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With modular automation, modular industrial plants use a functional engineering approach, and modules enable plug &amp; produce plant engineering. However, plant configuration is still a largely manual process and often not optimized with respect to the available information. In this contribution, we propose a system and algorithm to support the automation engineer in the process of joining together modules into process pipelines and in their optimization. Our solution is built upon an abstract semantic data model that facilitates the automated matching of pre- and post-condition of modules and of the things that are processed by these modules. The pipeline generation engine is further extended by means of an optimization and ranking algorithm, and thus enables automated inter-module pipeline generation and plant optimization. We evaluate our system by means of a simple fictional use case scenario and prove feasibility, applicability as well as the huge potential for time and cost savings.

at - automatisierungstechnik

Semantic function module pipeline generation: Automating the generation and optimization of inter-module process pipelines for industrial plants using semantic annotations and pre- and post-condition matching