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Artificial Neural Networks as a Means for Making Process Control Charts User Friendly

  • Izabela Rojek
  • Agnieszka Kujawińska
  • Adam Hamrol
  • Michał Rogalewicz
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 637)

Abstract

The paper discusses usability of various pattern recognition methods, especially based on artificial neural networks for decision making support in process control chart analysis. Their effectiveness for detecting process instability is compared with the effectiveness of a human operator and of a widely accessed commercial statistical software. The results are verified on the basis of data obtained from real production processes.

Keywords

Statistical process control Control chart Pattern recognition Neural networks 

Notes

Acknowledgements

The presented results derive from a scientific statutory research conducted by Chair of Management and Production Engineering, Faculty of Mechanical Engineering and Management, Poznan University of Technology, Poland and Institute of Mechanics and Applied Information Science, Faculty of Mathematics, Physics and Technical Sciences, Kazimierz Wielki University, Poland, supported by the Polish Ministry of Science and Higher Education from the financial means in 2017.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Izabela Rojek
    • 1
  • Agnieszka Kujawińska
    • 2
  • Adam Hamrol
    • 2
  • Michał Rogalewicz
    • 2
  1. 1.Institute of Mechanics and Applied Computer ScienceKazimierz Wielki UniversityBydgoszczPoland
  2. 2.Department of Management and Production EngineeringPoznan University of TechnologyPoznanPoland

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