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S. Biffl, D. Winkler, R. Mordinyi, S. Scheiber, G. Holl:
"Efficient Monitoring of Constraints in a Multi-Disciplinary Engineering Project with Semantic Data Integration in the Multi-Model Dashboard Process";
Vortrag: 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Barcelona, Spain; 16.09.2014 - 19.09.2014; in: "Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)", IEEE, (2014), ISBN: 978-1-4799-4845-1; S. 1 - 10.

In a multi-disciplinary engineering project, such as
the parallel engineering of industrial production plants, domain
experts want to efficiently monitor project-level constraints that
depend on technical parameter values in local engineering models.
However, the heterogeneous representations of constraint
parameters in these engineering models make the automation of
constraint monitoring difficult. In this paper, we introduce the
Multi-Model Dashboard (MMD) process providing semantically
integrated values of parameters and of constraints to domain
experts, as parameter values in various local models change during
the project. The tool-supported MMD process guides the
definition and monitoring of MMD parameters and constraints.
We evaluate the effectiveness and efficiency of the MMD process
in a feasibility study with requirements and data from real-world
use cases at industry partners. Major results are that the MMD
process was effective and efficient in eliciting relevant project
constraints and model dependencies and in providing data for
change impact analysis.

Software Engineering Methods in Automation, Semantic Data Integration, Change Impact Analysis, Engineering Process Observation