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Performance Evaluation of One‐Class Classification‐based Control Charts through an Industrial Application
7 references·3 citing·31 second hop
Performance Evaluation of One‐Class Classification‐based Control Charts through an Industrial Application (2012)Performance Evaluation of One‐Class Class…One-Class Classification-Based Control Charts for Monitoring Autocorrelated Multivariate Processes (2010)One-Class Classification-Base…An assessment of the kernel‐distance‐based multivariate control chart through an industrial application (2010)An assessment of the kernel‐d…One-class classification-based control charts for multivariate process monitoring (2009)One-class classification-base…Robust kernel distance multivariate control chart using support vector principles (2008)Robust kernel distance multiv…Kernel distance-based robust support vector methods and its application in developing a robust K-chart (2005)Kernel distance-based robust …A kernel-distance-based multivariate control chart using support vector methods (2003)A kernel-distance-based multi…Introduction to Statistical Quality Control (1992)Introduction to Statistical Q…An unsupervised one-class-classifier support vector machine to simultaneously monitor location and scale of multivariate quality characteristics (2021)An unsupervised one-class-cla…A One-Class Classification-Based Control Chart Using the K -Means Data Description Algorithm (2014)A One-Class Classification-Ba…On the Use of the K-Chart for Phase II Monitoring of Simple Linear Profiles (2013)On the Use of the K-Chart for…Support vector machines for recognizing shifts in correlated and other manufacturing processes (2002)Introduction to Statistical Quality Control (2005)Optimal T2 Control Chart with a Double Sampling Scheme – An Alternative to the MEWMA Chart (2011)Time-adaptive support vector data description for nonstationary process monitoring (2017)One‐sided control chart based on support vector machines with differential evolution algorithm (2019)Using radial basis function neural networks to recognize shifts in correlated manufacturing process parameters (1998)A review of multivariate control charts (1995)Statistical Learning Methods Applied to Process Monitoring: An Overview and Perspective (2016)Support vector machine in statistical process monitoring: a methodological and analytical review (2016)A statistical learning method for image-based monitoring of the plume signature in laser powder bed fusion (2018)On-Line Monitoring When the Process Yields a Linear Profile (2000)On the Monitoring of Linear Profiles (2003)Monitoring General Linear Profiles Using Multivariate Exponentially Weighted Moving Average Schemes (2007)Time-Series Modeling for Statistical Process Control (1988)Introduction to Statistical Quality Control (2001)Support vector regression based residual MCUSUM control chart for autocorrelated process (2008)Integration of support vector machines and control charts for multivariate process monitoring (2010)Minimal Euclidean distance chart based on support vector regression for monitoring mean shifts of auto-correlated processes (2012)A Multivariate Exponentially Weighted Moving Average Control Chart (1992)Monitoring multivariate process variability with individual observations via penalised likelihood estimation (2012)Nonparametric monitoring of multivariate data via KNN learning (2020)A novel two-stage hybrid default prediction model with k-means clustering and support vector domain description (2021)Multivariate Generalizations of Cumulative Sum Quality-Control Schemes (1988)Synthetic charts to control bivariate processes with autocorrelated data (2016)A new time adjusting control limits chart for concept drift detection (2021)Research Issues and Ideas in Statistical Process Control (1999)Kollár Ádám Ferenc levelezése (2000)An efficient adaptive r-MD multivariate single control chart for nonlinear multiple quality characteristics (2023)A Multivariate Sign EWMA Control Chart (2011)Statistical process control as a tool for research and healthcare improvement (2003)Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications (2014)
this work references cited by second hop

References

  • 1992Introduction to Statistical Quality Control7,842 cited
  • 2003A kernel-distance-based multivariate control chart using support vector methods198 cited
  • 2009One-class classification-based control charts for multivariate process monitoring122 cited
  • 2008Robust kernel distance multivariate control chart using support vector principles54 cited
  • 2005Kernel distance-based robust support vector methods and its application in developing a robust K-chart53 cited
  • 2010An assessment of the kernel‐distance‐based multivariate control chart through an industrial application29 cited
  • 2010One-Class Classification-Based Control Charts for Monitoring Autocorrelated Multivariate Processes22 cited

Cited by

  • 2014A One-Class Classification-Based Control Chart Using the K -Means Data Description Algorithm12 cited
  • 2021An unsupervised one-class-classifier support vector machine to simultaneously monitor location and scale of multivariate quality characteristics11 cited
  • 2013On the Use of the K-Chart for Phase II Monitoring of Simple Linear Profiles8 cited

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