Smart Manufacturing and Continuous Improvement and Adaptation of Predictive Models

Abstract

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.