1

An Event Data Extraction Approach from SAP ERP for Process Mining

The extraction, transformation, and loading of event logs from information systems is the first and the most expensive step in process mining. In particular, extracting event logs from popular ERP systems such as SAP poses major challenges, given the …

Towards Reliable Business Process Simulation: A Framework to Integrate ERP Systems

A digital twin of an organization (DTO) is a digital replication of an organization used to analyze weaknesses in business processes and support operational decision-making by simulating different scenarios. As a key enabling technology of DTO, …

OCEL: A Standard for Object-Centric Event Logs

The application of process mining techniques to real-life information systems is often challenging. Considering a Purchase to Pay (P2P) process, several case notions such as order and item are involved, interacting with each other. Therefore, …

A General Framework for Action-Oriented Process Mining

Process mining provides techniques to extract process-centric knowledge from event data available in information systems. These techniques have been successfully adopted to solve process-related problems in diverse industries. In recent years, the …

From predictive to prescriptive process monitoring: Recommending the next best actions instead of calculating the next most likely events

Predictive business process monitoring (PBPM) deals with predicting a process's future behavior based on historical event logs to support a process's execution. Many of the recent techniques utilize a machine-learned model to predict which event type …

Prediction-based Resource Allocation using LSTM and Minimum Cost and Maximum Flow Algorithm

Predictive business process monitoring aims at providing the predictions about running instances by analyzing logs of completed cases of a business process. Recently, a lot of research focuses on increasing productivity and efficiency in a business …