Utilizing pre-exicting knowledge from engineering artifacts in process industry plantsCopyright: © PLT
In the supply chain of manufacturing companies in the process industry, the actual production process of a plant is the main process step for adding value. In the lifecycle of a plant, phases which are taking place before production are: Product and process development, engineering, plant construction and commissioning. The duration of these phases usually has a major influence on the prospects of economic success. PCE projects run in parallel and include the following parts of the phases: Process development, engineering, plant construction and commissioning.
Accordingly, PCE projects offer opportunities for realizing efficiency gains. Looking at the process steps of PCE projects according to Namur Worksheet NA 35: Requirements, Concept, Basic Engineering, Detail Engineering, Construction & Commissioning, it is noticeable that in the first steps various requirements and framework conditions are defined and various engineering artifacts such as P&IDs, consumer lists, PCE location lists, FUBs, C&E matrices, simulation models, etc. are generated and compiled. Despite this broad knowledge base, in later steps the actual workflows and configurations in the DCS are implemented mostly by hand. Parts of these implementations concern the realization of process interlocks.
The knowledge required to generate these automatically to a large extent can also be acquired from the various engineering artifacts. However, a prerequisite for this is that the required information is semantically annotated and available in well-defined data formats in a machine-readable form.
In the context of my research, I am concerned with the provision of the information, with the knowledge generation from this information, and with the automatical generation of process interlocks. The aim is to create a manufacturer-independent typical library that covers all typical process interlocks and allows configurations such as sensor selection, measurement filtering, etc.