In the product development process, as it is currently practiced, production is still often neglected in the early design phases, leading to late and costly changes. Using the knowledge of product designers concerning production process design, this paper introduces an ontological framework that enables early feasibility analyses. In this way, the number of iterations between product and process design can almost certainly be reduced, which would accelerate the product development process. Additionally, the approach provides process engineers with possible production sequences that can be used for process planning. To provide feasibility feedback, the approach presented relies on semantic web technologies. An ontology was developed that supports designers to model the relations among products, processes, and resources in a way that allows the use of generic Sparql Protocol And RDF Query Language (SPARQL) queries. Future applicability of this approach is ensured by aligning it with the top-level ontology Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE). We also compare the ontology’s universals to fundamental classes of existing knowledge bases from the manufacturing and the batch processing domains. This comparison demonstrates the approach’s domain-independent applicability. Two proofs of concept are described, one in the manufacturing domain and one in the batch processing domain.
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December 2019
Research-Article
Applying Semantic Web Technologies to Provide Feasibility Feedback in Early Design Phases
Felix Ocker,
Felix Ocker
1
Institute of Automation and Information Systems,
TUM Department of Mechanical Engineering,
85748 Garching b. München,
e-mail: felix.ocker@tum.de
TUM Department of Mechanical Engineering,
Technical University of Munich
,85748 Garching b. München,
Germany
e-mail: felix.ocker@tum.de
1Corresponding author.
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Birgit Vogel-Heuser,
Birgit Vogel-Heuser
Professor
Institute of Automation and Information Systems,
TUM Department of Mechanical Engineering,
85748 Garching b. München,
e-mail: vogel-heuser@tum.de
Institute of Automation and Information Systems,
TUM Department of Mechanical Engineering,
Technical University of Munich
,85748 Garching b. München,
Germany
e-mail: vogel-heuser@tum.de
Search for other works by this author on:
Christiaan J. J. Paredis
Christiaan J. J. Paredis
Professor
Fellow ASME
BMW Chair in Systems Engineering,
Department of Automotive Engineering,
Greenville, SC 29607
e-mail: paredis@clemson.edu
Fellow ASME
BMW Chair in Systems Engineering,
Department of Automotive Engineering,
Clemson University
,Greenville, SC 29607
e-mail: paredis@clemson.edu
Search for other works by this author on:
Felix Ocker
Institute of Automation and Information Systems,
TUM Department of Mechanical Engineering,
85748 Garching b. München,
e-mail: felix.ocker@tum.de
TUM Department of Mechanical Engineering,
Technical University of Munich
,85748 Garching b. München,
Germany
e-mail: felix.ocker@tum.de
Birgit Vogel-Heuser
Professor
Institute of Automation and Information Systems,
TUM Department of Mechanical Engineering,
85748 Garching b. München,
e-mail: vogel-heuser@tum.de
Institute of Automation and Information Systems,
TUM Department of Mechanical Engineering,
Technical University of Munich
,85748 Garching b. München,
Germany
e-mail: vogel-heuser@tum.de
Christiaan J. J. Paredis
Professor
Fellow ASME
BMW Chair in Systems Engineering,
Department of Automotive Engineering,
Greenville, SC 29607
e-mail: paredis@clemson.edu
Fellow ASME
BMW Chair in Systems Engineering,
Department of Automotive Engineering,
Clemson University
,Greenville, SC 29607
e-mail: paredis@clemson.edu
1Corresponding author.
Manuscript received January 24, 2019; final manuscript received May 7, 2019; published online July 18, 2019. Assoc. Editor: Conrad Tucker.
J. Comput. Inf. Sci. Eng. Dec 2019, 19(4): 041016 (12 pages)
Published Online: July 18, 2019
Article history
Received:
January 24, 2019
Revision Received:
May 7, 2019
Accepted:
May 7, 2019
Citation
Ocker, F., Vogel-Heuser, B., and Paredis, C. J. J. (July 18, 2019). "Applying Semantic Web Technologies to Provide Feasibility Feedback in Early Design Phases." ASME. J. Comput. Inf. Sci. Eng. December 2019; 19(4): 041016. https://doi.org/10.1115/1.4043795
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