Completed Projects
During the last years, a large number of research projects were successfully completed. These generates new impulses for further research.
Modularization and Package Unit Integration
Modularization and Package Unit Integration
Today, package units are used to supply the plant with input and auxiliary materials or to assemble end products and are usually supplied with their own automation system with predefined functions and behavior. The integration of such a package in a superior control system involves large manual efforts. One main aspect of the integration of package units is the ability to transfer descriptions of sequence controls of the package unit for visualization and manual intervention.
In this project, potentials and limits of current and perspective technologies (e.g. FDI) for a simplified integration of package units into a process control system were analyzed and prototypically implemented by using the example of the integration of a process control system.
SIMATIC PCS 7 University Modules
Siemens Automation Cooperates with Education (SCE) offers more than 100 free didactically prepared training materials for initial training in automation and drive technology - tailored to studies and optimally usable in combination with the available trainer packages.
Training documents for SIMATIC PCS 7 were still missing and therefore a suitable concept for the use at universities should be created.
SCE knowledge platform
Siemens Automation Cooperates with Education (SCE) offers mothen than 100 free didactically prepared teachings materials for the initial training on the subject of automation and drive technology - adapted to curricula and study plans and optimally usable in combination with the purchasable trainer packages.
With the TIA portal and the new S7-1500 controllers, these were to be checked once again for their didactic concept and optimized.
The aim of this project is therefore to create a modern didactic concept for the teaching materials of SCE and to realize the first modules with it.
FDI Usability Style Guide
In this project, the Chair of Process Control Engineering supported the FDI Usability Style Guide Team in analyzing the current status of field device integration, identifying the need for action, formulating suggestions for improvement, and in the design and evaluation of the style guide by usability experts.
Explorative investigation of app-based plant diagnosis with mobile information systems
Explorative Untersuchung der App-basierten Anlagendiagnose mit mobilen Informationssystemen
Within the scope of this project, the potential of an app-based system diagnosis with mobile information systems was explanatively investigated. For this purpose, the work tasks and usage contexts of the plant diagnosis were analyzed in detail, priority tasks identified and suitable scenarios derived.
For the three exemplary tasks of monitoring, diagnosis and therapy, an integrated mobile information system was conceived, designed and prototypically realized, which can obtain information from the digital system via a wireless network connection and visualize it on site.
Based on these results, a focus group workshop with representatives from different industrial sectors identified and elaborated novel services in the field of plant diagnostics.
Fast Semantics
For the vertical integration of semantic information carriers in process-related plant levels, it is indispensable that actuators and sensors show their data intelligently at the field level. Scenarios like process optimization, intelligent process control assistive control room technology, or preventative maintenance require to receive and process lifetime and life cycle data from every level and abstraction layers of a plant topology.
Actuator and sensor technology is a major booster of every process automation. Data protocols like OPC UA challenge these device classes. The microcomputing platforms built into these are designed to be long-lasting, resilient, and simultaneously cost-effective. However, the requirements for the OPC UA protocol forces the use of complex 32 bit based computer systems using external memory components. This not only increases the price, but also the complexity of the products as well as the number of failure errors. The main task of the computing platform, the control of the actuators and sensors, remains unaltered. The software for the new and powerful platforms must be ported and verified at great expense.
In the project, Fast Semantics, within the scope of the cluster Fast Actuators, Sensors & Transceiver, will investigate the realization of a hardware-based OPC UA server that functions as a peripheral component for microcomputing architectures. The hardware implementation enables completely and for the first time the deterministic, hard-real time implementation of the OPC UA protocol on-chip. The ASIC created for this project also uses the 28 nm CMOS SLP technology, which enables magnificent energy efficiency. The 2-Wire, GBit Ethernet PHY, contributed by the fast carnet, offers a real-time communication connection with high bandwidth. It arises a high parameterizable, scalable IP-basis for semantically communication actuators and sensors in the field level.
AI-incubator-labs in the process industry
AI-incubator-labs in the process industry
KEEN connects 20 partners consisting of industrial companies and scientific institutions with the objective to introduce artificial intelligence (AI) technologies and methods in the process industry and to evaluate and implement their technical, economical, and social potential. The KEEN consortium investigates the implementation of AI methods in the process industry regarding the following three topics:
- modelling of processes, product features, and plants
- engineering of plants and processes
- operation optimisation and the implementation of self-optimising plants.
The KEEN project has the objective to improve substantially the efficiency of all engineering and production activities along the product life cycle via the implementation of AI methods. For the testing of the method real data from industrial processes will be provided. The newly developed AI methods will be tested in real working environments and production plants in order to prove the economic benefit, applicability, and reliability of the methods and technologies.
KEEN is a research project that will generate another post pilot gap which will be closed by a network of AI Incubator Labs for a sustainable transfer. The addressed gap reaches from TRL4 (technology readiness level) in the lab phase to TRL8 in the pilot application phase.
Goal of the Incubator-Labs is deriving and defining of AI-based business models for prolonging the AI-Incubator-Labs beyond public funding. Preliminary specific answers will be given on typical questions of the business model development such as customer segments, key partners, key activities, and key resources. Transparency requirements for the eco-system and conflicts of interest and goals will be identified.