Predictive models are an important success factor for smart manufacturing. Accordingly, purely data-driven models as well as hybrid models are increasingly deployed within manufacturing environments for optimal control of plants. However, long-term monitoring and adaptation of predictive models has not been a focus of studies so far but will likely become increasingly more important as more and more predictive models are deployed. We give a number of recommendations for effectively managing predictive models in smart manufacturing environments.
|Seiten (von - bis)||528-531|
|Publikationsstatus||Veröffentlicht - 2020|
|Veranstaltung||1st International Conference on Industry 4.0 and Smart Manufacturing, ISM 2019 - Rende (CS), Italien|
Dauer: 20 Nov. 2019 → 22 Nov. 2019