115 Forum on Fuzziness Applications of a Universal Expert System in Industry * M. Dohnal Dept. of Chemical Engineering, Technical University of Brno, Kravi Hora 2, 602 O0 Brno, Czechoslovakia The theory of artificial intelligence has reached a level which enables practical applications. As a consequence of this several expert systems (corrosion, rubber science etc.) already exist. However, a development of such expert systems is time- consuming and requires highly sophisticated software. There- fore a fuzzy based expert system SENECA is proposed. A fuzzy simulation program is available so it is relatively easy to develop the expert system based on a concept of fuzzy similar- ity. An expert base of SENECA can absorb very heterogenous, partially inconsistent and incomplete data of different range and accuracy. The application of SENECA is demonstrated on a hypothetical chemical reactor with two independent variables. Keywords: expert system, artificial intelligence, fuzzy simula- tion, fuzzy sets, ill-known system, engineering expe- rience, linguistic quantification, SENECA, intelli- gent user interface, corrosion, bio-engineering. M. Dohnal was born in Brno, Czechoslovakia, in 1943. He received his Ing. and CSc degrees in Mechani- cal Engineering from the Technical University of Brno in 1965 and 1971, respectively; and his DrSc degree in System Engineering from the Techni- cal University of Leuna-Merseburg, GDR in 1983. In 1968 he joined the Technical University of Brno, where he is currently Associate Professor of Control Engineering. From 1976 to 1977, he was with the Chemical En- gineering Department at the University of Cambridge. From 1980-81, he was with the Department of System Engineering at the Technical University of Leuna-Merseburg as a visiting Associate Professor. His research interests include application of Artificial Intelligence, and System and Chemical Engineer- ing. He has written more than 100 papers on these subjects. He was formerly employed as a Process Engineer with Chemopro- jekt and Chepos, performing CAD and economical evaluation of chemical and food plants. * This is the second article in our series on "Fuzziness ". For the first article see Vol. 6 Nr. 1 of the journal. North-Holland Computers in Industry 6 (1985) 115-121 1. Introduction Primary information is such information which is available at the very beginning of its analysis (e.g. statistical [1], fuzzy [2]). It means that experi- mental results (laboratory studies, pilot plants ex- perimentation, full-scale operation) are not the only source of primary information. Re-used in- formation (e.g. literature) supplies primary infor- mation provided that original experimental results are not accessible directly. Whether an engineer is concerned with design, planning, operability or hazard analysis, operation and control, predictions of the process behaviour are needed. Therefore a suitable mathematical model has to be developed. This is why primary information is needed. An information analysis of modelling confirms that a limited extent of the primary information set and the information loss during the formal treatment (e.g. statistical analysis), are two main bottlenecks on the way towards suitable models [31. 2. Pre-Processing A limited amount in a primary information set and information loss during the formal treatment can be significantly influenced by a suitable choice of pre-processing mode. A pre-processing is the formal treatment of primary data in order to in- crease data adressability and instant applicability. Addressability is a property of information items to be stored within a given information structure (data base). An instant applicability means a pos- sibility to use the result of pre-processing for de- sired purposes (optimization, hazard analysis etc.) without any further formal treatment. 0166-3615/85/$3.30 © 1985 Elsevier Science Publishers B.V. (North-Holland)