12
ISBN (Print)9783319546599
DOIs
StatePublished - 2016
Event13th IFIP WG 5.1 International Conference on Product Lifecycle Management for Digital Transformation of Industries, PLM 2016 - Columbia, United States
Duration: Jul 11 2016Jul 13 2016

Publication series

NameIFIP Advances in Information and Communication Technology
Volume492
ISSN (Print)1868-4238

Other

Other13th IFIP WG 5.1 International Conference on Product Lifecycle Management for Digital Transformation of Industries, PLM 2016
CountryUnited States
CityColumbia
Period7/11/167/13/16

Keywords

  • Data analytics
  • Manufacturing process
  • Meta-model
  • Neural network
  • Predictive modeling

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management

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  • Cite this

    Lechevalier, D., Narayanan, A., Rachuri, S., Foufou, S., & Lee, Y. T. (2016). Model-based engineering for the integration of manufacturing systems with advanced analytics. In B. Eynard, A. Bouras, A. Bernard, L. Rivest, & R. Harik (Eds.), Product Lifecycle Management for Digital Transformation of Industries - 13th IFIP WG 5.1 International Conference, PLM 2016, Revised Selected Papers (pp. 146-157). (IFIP Advances in Information and Communication Technology; Vol. 492). Springer New York LLC. https://doi.org/10.1007/978-3-319-54660-5_14