Automated statistical evaluation of energy data in the automotive production

Ingo Labbus, Hanno Teiwes, Marc-André Filz, Christoph Herrmann, Mark Gonter, Markus Rössinger, Sebastian Thiede

Research output: Contribution to journalConference articleAcademicpeer-review

2 Citations (Scopus)
11 Downloads (Pure)

Abstract

In the manufacturing industry, there is a strong demand for methods evaluating energy related data like energy load profiles. The obtained energy data can be used in commercial production system planning and simulation software solutions. However, due to missing automated evaluation solutions, there is a lack of data for e.g. machine tools or utilities. Therefore, the industry tries to bridge the gap between software and measured energy data. The aim of this article is to develop an automated energy load profile analysis for production equipment to provide consumption data for further uses, e.g. in the early factory planning phase. The main advantage of the presented method is the reduction of input data only on energy data to identify e.g. the machine state depended energy demand. To achieve this, statistical methods and clustering algorithms are applied. The approach is exemplified by a use case from the automotive industry.
Original languageEnglish
Pages (from-to)1154-1159
JournalProcedia CIRP
Volume81
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event52nd CIRP Conference on Manufacturing Systems, CIRP CMS 2019 - Ljubljana, Slovenia
Duration: 12 Jun 201914 Jun 2019
Conference number: 52

Keywords

  • Energy efficiency
  • Automotive industry
  • Statistical evaluation
  • Data analysis

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  • Cite this

    Labbus, I., Teiwes, H., Filz, M-A., Herrmann, C., Gonter, M., Rössinger, M., & Thiede, S. (2019). Automated statistical evaluation of energy data in the automotive production. Procedia CIRP, 81, 1154-1159. https://doi.org/10.1016/j.procir.2019.03.284