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In recent years we observe dramatic changes in the way in which quality features of manufactured products are designed and inspected. The modeling and monitoring problems obtained by new inspection methods and fast multi-stream high-speed sensors are quite complex. It is mainly not the mean, the variance, the covariance matrix or a simple profile which reflects the behavior of the quality characteristics but the shape, surfaces and images, etc.
In this talk new procedures for monitoring image processes are introduced. They are based on multivariate exponential smoothing and cumulative sums taking into account the local correlation structure. A comparison is given with existing methods. Within an extensive simulation study the performance of the analyzed methods is discussed. The presented results are based on a joint work with Yarema Okhrin and Ivan Semeniuk.
Reference:
Y. Okhrin, W. Schmid and I. Semeniuk: New approaches for monitoring image data. In: IEEE Transactions on Image Processing, 30, 921-933, 2021.
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