A significant part of the knowledge used in the production processes is represented with natural language. Yet, the use of that knowledge

in computer-assisted decision-making requires the application of appropriate formal and development tools. An interesting possibility is

created by the use of an ontology that is understandable both for humans and for the computer. This paper presents a proposal for

structuring the information about the foundry processes, based on the definition of ontology adapted to the physical structure of the

ongoing technological operations that make up the process of producing castings.

One way to ensure the required technical characteristics of castings is the strict control of production parameters affecting the quality of

the finished products. If the production process is improperly configured, the resulting defects in castings lead to huge losses. Therefore,

from the point of view of economics, it is advisable to use the methods of computational intelligence in the field of quality assurance and

adjustment of parameters of future production. At the same time, the development of knowledge in the field of metallurgy, aimed to raise

the technical level and efficiency of the manufacture of foundry products, should be followed by the development of information systems

to support production processes in order to improve their effectiveness and compliance with the increasingly more stringent requirements

of ergonomics, occupational safety, environmental protection and quality. This article is a presentation of artificial intelligence methods

used in practical applications related to quality assurance. The problem of control of the production process involves the use of tools such

as the induction of decision trees, fuzzy logic, rough set theory, artificial neural networks or case-based reasoning.