Evaluating early predictive performance of machine learning approaches for engineering change schedule – A case study using predictive process monitoring techniques

By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering change (EC) process. Here, failing to adhere to planned imp...

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Veröffentlicht in:	Supply Chain Analytics Jg. 8; S. 100087
Hauptverfasser:	Radišić-Aberger, Ognjen, Burggräf, Peter, Steinberg, Fabian, Becher, Alexander, Weißer, Tim
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.12.2024 Elsevier
Schlagworte:	Earliness Effectivity Date Engineering Change Machine Learning Predictive Process Monitoring Engineering Change Predictive Process Monitoring Effectivity Date Earliness Machine Learning
ISSN:	2949-8635, 2949-8635
Online-Zugang:	Volltext
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