While real-time data and sophisticated Reinforcement Learning (RL) approaches are emerging, logistic organizations, in particular Small and Medium-sized Enterprises (SMEs), lack the tools and expertise to effectively identify whether (parts of) their business processes are suitable for using RL and adopt these approaches in their daily practice. This paper presents the results of our efforts […]

In the past decades, a broad range of technological innovations have helped organizations reach new levels of performance and have shaped the economies of the world and societies of the future. However, unexpected events, such as the COVID-19 pandemic and the blocking of the Suez Canal, have shown that many organizations are unprepared to deal […]

A bottleneck usually is a sub-process in the main process which delays the process. The performance of a process can be increased by eliminating the bottlenecks. To this end, opportunities to analyze and mitigate bottlenecks by using process mining techniques can be an interesting direction to utilize. This paper aims to classify literature on process […]

When aggregating logistic event data from different supply chain actors and information systems for process mining, interoperability, data loss, and data quality are common challenges. This position paper proposes and evaluates the use of the Open Trip Model (OTM) for process mining. Inspired by the current industrial use of the OTM for reporting and business […]