[Zurück]

S. Biffl, A. Lüder, F. Rinker, L. Waltersdorfer, D. Winkler:
"Engineering Data Logistics for Agile Automation Systems Engineering";
in: "Security and Quality in Cyber-Physical Systems Engineering", Springer International Publishing, Switzerland, 2019, ISBN: 978-3-030-25311-0.

In the parallel engineering of large and long-running automation systems, such as Production Systems Engineering (PSE) projects, engineering teams
with different backgrounds work in a so-called Round-Trip Engineering (RTE) process to iteratively enrich and refine their engineering artifacts and need to exchange
data efficiently to prevent the divergence of local engineering models. Unfortunately, the heterogeneity of local engineering artifacts and data, coming from several engineering disciplines, makes it hard to integrate the discipline-specific views
on the data for efficient synchronization.
In this chapter, we introduce the approach of Engineering Data Logistics (EDaL)
to support RTE requirements and enable the efficient integration and systematic
exchange of engineering data in a PSE project. We propose the concept of EDaL
that analyzes efficient Engineering Data Exchange (EDEx) flows from data providers to a consumer derived from data exchange use cases. Requirements for EDEx
flows are presented, e.g. the definition and semantic mapping of engineering data
elements for exchange. We discuss main requirements for and design elements of
an EDaL information system for automating EDaL process capabilities. We evaluate the benefit and cost of the EDEx process and concepts in a feasibility case study
with requirements and data from real-world use cases at a large PSE company in
comparison to a traditional manual point-to-point engineering data exchange. Results from the feasibility study indicate that the EDEx process flows may be more
effective than the traditional point-to-point engineering artifact exchange and a
good foundation to EDaL as foundation for more agile engineering.

multidisciplinary engineering, production systems engineering, cyberphysical production systems, engineering process, process design, data exchange, data integration.

http://dx.doi.org/10.1007/978-3-030-35312-7_8