TY - JOUR
T1 - Herausforderungen in der interdisziplinären Entwicklung von Cyber-Physischen Produktionssystemen
AU - Vogel-Heuser, Birgit
AU - Fantuzzi, Cesare
AU - Wimmer, Manuel
AU - Böhm, Markus
AU - Fay, Alexander
N1 - Publisher Copyright:
© 2019 Walter de Gruyter GmbH, Berlin/Boston 2019.
PY - 2019/6/1
Y1 - 2019/6/1
N2 - Model-based systems engineering has gained increasing application in the industrial development of a large number of technical systems. The use of various models is decisive for interdisciplinary innovations. However, it also comprises many challenges. The first challenge is the heterogeneous model landscape, which is characterized in particular by overlapping, partially redundantly modelled information. Second, the development, production and service processes are constantly subject to internal and external development cycles. To overcome these challenges, various methods and techniques can be used. In this paper, different approaches are investigated regarding their advantages and limitations: inconsistency management of coupled models in engineering, cross-disciplinary management of the engineering workflow, and the importance of smart data approaches.
AB - Model-based systems engineering has gained increasing application in the industrial development of a large number of technical systems. The use of various models is decisive for interdisciplinary innovations. However, it also comprises many challenges. The first challenge is the heterogeneous model landscape, which is characterized in particular by overlapping, partially redundantly modelled information. Second, the development, production and service processes are constantly subject to internal and external development cycles. To overcome these challenges, various methods and techniques can be used. In this paper, different approaches are investigated regarding their advantages and limitations: inconsistency management of coupled models in engineering, cross-disciplinary management of the engineering workflow, and the importance of smart data approaches.
KW - inconsistency management
KW - model coupling
KW - model-spanning optimization
UR - http://www.scopus.com/inward/record.url?scp=85067392625&partnerID=8YFLogxK
U2 - 10.1515/auto-2018-0144
DO - 10.1515/auto-2018-0144
M3 - Artikel
AN - SCOPUS:85067392625
SN - 0178-2312
VL - 67
SP - 445
EP - 454
JO - At-Automatisierungstechnik
JF - At-Automatisierungstechnik
IS - 6
ER -