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Monitoring Constraints in Business Processes Using Object-Centric Constraint Graphs

arXiv 2210.12080 ↗First posted 21 Oct 2022cs.AIcited by 2

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Abstract (arXiv)

Constraint monitoring aims to monitor the violation of constraints in business processes, e.g., an invoice should be cleared within 48 hours after the corresponding goods receipt, by analyzing event data. Existing techniques for constraint monitoring assume that a single case notion exists in a business process, e.g., a patient in a healthcare process, and each event is associated with the case notion. However, in reality, business processes are object-centric, i.e., multiple case notions (objects) exist, and an event may be associated with multiple objects. For instance, an Order-To-Cash (O2C) process involves order, item, delivery, etc., and they interact when executing an event, e.g., packing multiple items together for a delivery. The existing techniques produce misleading insights when applied to such object-centric business processes. In this work, we propose an approach to monitoring constraints in object-centric business processes. To this end, we introduce Object-Centric Constraint Graphs (OCCGs) to represent constraints that consider the interaction of objects. Next, we evaluate the constraints represented by OCCGs by analyzing Object-Centric Event Logs (OCELs) that store the interaction of different objects in events. We have implemented a web application to support the proposed approach and conducted two case studies using a real-life SAP ERP system.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 4 of its 11 references that are in the map. First posted on arXiv 21 Oct 2022.

Builds on

4 of 11 references.

References · 4

  1. 2020Discovering Object-Centric Petri Netscited by 28
  2. 2020Multi-Dimensional Event Data in Graph Databasescited by 14
  3. 2021Precision and Fitness in Object-Centric Process Miningcited by 9
  4. 2022OPerA: Object-Centric Performance Analysiscited by 4

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Citing papers per year: 2023: 1; 2024: 0; 2025: 1.

2 papers.