Conceptional Approach for Process Monitoring Based on an Assistance System for Grinding

  • Tobias KaufmannEmail author
  • Joachim Stanke
  • Daniel Trauth
  • Thomas Bergs
Conference paper


The Industrial Internet of Things (IoT) has a major role both in research and in manufacturing companies. There is an international understanding that the greatest economic opportunities of the overall IoT context are found in production optimization. High tolerance requirements prevailing in grinding highlight the necessity and thus represent one of the driving factors for the development of an assistance system for grinding processes. The mass information stream (big data) from process monitoring and control, that is generated during the investigation of cause-effect relationships in the grinding process, poses special challenges to the data processing architecture. Therefore, this contribution focusses on a concept of an edge computing approach for acquisition and sustainable storage of grinding process data streams and gives a demonstrating proof of concept using both machine control data and external sensor data focussing on the cooling lubrication supply.


Grinding Process control Edge computing system architecture 



The authors thank the German Research Foundation (DFG) for the funding of the depicted research within the SFB/TR96-A03. The authors also thank the Senseering working group of the Department for Grinding, Forming and Technology Planning of the machine tool laboratory wzl of the rwth aachen university for their hardware and software support. In particular, the authors thank H. Breuer, B. Sc. and P. Niemietz, M. Sc.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Tobias Kaufmann
    • 1
    Email author
  • Joachim Stanke
    • 1
  • Daniel Trauth
    • 1
  • Thomas Bergs
    • 1
  1. 1.Laboratory for Machine Tools and Production Engineering WZLRWTH Aachen UniversityAachenGermany

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