Detecting Deviations in Business Processes Using Process Mining
| Autor: | Mahmoud Abd Ellatif, Mohamed Ahmed Amin, Essam Shaaban |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Service (business)
Business process Computer science Process (engineering) Process mining 02 engineering and technology computer.software_genre Conformance checking Data modeling Business process discovery 020204 information systems 0202 electrical engineering electronic engineering information engineering Process control 020201 artificial intelligence & image processing Data mining computer |
| Zdroj: | 2019 14th International Conference on Computer Engineering and Systems (ICCES). |
| DOI: | 10.1109/icces48960.2019.9068146 |
| Popis: | Monitoring business processes is one of process mining duties, this study aims to detect and diagnose deviations in business processes starting from process discovery to detection and diagnosis as well. The solution is applied to an anonymous Radiology lab in Egypt that focuses on the service process. The data set is about 184622 events that represent 21478 cases extracted from the database according to process mining required attributes. After detecting deviations by applying conformance checking; the results show the deviated cases because of the skipped, inserted, or switched activities. Besides; in some cases, there are overlapped processes that lead to a lot of diagnostics are applied to know deviations causes that influence the process which gives more insights for both all moves on the log and all moves on model for all activities. This finally gives recommendations to control these deviations and to enhance the service process by separating some activities into another process, some cases when doing more one service, or the interaction between instruments and the service process which finally enhanced the service process in the Radiology lab. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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