Combining Process Mining and Queueing Theory for the ICT Ticket Resolution Process at LUMC

Aslan, Ayse (2017) Combining Process Mining and Queueing Theory for the ICT Ticket Resolution Process at LUMC.

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Abstract:The research in this thesis analyzes and supports the ticket resolution process of ICT department in Leiden University Medical Center (LUMC). In this work, the performance of the ticket resolution process is investigated and resolution time predictions for tickets are produced. The main purpose of the research is combining process mining and queueing theory techniques for the ticket resolution process. Process mining is utilized to gain insights of the ticket resolution process from the historical data. The mission of combining process mining and queueing theory is accomplished by making use of the process insights that process mining provides to build a queueing network model of the ticket resolution process. This research aims to take a queueing theory perspective in providing resolution time predictions for tickets. A stochastic Petri net approach which incorporates mean queueing performances of the queueing network model of the ticket resolution process is proposed to provide queueing theory perspective resolution time predictions.
Item Type:Essay (Master)
Clients:
Leiden University Medical Center
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 85 business administration, organizational science
Programme:Applied Mathematics MSc (60348)
Link to this item:http://purl.utwente.nl/essays/73305
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