Application of bayesian network in the diagnosis of hot-dip galvanising process

Barbara Mrzygłód¹, Anna Adrian¹, Stanisława Kluska-Nawarecka^1,2, Robert Marcjan³

¹AGH University of Science and Technology, Department of Industrial Computer Science.
²Center of Competence for Advanced Foundry Technology in Cracow.
³AGH University of Science and Technology, Department of Computer Science.

DOI:

https://doi.org/10.7494/cmms.2007.2.0163

Abstract:

This study presents an output of the application of a probabilistic method of inference based on Bayes’ rule in the diagnosis of defects formed during hot-dip galvanising process. Bayesian cause-effect network for given group of surface defects and its causes was build. Many factors causing defects was taken into consideration in like: technological parameters, technological nodes and character of cause. The process of creating knowledge representation of the hot-dip galvanising process was disclosed on chosen defect (discontinuity of coating) and two causes (pH fluxing bath and surface contamination) along with a scheme of reasoning in Bayesian network and its implementation in a Norsys Netica packet. The advantages and drawbacks of a probabilistic method of representation of the incomplete and uncertain empirical knowledge were highlighted.

Cite as:

Mrzygłód, B., Adrian, A., Kluska-Nawarecka, S., & Marcjan, R. (2007). Application of bayesian network in the diagnosis of hot-dip galvanising process. Computer Methods in Materials Science, 7(2), 317 – 323. https://doi.org/10.7494/cmms.2007.2.0163

Article (PDF):

Keywords:

Formalization of knowledge, Uncertain knowledge, Bayesian networks, Reasoning in a Bayesian network

References:

Cowell, R.G., Dawid, A.P., Lauritzen, S.L., Spiegelhalter, D.J., 1999, Probabilistic networks and expert systems, in: Statistics for Engineering and Information Science, Springer, New York.

Kluska-Nawarecka, S., Marcjan, R., Mrzygłód, B., 2006, Ocena możliwości implementacji wybranych metod reprezentacji wiedzy dla potrzeb diagnostyki wad powierzchni wyrobów metalowych, Proc. 13th Conf. Informatyka w Technologii Metali – KomPlasTech, eds, Szeliga, D., Pietrzyk, M., Kusiak, J., Szczawnica, 23-30 (in Polish).

Norsys Software Corp., 2004, http://www.norsys.com/

Plucińska A., Pluciński T, 2005, Probabilistyka. Rachunek prawdopodobieństwa. Statystyka matematyczna. Procesy stochastyczne, Wydawnictwo Naukowo-Techniczne, Warszawa, (in Polish).

Russell S.J., Norvig P., 1995, Artificial Intelligence: a modern approach, Prentice Hall, Englewood Cliffs.