Abstract: General requirements for knowledge representation in
the form of logic rules, applicable to design and control of industrial
processes, are formulated. Characteristic behavior of decision trees
(DTs) and rough sets theory (RST) in rules extraction from recorded
data is discussed and illustrated with simple examples. The
significance of the models- drawbacks was evaluated, using
simulated and industrial data sets. It is concluded that performance of
DTs may be considerably poorer in several important aspects,
compared to RST, particularly when not only a characterization of a
problem is required, but also detailed and precise rules are needed,
according to actual, specific problems to be solved.