In process systems engineering models are used for many applications, e.g., process simulation, optimization or control. Various types of models such as shortcut or rigorous models exist. An exchange and reuse thereof is highly desirable, but seldom performed. This article focuses on current approaches for developing and solving process models in specific instances for different applications. A close look will be made at the state of the art in modeling, simulation, and optimization software. Requirements for future software developments are derived to reduce the development and synthesis costs for new chemical engineering processes. The web‐based modeling, simulation, and optimization environment MOSAIC is taken as an example to highlight current developments towards collaborative computer‐aided engineering work.
In this paper, the problem of the data and model management in the lifecycle of a process plant is addressed by presenting the database structure of the modeling and optimization platform MOSAIC. The first step of data integration is done by combining models and plant data into one central database. This has advantages for both plant design and plant optimization. Basic engineering workflows can then be improved. Several database configurations are presented to meet the different requirements with respect to security and open access.
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.
Dedicated software exists for both process simulation and optimization. Given the advantages of simultaneous optimization schemes, engineers are frequently tasked with reimplementing their simulation models in optimization languages or environments. In this contribution, a workflow is introduced to model chemical engineering models in MathML and to have an automatic code generation for both specialized simulation and optimization tools. Two examples are given to highlight the performance of this workflow implemented in the modeling, simulation, and optimization environment MOSAIC.
The ideas and requirements for digitization in the process industry are manifold – the interoperability of the tools in use by engineers is an important prerequisite. The strong heterogeneity of existing data formats and standards as well as the variety of proprietary and company‐specific solutions confronts the process industry with huge challenges. This paper deals with the data exchange between process simulation, 2D CAD, and 3D CAD tools, provides an overview of existing standards and formats as well as initial experiences gained in a case study.
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