REUNION – Vernetzter Demonstrator-Verbund für optimierte Prozessketten
BMWE Förderkennzeichen 03EN2100A

Modular process engineering lays the foundation for energy-optimised production plants. Thanks to flexibly combinable modules, plants can be constructed and operated to meet specific needs, designed to be more energy-efficient, and optimised more precisely during operation.

Modular Production

Process engineering is on the eve of profound change. Smaller batch sizes, increasing product diversity and the need for rapidly adaptable production facilities call for new approaches to the planning, operation and further development of industrial plants. One promising approach is the modularisation of production systems: individual process steps are implemented using specialised Process Equipment Assemblies (PEA), which can be interconnected to form complete processes. This interconnection takes place not only physically via defined interfaces, but also at the control level (Process Orchestration Layer) via the standardised automation interface Module Type Package (MTP).

Project goals

Within REUNION, suppliers, operators, universities and regulatory authorities are working together to clarify the requirements for such modules and subsequently put them into practice. Particular emphasis is placed on bridging the gap between research and industrial application. The newly developed and further refined modules will be MTP-automated, and their energy efficiency will be made transparent through energy KPIs. The aim is also to further develop the MTP standard. The compatibility of different modules is demonstrated in joint set-ups. The further development of MTP with energy KPIs and its integration into the Process Orchestration Layer is implemented and verified using demonstrators. The modules are documented in accordance with the FAIR (findable, accessible, interoperable, reusable) principles, enabling flexible process development and approval of modular chemical plants.

REUNION at FST

Our research investigates how modular systems can not only be implemented technically, but also systematically described, interconnected and optimised. The focus is on developing semantic, machine-readable documentation that remains usable throughout the entire lifecycle of the systems. To this end, information is converted into knowledge models and linked in a graph database to enable data access for various stakeholders, such as PEA manufacturers, automation specialists, operators of modular systems and regulatory authorities.

On this basis, we are developing approaches for the selection, interconnection and operation of modular plants that take technical, organisational and IT aspects into account collectively. This results in tools with which modular production systems can be designed not only to be more flexible, but also more transparent and sustainable. In doing so, we are contributing to the scientific foundation and practical implementation of modular process engineering as a key technology for sustainable production.

Graph databases allow the user to efficiently store and retrieve data and metadata for physical and virtual experiments. Thanks to their flexibility and efficiency, graph data bases are the optimal choice for most of our research.

To make data machine readable and interpretable, it is essential to semantically describe them with clear, consistent and standardised vocabulary. To achieve this, ontologies are used. Ontologies define classes within a domain, as well as their attributes and the relations between them. They create a common understanding of terms within a domain, and thus allow precise communication between humans and machines. Additionally, ontologies enable users to make logical conclusions through the relations between classes and their properties. Furthermore, ontologies can be used to integrate data from different sources, to structure data and to improve search capabilities. The use of ontologies support users in adhering to FAIR (findable, accessible, interoperable, reusable) principles.

Further reading:

W3C: Web Ontology Language (OWL 2)

Technical Operations Research can help to structure the solution process in order to master the complexity of system design. The goal is to establish mathematical optimisation methods in engineering and to objectify the decision-making process. The questions shown in the figure of the TOR pyramid guide the engineer through the planning process. After defining the function, goal and playing field, the planning problem is transformed into a mathematical optimisation problem. With the help of discrete optimisation, we determine the best possible selection of components, their interconnection and the corresponding control strategy. This system design is then verified using suitable software solutions such as Modelica. In order to validate the calculations and models, we carry out experimental investigations at the institute.

With suitable software solutions we want to contribute to the use of discrete processes in the early design stage of technical systems. We have also published this methodology under the maxim “As good as possible”. Furthermore, we offer the lecture Technical Operations Research (TOR).

One of the core competences of the Chair of Fluid Systems is the analytical modeling of physical processes. The created models represent a physical process which can be solved by an equation with analytical solution. The problem is simplified to such an extent that only physical quantities that influence the process are considered (“as little as possible – as much as necessary”).

Furthermore, we use dimensional analysis. With dimensional analysis, a problem can be described in a dimensionless way by relating all quantities to corresponding characteristic quantities of the problem. The resulting dimensionless values help to achieve a compact “generally valid” representation of the results.

The dimensionless results are not only valid for a certain case, but for all physically similar problems. We use this for scaling. The functional data obtained on a model (e.g. reduced image, or model with different material) are transferred to the function of the real fullscale system.