Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …

The increasing need for economic, safe, and sustainable smart manufacturing combined
with novel technological enablers has paved the way for artificial intelligence (AI) and big …

While a business process is most often executed following a normal path, anomalies may
sometimes arise and can be captured in event logs. Event log anomalies stem, for instance …

Predictive Process Monitoring [29] is a branch of process mining that aims at predicting the
future of an ongoing (uncompleted) process execution. Typical examples of predictions of …

GPT-3 and several other language models (LMs) can effectively address various natural
language processing (NLP) tasks, including machine translation and text summarization …

The predictive business process monitoring is a family of online approaches to predict the
unfolding of running traces based on the knowledge learned from historical event logs. In …

Object-centric processes (also known as Artifact-centric processes) are implementations of a
paradigm where an instance of one process is not executed in isolation but interacts with …

Traditional process mining techniques take event data as input where each event is
associated with exactly one object. An object represents the instantiation of a process …

As business environments become more dynamic and complex, it becomes indispensable
for organizations to objectively analyze business processes, monitor the existing and …

Large Language Models (LLMs) are likely to play a prominent role in future AI-augmented
business process management systems (ABPMSs) catering functionalities across all system …