(Below is an excerpt from the September 20 edition of the CDL-Flex Industry Newsletter. Download the entire PDF newsletter here PDF.)
Software and systems engineering projects require the cooperation of several engineering disciplines, such as electrical, mechanical and software engineering. However, in engineering tool networks the distributed engineering of automated systems often relies on point-to-point data exchange, which a) does not sufficiently enable quality and consistency management, b) complicates round-trip engineering, and c) hampers the traceability of changes across engineering disciplines.
The need for round-trip engineering arises when the same information is present and relevant in multiple engineering domains and therefore inconsistencies may occur if not all related system elements are consistently updated to reflect a given change. Engineering views on the plant model are not automatically synchronized and changes between engineering operations in cross-discipline context not made visible to the engineers.
Figure 1 shows a simple engineering process and project role setting. While the plant planner is responsible for defining the overall topology of the automated system, the mechanical engineer, the electrical engineer, and the PLC programmer are in charge of creating and changing detailed engineering data linked to the plant topology.
However, another characteristic of tool networks in multi-disciplinary engineering environments is the vast amount of various data formats and heterogeneous data models. While the emerging AutomationML (AML) standard  supports structuring engineering data and modeling automation systems, project managers and system integrators may hesitate to migrate all data models of company specific services and tools to AML at once – preferring a step-wise migration of their settings to AutomationML to mitigate risks.
The AutomationML Hub (AML.hub) concept, as shown in Figure 2, systematically integrates tool networks regardless of the data model of participating engineering tools and enables the automation of engineering processes. While available software tools support individual engineering disciplines quite well, they only represent a discipline-specific view on the engineering plant. Therefore, the AML.hub deals in two aspects with engineering information. On the one hand, the AML.hub reflects at its core contributions of all involved disciplines on a so-called integrated plant model in a structured manner . That plant model captures and combines all different views into one AutomationML-based representation in order to provide an overarching, discipline-independent view on the engineering plant.
On the other hand, the AML.hub analyzes the data model of exchanged engineering data and transforms the data into a disciplinespecific AML representation in case of nonAML models. Once the transformation has been executed, the newly created AML representation is merged into the integrated plant model. This approach provides the following advantages:
- Engineering roles may define and maintain their discipline-specific topology tree of and their tool-specific view on the automated system.
- Engineering projects are AML-ready even if the tools do not export AML.
- The coexistence of engineering tools exporting and importing AutomationML models and of tools that do not yet facilitate AML is supported.
- A migration strategy from traditional engineering tool networks to AML-based tool networks may be defined.
The AML.hub approach facilitates the efficient versioning of exchanged AML models in tool networks and of operations performed on links between various topology trees and views to improve the traceability of changes across disciplines. Versioning also enables deriving the impact of changes on the integrated plant model and reporting differences to the engineer for improvement of their awareness.
The automation of engineering processes facilitates the synchronization of views on the integrated plant model and the execution of advanced processes such as test automation
for quality assurance.
In an industrial example, the AML.hub was evaluated by a hydro power plant builder using various non-AML models for exchanging information about signals across engineering disciplines in their tool network.
- Mordinyi, R.; Biffl, S., “Versioning in Cyber-physical Production System Engineering — Best-Practice and Research Agenda,” in Software Engineering for Smart Cyber-Physical Systems (SEsCPS), 2015 IEEE/ACM 1st International Workshop on , vol., no., pp.44-47, 17-17 May 2015
- Schmidt N., Lüder A., Biffl S., Steininger H. (2014): “Analyzing requirements on software tools according to functional engineering phase in the Technical Systems Engineering Process”, In: Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, pp.1-8.
- DIN EN 62714 (2015): “Datenaustauschformat für Planungsdaten industrieller Automatisierungssysteme – Automation Markup Language – Teil 1: Architektur und allgemeine Festlegungen”, DIN EN 62714-1:2015-06, IEC 62714- 1:2014, EN 62714-1:2014. (Richard Mordinyi)
(Dipl.-Ing. Mag. Dr. Richard Mordinyi – TU Wien, Christian Doppler Labor)