Artificial Neural Networks as a Means for Making Process Control Charts User Friendly
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.
KeywordsStatistical process control Control chart Pattern recognition Neural networks
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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