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

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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Bibliographic Details
Main Authors: Ognjen Radišić-Aberger, Peter Burggräf, Fabian Steinberg, Alexander Becher, Tim Weißer
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Supply Chain Analytics
Subjects:
Engineering Change
Machine Learning
Effectivity Date
Predictive Process Monitoring
Earliness
Online Access:http://www.sciencedirect.com/science/article/pii/S294986352400030X

Internet

http://www.sciencedirect.com/science/article/pii/S294986352400030X

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