通过BPMN扩展建模多层次业务流程监控

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Guosheng Kang, Zhen Wang, Hangyu Cheng, Jianxun Liu, Yiping Wen, Jun Peng
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引用次数: 0

摘要

业务流程监控包括对组织为实现特定目标而进行的一系列活动进行实时监督。流程事件监控点(pmp)用于查明流程模型中预期事件发生的特定位置。然而,在一般的业务流程建模语言中,例如业务流程模型和表示法(BPMN),缺乏对pemp的显式建模。本文提出了一种对业务流程模型中的成对事件监控点进行建模的方法,以通过BPMN扩展跟踪特定活动或流程段的执行状态。具体来说,通过扩展序列流的建模元素来设计过程监测点。此外,利用改进的流程结构树(RPST)对业务流程模型进行分解,以验证所设计的成对监控点的可靠性。所提出的方法允许在过程段级别进行灵活的监控。流程监控数据可用于清晰地了解业务流程,尤其对异构业务流程模型的决策提供支持。通过对实际业务流程的案例研究,验证了所提出的流程监控建模方法的有效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Multilevel Business Process Monitoring via BPMN Extension

Business process monitoring involves real-time supervision of a series of activities carried out by an organization to achieve specific objectives. Process event monitoring points (PEMP) are used to pinpoint specific locations within a process model where expected events are anticipated to occur. However, in general business process modeling languages, such as business process model and notation (BPMN), there is a lack of explicit modeling for PEMPs. This article proposes a method for modeling pairwise event monitoring points in business process models to track the execution status of specific activities or process segments via BPMN extension. Specifically, process monitoring points are designed by expanding the modeling element of sequence flow. Moreover, the business process model is decomposed using the refined process structure tree (RPST) to verify the soundness of the designed pairwise monitoring points. The proposed method allows flexible monitoring at the process segment level. And the process monitoring data could be used for a clear understanding of business progress, especially useful in heterogeneous business process model to support decision-making. Through case study from real-world business processes, the effectiveness and usefulness of the proposed process monitoring modeling method is validated.

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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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