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An assessment of the kernel‐distance‐based multivariate control chart through an industrial application

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References

2005Introduction to Statistical Quality Control954 cited
2003A kernel-distance-based multivariate control chart using support vector methods198 cited
2002Support vector machines for recognizing shifts in correlated and other manufacturing processes78 cited
2001A Smooth Nonparametric Approach to Multivariate Process Capability59 cited
2005Kernel distance-based robust support vector methods and its application in developing a robust K-chart53 cited
2006Multivariate Fuzzy Multinomial Control Charts30 cited

Cited by

2019One‐sided control chart based on support vector machines with differential evolution algorithm26 cited
2011Optimal T2 Control Chart with a Double Sampling Scheme – An Alternative to the MEWMA Chart25 cited
2017Time-adaptive support vector data description for nonstationary process monitoring24 cited
2014A Comparison Study of Distribution‐Free Multivariate SPC Methods for Multimode Data23 cited
2012Performance Evaluation of One‐Class Classification‐based Control Charts through an Industrial Application18 cited
2018A control scheme for monitoring process covariance matrices with more variables than observations16 cited
2018An effective multivariate control chart for detecting small mean shifts using support vector data description12 cited
2014

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A One-Class Classification-Based Control Chart Using the K -Means Data Description Algorithm

12 cited

2022Advances in statistical quality control chart techniques and their limitations to cement industry8 cited

2013On the Use of the K-Chart for Phase II Monitoring of Simple Linear Profiles8 cited