Ontologie

Knowledge management through semantic modeling

Communication between autonomous systems requires a common language and uniform semantics. Furthermore, due to the increasing complexity of the entire systems, a stronger human-machine interaction is unavoidable. However, this requires a language construct which, on the one hand, takes into account the limited absorption capacity of the human person and, on the other hand, heeds the peculiarities of the machine processing.

In recent years, the ontologies have established themselves as a suitable tool for the semantic description of plant components, processes and data and thus offer a uniform and extensible format for communication between the different systems as well as between the systems and the people at the plants.

The BFI used ontologies in the projects I2MSteel and EnergyDB to provide the software components with a description of the interfaces to the already existing systems (measured values, controllers, production control systems, etc). This also includes the internal data storage as well as the communication of the system among each other.

An additional field of application for the ontologies is the formalization of human experience (know-how) into a form that can be interpreted by machines (softwares). This approach makes it possible to collect, process and store the experience of the various employees. With the help of this knowledge, computers are enabled to generate trade recommendations for the current situation on the basis of human experience from the past.

See also:

Projects KnowDec and RuleDec

Recommendation

Processing of raw materials and residues by agglomeration

Situation: Agglomeration also results in fine-grained feedstocks, e.g. Alternative carbon carriers, fine-grained or ferrous residuals, and made usable for sintering […]

Concepts for reducing friction and wear

Your goals: Optimization of components with regard to wear resistance Selection and evaluation of optimal materials and coatings Optimization of […]

Adjustment of the fuel gas air ratio in the near stoichiometric range

Your goals: Efficient heat treatment of steel, non-ferrous metals, porcelain / ceramics Gas generation from natural gas Complete thermal post-combustion […]

Optimization of dedusting

Goals: Cost-effective inventory and assessment of existing plants with regard to dust emissions and the efficiency of dedusting Proposal and […]