An Approach to Participatory Business Process Modeling: BPMN Model Generation Using Constraint Programming and Graph Composition

Designing business process models plays a vital role in business process management. The acquisition of such models may consume up to 60% of the project time. This time can be shortened using methods for the automatic or semi-automatic generation of process models. In this paper, we present a user-f...

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Bibliographic Details
Main Authors: Piotr Wiśniewski, Krzysztof Kluza, Antoni Ligęza
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Applied Sciences
Subjects:
Online Access:http://www.mdpi.com/2076-3417/8/9/1428
Description
Summary:Designing business process models plays a vital role in business process management. The acquisition of such models may consume up to 60% of the project time. This time can be shortened using methods for the automatic or semi-automatic generation of process models. In this paper, we present a user-friendly method of business process composition. It uses a set of predefined constraints to generate a synthetic log of the process based on a simplified, unordered specification, which describes activities to be performed. Such a log can be used to generate a correct BPMN model. To achieve this, we propose the use of one of the existing process discovery algorithms or executing the activity graph-based composition algorithm, which generates the process model directly from the input log file. The proposed approach allows process participants to take part in process modeling. Moreover, it can be a support for business analysts or process designers in visualizing the workflow without the necessity to design the model explicitly in a graphical editor. The BPMN diagram is generated as an interchangeable XML file, which allows its further modification and adjustment. The included comparative analysis shows that our method is capable of generating process models characterized by high flow complexity and can support BPMN constructs, which are sufficient for about 70% of business cases.
ISSN:2076-3417