AixCAPE® holds and offers expertise in different fields of application (see below).
There are various projects along these fields of expertise that have been finished successfully in the past or are still in the phase of soliciting interest or execution. The corresponding software prototypes are available to members of the AixCAPE® consortium for test and validation purposes in industrial environments. Some prototypes have been released as open source under the GNU General Public License (GPL). AixCAPE® also offers service and consulting in its areas of expertise for members and non-members.
The analysis of process data with advanced methods has large potential for the creation of predictive models and the improvement of process behavior. However, process data are typically not available in a form that is suitable for data analysis tools, and thus pre-processing steps are often indispensable.
A public Data Processing Compendium provided by AixCAPE® contains a plethora of workflows and best practices for pre-processing and knowledge exploitation in the process industries.
Data Exchange and Integration
Data Exchange in Process Industry (DEXPI)
As a typical result of engineering activities and plant operation, documents and data of various kinds are produced, such as design specifications, flowsheets, and records of measured data. This information is typically stored in tool-specific data formats. In consequence, data exchange between different tools on the large scale is still an open issue in today’s engineering workflows.
Process Development and Optimization
Separation processes are energy-intensive and, therefore, costly. Shortcut calculation methods allow for simulation and optimization of processes with less specification effort than traditional simulation, while still providing adequate accuracy. They allow for fast screening of more process alternatives to develop the most energy efficient/cost-optimal process.
Models are a valuable resource in today‘s processing industry. Large efforts are spent to build and maintain models in order to capture process knowledge. Having relevant information about models directly available helps to streamline modeling, simulation and optimization tasks.
Workflow and Knowledge Management
Efficient work processes for core activities such as process design and plant operation are pivotal for economic success.
Reliable data for physical properties are a prerequisite for the successful usage of models for process development and optimization.