Efficient Automation Engineering of Modular Process Equipment Assemblies Using the Digital Twin

Modular process plants are a promising approach to accelerate the engineering of greenfield process plants. This is achieved by the combination of pre-engineered process equipment assemblies (PEAs) with a standardized interface for the integration in process control systems, the module type package (MTP). This standardized interface can be integrated in the engineering process to further improve the potential. In this paper existing standards are used to generate aspects of the MTP. For this purpose, the engineering process of conventional plants is adapted for the engineering of PEAs. Therefore, similarities and potential of the described aspects have been analyzed regarding shared fundamental standards and characterized by their location in the asset life cycle. To describe the interconnections of the different standards, exemplary rules are proposed, which can be used for a transformation.     

Towards a Systematic Data Harmonization to Enable AI Application in the Process Industry

Current methods of artificial intelligence may often proof ineffective in the process industry, usually because of insufficient data availability. In this contribution, we investigate how data standards can contribute to fulfill the data availability requirements of machine learning methods. We give an overview of AI use cases relevant in the process industry, name related requirements and discuss known standards in the context of implicit vs. explicit data. We conclude with a roadmap sketching how to bring the results of this contribution into practical application.