Smart manufacturing and continuous improvement and adaptation of predictive models

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3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)528-531
Number of pages4
JournalProcedia Manufacturing
Volume42
DOIs
Publication statusPublished - 2020
Event1st International Conference on Industry 4.0 and Smart Manufacturing, ISM 2019 - Rende (CS), Italy
Duration: 20 Nov 201922 Nov 2019

Keywords

  • Artificial Intelligence
  • Concept Drift
  • Predictive Models
  • Smart Manufacturing

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