Journal article

POSPÍŠIL Milan, MATES Vojtěch, HRUŠKA Tomáš and BARTÍK Vladimír. Process Mining in a Manufacturing Company for Predictions and Planning. International Journal on Advances in Software. 2013, vol. 2013, no. 3, pp. 283-297. ISSN 1942-2628. Available from:
Publication language:english
Original title:Process Mining in a Manufacturing Company for Predictions and Planning
Title (cs):Dolování dat z procesů pro predikci a plánování
Journal:International Journal on Advances in Software, Vol. 2013, No. 3, US
business process simulation, business process intelligence, data mining, process mining, prediction, optimization, recommendation, association rules, genetic algorithms.
Simulation can be used for analysis, prediction and optimization of business processes. Nevertheless, process models often differ from reality. Data mining techniques can be used to improve these models based on observations of a process and resource behavior from detailed event logs. More accurate process models can be used not only for analysis and optimization, but also for prediction and recommendation as well. This paper analyses process models in a manufacturing company and its historical performance data. Based on the observation, a simulation model can be created and used for analysis, prediction, planning and for dynamic optimization. Focus of this paper is in different data mining problems that cannot be solved easily by well-known approaches like Regression Tree.
   author = {Milan Posp{\'{i}}{\v{s}}il and Vojt{\v{e}}ch Mates and
	Tom{\'{a}}{\v{s}} Hru{\v{s}}ka and Vladim{\'{i}}r
   title = {Process Mining in a Manufacturing Company for Predictions
	and Planning},
   pages = {283--297},
   journal = {International Journal on Advances in Software},
   volume = {2013},
   number = {3},
   year = {2013},
   ISSN = {1942-2628},
   language = {english},
   url = {}

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