Statistical process control with intelligence
using fuzzy ART neural networks

doi:10.1007/s11465-010-0008-y

Front. Mech. Eng.

2010, Vol. 5

Issue (2) : 149-156 https://doi.org/10.1007/s11465-010-0008-y

Research articles

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG,Tao ZAN,Renyuan FEI,

School of Mechanical Engineering, Beijing University of Technology, Beijing 100022, China;

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Abstract With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.

Keywords statistical process control (SPC) fuzzy adaptive resonance theory (ART) histogram control chart time series analysis

Issue Date: 05 June 2010

Cite this article:

Renyuan FEI,Min WANG,Tao ZAN. Statistical process control with intelligence using fuzzy ART neural networks[J]. Front. Mech. Eng., 2010, 5(2): 149-156.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-010-0008-y
https://academic.hep.com.cn/fme/EN/Y2010/V5/I2/149

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