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.
The work presents the results of the experimental research concerning the impact of a heat treatment (toughening) of aluminum bronze CuAl10Fe4Ni4 on its mechanical properties. The conditions of the experiments and selected results are described. A detailed description of the effects of individual heat treatment conditions namely low and high temperature aging is also presented in the work.
The object of the experimental studies was to determine the mechanical properties of a hypoeutectic EN AC - 42100 (EN ACAlSi7Mg0,3)
silumin alloy, where the said properties are changing as a result of subjecting the samples of different types to solution
treatment. An important aspect of the studies was the use type of device for the heat treatment. As a basic parameter representing the
mechanical properties, the tensile strength of the metal (Rm) was adopted.
The article describes the problem of selection of heat treatment parameters to obtain the required mechanical properties in heat- treated
bronzes. A methodology for the construction of a classification model based on rough set theory is presented. A model of this type allows
the construction of inference rules also in the case when our knowledge of the existing phenomena is incomplete, and this is situation
commonly encountered when new materials enter the market. In the case of new test materials, such as the grade of bronze described in
this article, we still lack full knowledge and the choice of heat treatment parameters is based on a fragmentary knowledge resulting from
experimental studies. The measurement results can be useful in building of a model, this model, however, cannot be deterministic, but can
only approximate the stochastic nature of phenomena. The use of rough set theory allows for efficient inference also in areas that are not
yet fully explored.
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