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Extraction of Manufacturing Rules From Unstructured Text Using a Semantic Framework

[+] Author Affiliations
SungKu Kang, Lalit Patil

University of Illinois at Urbana-Champaign, Urbana, IL

Arvind Rangarajan, Abha Moitra, Tao Jia, Dean Robinson

GE Global Research, Niskayuna, NY

Debasish Dutta

Purdue University, West Lafayette, IN

Paper No. DETC2015-47556, pp. V01BT02A033; 9 pages
doi:10.1115/DETC2015-47556
From:
  • ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1B: 35th Computers and Information in Engineering Conference
  • Boston, Massachusetts, USA, August 2–5, 2015
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5705-2
  • Copyright © 2015 by ASME

abstract

Formal ontology and rule-based approaches founded on semantic technologies have been proposed as powerful mechanisms to enable early manufacturability feedback. A fundamental unresolved problem in this context is that all manufacturing knowledge is encoded in unstructured text and there are no reliable methods to automatically convert it to formal ontologies and rules. It is impractical for engineers to write accurate domain rules in a structured semantic languages such as Web Ontology Language (OWL) or Semantic Application Design Language (SADL). Previous efforts in manufacturing research that have targeted extraction of OWL ontologies from text have focused on basic concept names and hierarchies. This paper presents a semantics-based framework for acquiring more complex manufacturing knowledge, primarily rules, in a semantically-usable form from unstructured English text such as those written in manufacturing handbooks. The approach starts with existing domain knowledge in the form of OWL ontologies and applies natural language processing techniques to extract dependencies between different words in the text that contains the rule. Domain-specific triples capturing each rule are then extracted from each dependency graph. Finally, new computer-interpretable rules are composed from the triples. The feasibility of the framework has been evaluated by automatically and accurately generating rules for manufacturability from a manufacturing handbook. The paper also documents the cases that result in ambiguous results. Analysis of the results shows that the proposed framework can be extended to extract domain ontologies which forms part of the ongoing work that also focuses on addressing challenges to automate different steps and improve the reliability of the system.

Copyright © 2015 by ASME
Topics: Manufacturing

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