Knowledge-based selection of principle solutions for sensors and actuators based on standardized plant description and semantic concepts

Specifying and selecting actuation and instrumentation devices under the analysis of multiple requirements is a complex and labor-intensive step within the engineering of process plants. In industrial practice, this task is usually conducted following a product-oriented approach, i.e. devices are selected based on vendor-specific product catalogues and typically considering only known or previously used solutions. In many cases, selection decisions are taken in a one-to-one basis, i.e. one device at a time, and resulting selection data must be entered manually in planning and enterprise software tools. Such rudimentary practices often result in suboptimal design solutions and have a direct impact on the efficiency of the engineering workflow. In an effort to overcome such limitations, this contribution presents a concept based on plant description and semantic models (resp. AutomationML and eCl@ss) which allows for the knowledge-based selection of principle solutions, i.e., abstract design alternatives fulfilling required process functions (e.g. flow measurement). This concept does not only enable a function-oriented selection process capable of considering a wider solution space but also allows the seamless integration of this procedure into the plant engineering workflow.