Process mining techniques can be used to analyse business processes using the data
logged during their execution. These techniques are leveraged in a wide range of domains …

This paper examines the role of advanced analytics in optimizing business processes,
focusing on techniques, implementation strategies, benefits, and challenges. Advanced …

This perspective article explores how process mining can extract clinical insights from
mobile health data and complement data-driven techniques like machine learning. Despite …

The transition to Industry 4.0 means a new era in manufacturing with a new level of
production automation, human-to-machine cooperation and product customization. It …

Process mining is a research area focusing on the design of algorithms that can
automatically provide insights into business processes. Among the most popular algorithms …

The increasing number of IoT devices equipped with sensors and actuators pervading every
domain of everyday life allows for improved automated monitoring and analysis of …

The engineering of digital twins and their user interaction parts with explicated processes,
namely process-aware digital twin cockpits (PADTCs), is challenging due to the complexity …

The complexity of industrial processes imposes a lot of challenges in building accurate and
representative causal models for abnormal events diagnosis, control and maintenance of …

Predictive process monitoring is a family of techniques to analyze events produced during
the execution of a business process in order to predict the future state or the final outcome of …

Process mining supports the analysis of the actual behavior and performance of business
processes using event logs. An essential requirement is that every event in the log must be …