Rainer Drath (Pforzheim University) · Hamied Nabizada (Helmut Schmidt University Hamburg)
Presented at
2026 IEEE 31st International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 8 to 11 September 2026
Type
Conference paper, IEEE ETFA 2026, 4 pages
Full text
Read on IEEE Xplore (doi:10.1109/ETFA68377.2026.11724778)
Summary
The CAEX mirror concept lets one engineering object, such as a pump or a sensor, appear in several places of a hierarchy without duplicating its data. Mirrors must, however, have identical content: they cannot carry attributes, structure or metadata that only apply in one context. The paper analyses industrial use cases where this limits modeling and introduces a generalized reference concept for AutomationML.
The concept allows distributed, layered and context-dependent representations of one engineering object while keeping a single source of truth, and supports model protection, distributed ownership and modeling separate aspects of an object without duplicated data. A reference library is available and is proposed as a candidate for future AutomationML standardization.
Keywords: mirror concept, CAEX, AutomationML, aspect
Summary written by AutomationML e.V.; the authors‘ abstract is available on IEEE Xplore. Listed as part of AutomationML at Academic Conferences 2026.
How to Cite
Rainer Drath, Hamied Nabizada: When One Reference Is Not Enough: Multi-Context Modeling in AutomationML. In: 2026 IEEE 31st International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden, 2026, pp. 1-4. doi: 10.1109/ETFA68377.2026.11724778
BibTeX
@inproceedings{Drath2026When,
author = {Rainer Drath and Hamied Nabizada},
title = {When One Reference Is Not Enough: Multi-Context Modeling in AutomationML},
booktitle = {2026 IEEE 31st International Conference on Emerging Technologies and Factory Automation (ETFA)},
address = {Västerås, Sweden},
publisher = {IEEE},
year = {2026},
pages = {1--4},
doi = {10.1109/ETFA68377.2026.11724778}
}