University of Pannonia, Faculty of Information Technology
Department of Electrical Engineering and Information Systems

Dr. Dósa György, DSc, professor, This email address is being protected from spambots. You need JavaScript enabled to view it.

Dulai Tibor, master teacher, This email address is being protected from spambots. You need JavaScript enabled to view it.

Starkné dr. Werner Ágnes, PhD, associate professor,  This email address is being protected from spambots. You need JavaScript enabled to view it.

Ábrahám Gyula, PhD student, This email address is being protected from spambots. You need JavaScript enabled to view it.

Nagy Zsuzsanna, MSc student, This email address is being protected from spambots. You need JavaScript enabled to view it.

Research Activity

Our research topics are the analysis of industrial processes, fault diagnosis and solving of scheduling problems. During the industrial process-related research on the one side tools record the measured values and the times belonging to them, on the other hand it can be recorded who or what completed what kind of intervention during the analysis. If this information is put in the correct order then we can get history or issue of the research process. By recording information belonging to the process execution a log file can be prepared. Because the analysis can be divided into parts ‒ e.g., a test of a product ‒, there can be found a relation between the data recorded during the analysis and the performance of analysis in most cases. If this part-analysis is performed more then once then trends can be detected with the analysis of data series, and so certain conclusions can be made, possibly incorrectly performed operations can be cleared up or identified. In the field of scheduling problems we can try to assign resources to the activities of processes so that the outputs should be suitable for the criteria of conventional scheduling (time, cost or combination of these aspire to minimum), and unexpected events generate the smallest possible negative effect. For achieving our goal we take the cooperation of the resources into consideration, respectively we rest on the information, which origin from acquired experience in the course of earlier running.

Current Project Activities

EFOP-3.6.1-16-2016-00015 –  University of Pannonia’s comprehensive institutional development program to promote Smart Specialization Strategy.

Selected Publications

  • Nagy, Zs. ; Werner-Stark, Á. ; Dulai, T. An Industrial Application Using Process Mining to Reduce the Number of Faulty Products, In: András, Benczúr; Bernhard, Thalheim; Tomáš, Horváth; Silvia, Chiusano; Tania, Cerquitelli; Csaba, Sidló; Peter, Z Revesz (szerk.) New Trends in Databases and Information Systems : ADBIS 2018 Short Papers and Workshops, AI*QA, BIGPMED, CSACDB, M2U, BigDataMAPS, ISTREND, DC, Budapest, Hungary, September, 2-5, 2018, Proceeding Cham (Svájc), Svájc : Springer International Publishing, (2018) pp. 352-363. , 12 p.