Xhelo, Evrikli (2022) Building a software system to autonomize business process adaptation. Master's Thesis / Essay, Computing Science.
|
Text
mCS_2022_XheloE.pdf Download (4MB) | Preview |
|
![[img]](https://fse.studenttheses.ub.rug.nl/style/images/fileicons/text.png) |
Text
toestemming.pdf Restricted to Registered users only Download (171kB) |
Abstract
The discipline of business process management (BPM) is an integral aspect of businesses, systems and other disciplines that work with business processes. Business processes are used by any establishment whose end goal is to provide a service to their customers. Such establishments use business processes to structurally define the steps that are followed in order to produce the goal of their outcome (the happy flow) or the other possible paths. Recently, however, it has become clear that there is a need for a new (and optional) phase in the BPM life-cycle, called process adaptation. The rise of predictive process monitoring has made it possible to learn about the outcome of a running business process before its execution is finished. When the outcome is not as expected, it should be possible to adapt the process accordingly and resume its execution without having to start from the beginning. Today, workflow engines that facilitate the execution of business processes also provide developers with the means to make process adaptation possible, however, in most cases this feature has to be implemented in-house by the organisation’s developers. In this thesis, we have created a system that makes process adaptation convenient to oversee. One of the primary products of this system is an extensible, user-friendly dashboard that depicts information about process instances that could potentially require adaptation.
| Item Type: | Thesis (Master's Thesis / Essay) |
|---|---|
| Supervisor name: | Karastoyanova, D. and Mohsen, F.F.M. |
| Degree programme: | Computing Science |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 24 Jan 2022 12:38 |
| Last Modified: | 24 Jan 2022 12:38 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/26486 |
Actions (login required)
 |
View Item |