Combining Process Mining and Machine Learning for Lead Time Prediction in High Variance Processes

Lecture notes in production engineering, pp. 528–537

Authors 6

1. Martin Welsing corresponding Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany

2. Jan Maetschke Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany

3. Katharina Thomas Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany

4. Andreas Gützlaff Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany

5. Günther Schuh Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany

6. S. Meusert
   Affiliation as printed

   MAN Truck & Bus SE, Vogelweiherstraße 33, 90441, Nürnberg, Germany