Designing learning environments for energy efficiency through model scale production processes

Alexander Kaluza*, Max Juraschek, Benjamin Neef, Reinhard Pittschellis, Gerrit Posselt, Sebastian Thiede, Christoph Herrmann

*Corresponding author for this work

Research output: Contribution to journalConference articleAcademicpeer-review

13 Citations (Scopus)
51 Downloads (Pure)

Abstract

In the recent past global industries started to take action towards energy efficient manufacturing to oppose the challenges of the increasing demand for natural resources. Substantiated competencies on energy efficiency measures can serve as a competitive advantage especially in energy intensive manufacturing environments. Learning environments that build upon action based learning have proven to be an effective instrument for developing competence in manufacturing. Evolving from environments that focus on traditional command variables related to cost, quality and time, learning environments especially designed for energy efficiency are the subsequent step. To enable the competence development on energy efficiency in academic and occupational education a design approach for learning environments is presented. The initial focus is set on the machine level. The model scale is chosen due to good accessibility, less space and investment requirements compared to industrial scale learning environments. A main consideration for the design is the reproduction of the surrounding machine periphery entailing a significant energy demand. Additionally, potential efficiency measures need to be aligned of the requirements on the model scale. The case of a CNC milling center is presented and evaluated concerning technical functionality of the designed milling center.

Original languageEnglish
Pages (from-to)41-46
Number of pages6
JournalProcedia CIRP
Volume32
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event5th Conference on Learning Factories, CLF 2015 - Bochum, Germany
Duration: 7 Jul 20158 Jul 2015
Conference number: 5

Keywords

  • Energy efficiency
  • Learning environment
  • Machine level
  • Model scale

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