Process model extension using heuristics miner: (Case study: Incident management of Volvo IT Belgium)

VINST is a system used to record all activities related to the incident and problem management in Volvo IT Belgium. In this VINST system, activities recorded in several attributes, such as serial number, change date and time, status, and any other attributes needed, which is stored in the event log. In these sequenced activities, there are some specific knowledge that is not explicitly described in the event log. To find some of the necessary knowledge, this study extracts knowledge from the event log, by using process mining. Heuristic miner algorithm was implemented in this study, because this algorithm has advantages compared to other methods, such as the ability to calculate the frequency of the process, to handle noise, and to combine the frequency between events and trace in the event log to build a process model. The steps being taken in this study began with the discovery process, followed by conformance checking, and completed with process model extension in enhancement step, which was finding knowledge based on analysing process model and event log. This study was using a specifically designed program to achieve the goals of this study. This study used VINST incident records with 149 cases consisting of 2.771 events. By applying heuristics miner, a process model discovered with precision, recall, and f-measure more than 96%. Knowledge gained from this process model extension were the analysis of time and organizational perspectives in forms of timestamp-impact attribute relation and originator-impact attribute relation.