Predicting schedule adherence of engineering changes : a case study on effectivity date adherence prediction using machine learning
Ognjen Radisic-Aberger, Peter Burggräf, Fabian Steinberg, Alexander Becher and Tim Weisser
| Year of publication: |
2025
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|---|---|
| Authors: | Radisic-Aberger, Ognjen ; Burggräf, Peter ; Steinberg, Fabian ; Becher, Alexander ; Weißer, Tim |
| Published in: |
International journal of production research. - London [u.a.] : Taylor & Francis, ISSN 1366-588X, ZDB-ID 1485085-0. - Vol. 63.2025, 11, p. 3913-3937
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| Subject: | Artificial intelligence | engineering change | machine learning | predictive business process monitoring | schedule adherence | SDG 9: Industry, innovation, and infrastructure | Künstliche Intelligenz | Prozessmanagement | Business process management | Prognoseverfahren | Forecasting model | Scheduling-Verfahren | Scheduling problem | Algorithmus | Algorithm | Neuronale Netze | Neural networks | Innovation |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1080/00207543.2024.2432465 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015445280