Authors: Lukas Kathrein 1 ; Arndt Lüder 2 ; Kristof Meixner 1 ; Dietmar Winkler 1 and Stefan Biffl 3

Affiliations: 1 Christian-Doppler-Laboratory for Security and Quality Improvement in the Produciton System Lifecycle, Technische Universität Wien, Favoritenstraße 9-11, Vienna and Austria ; 2 Institute of Factory Automation, Otto-von-Guericke University of Magdeburg, Magdeburg and Germany ; 3 Institute for Information Systems Engineering, Technische Universität Wien, Vienna and Austria

ISBN: 978-989-758-372-8

ISSN: 2184-4992

Keyword(s): Production Systems Engineering, Product-Process-Resource (PPR) Relationships, Engineering Process Analysis, Engineering Knowledge Representation.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Data Engineering ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Ontologies and the Semantic Web ; Society, e-Business and e-Government ; Software Engineering ; Web Information Systems and Technologies

Abstract: The Industry 4.0 vision of flexible manufacturing systems depends on the collaboration of domain experts coming from a variety of engineering disciplines and on the explicit representation of knowledge on relationships between products and production systems (PPR knowledge). However, in multi-disciplinary systems engineering organizations, process analysis and improvement has traditionally focused on one specific discipline rather than on the collaboration of several workgroups and their exchange of knowledge on product/ion, i.e., product and production processes. In this paper, we investigate requirements for the product/ion-aware analysis of engineering processes to improve the engineering process across workgroups. We introduce a product/ion-aware engineering processes analysis (PPR EPA) method, to identify gaps in PPR knowledge needed and provided. For representing PPR knowledge, we introduce a product/ion-aware data processing map (PPR DPM) by extending the BPMN 2.0 standard, add ing PPR knowledge classification. We evaluate the contribution in a case study at a large production systems engineering company. The domain experts found the PPR EPA method using the PPR DPM usable and useful to trace design decisions in the engineering process as foundation for advanced quality assurance analyses. (More)

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Paper citation in several formats:
Kathrein, L.; Lüder, A.; Meixner, K.; Winkler, D. and Biffl, S. (2019). Production-Aware Analysis of Multi-disciplinary Systems Engineering Processes.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-372-8, ISSN 2184-4992, pages 48-60. DOI: 10.5220/0007618000480060

author={Lukas Kathrein. and Arndt Lüder. and Kristof Meixner. and Dietmar Winkler. and Stefan Biffl.},
title={Production-Aware Analysis of Multi-disciplinary Systems Engineering Processes},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS,},


JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Production-Aware Analysis of Multi-disciplinary Systems Engineering Processes
SN - 978-989-758-372-8
AU - Kathrein, L.
AU - Lüder, A.
AU - Meixner, K.
AU - Winkler, D.
AU - Biffl, S.
PY - 2019
SP - 48
EP - 60
DO - 10.5220/0007618000480060

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