Advanced energy data analytics to predict machine overall equipment effectiveness (OEE): a synergetic approach to foster sustainable manufacturing

Sebastian Thiede*

*Corresponding author for this work

Research output: Contribution to journalConference articleAcademicpeer-review

1 Citation (Scopus)
33 Downloads (Pure)

Abstract

Understanding the relation of production activities and energy demand is of crucial importance for fostering sustainable manufacturing. While so far the perspective is mainly on augmenting production data with energy related aspects, this paper suggests an alternative approach to overcome current challenges. Energy data is the starting point and shall be utilized for the prediction of the overall equipment effectiveness (OEE) which is an established and comprehensive indicator for machine performance. Based on a common underlying definitory framework, two alternative prediction methods are presented. Results indicate that an energy based OEE prediction is actually possible with reasonable accuracy and effort.

Original languageEnglish
Pages (from-to)438-443
Number of pages6
JournalProcedia CIRP
Volume116
Early online date18 Apr 2023
DOIs
Publication statusPublished - 2023
Event30th CIRP Life Cycle Engineering Conference, LCE 2023 - Rutgers Academic Building, New Brunswick, United States
Duration: 15 May 202317 May 2023
Conference number: 30

Keywords

  • Energy efficiency
  • Machine
  • Overall Equipment Effectiveness (OEE)

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