Business process improvement (BPI) is a crucial value-adding stage of business process management, as it introduces process changes to eliminate flaws and enhance performance. However, the inherent demands of BPI on domain knowledge, process expertise, time, and creativity in conjunction with a...

Air cargo terminals are indispensable hubs in the global trade network, yet inefficiencies in their cargo handling processes can trigger significant disruptions, manifesting as costly delays, inflated operational expenses, and a decline in service quality, thereby jeopardizing intricate supply...

Business process analysis and improvement approaches typically require accurate models of activity processing or preceding waiting times. Data-driven methods derive these from historical event log data, but typically fit static probability distributions that overlook contextual information or...

Predictive business process monitoring aims to enhance process execution by providing real-time predictions about the future evolution of a process instance. In recent years, several deep learning approaches have been established as state of the art for various predictive tasks, including those...

Event logs are the primary source of information in process mining. An event log consists of events, each having three mandatory attributes: a case identifier, an activity, and a timestamp. Translucent event logs add a fourth mandatory attribute: enabled activities. These are activities for...

Process models are central artefacts in business process management: they drive analysis, automation, simulation, and compliance checking. Yet creating and maintaining high-quality models is labor-intensive and requires expertise in both the domain and formal notations such as Petri nets or...

The increasing reliance on data-driven technologies such as Artificial Intelligence and Process Mining has transformed various sectors. Yet, access to real-world data is often restricted by privacy concerns. Synthetic data offers a promising solution by enabling secure data sharing while...

Organizations use conformance checking, a sub-discipline of process mining, which compares process executions with predefined process models, to identify deviations in business processes. These capabilities make conformance checking highly relevant. To make its results accessible and tailored to...

Ambiguity in business process models can result in multiple interpretations by model readers. This leads to undesirable outcomes such as misunderstandings, unclear allocation of responsibilities, and unexpected behaviors. Despite these potential consequences, the impact of ambiguity on model...

In this paper, aProCheCk, an Autonomous Process Coherence Checking method, is developed. aProCheCk leverages large language models (LLMs) to enhance the coherence checking of multi-level process documentation within business process management (BPM). This research addresses the need for...