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Online monitoring and fault identification of mean shifts in bivariate processes using decision tree learning techniques
16 references·9 citing·28 second hop
Online monitoring and fault identification of mean shifts in bivariate processes using decision tree learning techniques (2011)Online monitoring and fault identificatio…A neural network ensemble-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes (2007)A neural network ensemble-bas…On‐line Identification and Quantification of Mean Shifts in Bivariate Processes using a Neural Network‐based Approach (2006)On‐line Identification and Qu…Fault Diagnosis in Multivariate Control Charts Using Artificial Neural Networks (2005)Fault Diagnosis in Multivaria…A hybrid learning-based model for on-line detection and analysis of control chart patterns (2005)A hybrid learning-based model…Mean shifts detection and classification in multivariate process: a neural-fuzzy approach (2002)Mean shifts detection and cla…Kollár Ádám Ferenc levelezése (2000)Kollár Ádám Ferenc levelezéseA Practical Approach for Interpreting Multivariate T2 Control Chart Signals (1997)A Practical Approach for Inte…Decomposition of T 2 for Multivariate Control Chart Interpretation (1995)Decomposition of T 2 for Mult…Multivariate Profile Charts for Statistical Process Control (1994)Multivariate Profile Charts f…Introduction to Statistical Quality Control (1992)Introduction to Statistical Q…A Multivariate Exponentially Weighted Moving Average Control Chart (1992)A Multivariate Exponentially …Comparisons of MultivariateCUSUMCharts (1990)Comparisons of MultivariateCU…Multivariate Generalizations of Cumulative Sum Quality-Control Schemes (1988)Multivariate Generalizations …Multivariate quality control (1985)Multivariate quality controlMultivariate CUSUM Quality-Control Procedures (1985)Multivariate CUSUM Quality-Co…Multivariate Quality Control-illustrated by the air testing of sample bombsights (1947)Multivariate Quality Control-…Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective (2021)Application of Machine Learni…Using Random Forest to Interpret Out-of-Control Signals (2020)Using Random Forest to Interp…A condition monitoring approach for machining process based on control chart pattern recognition with dynamically-sized observation windows (2020)A condition monitoring approa…One‐sided control chart based on support vector machines with differential evolution algorithm (2019)One‐sided control chart based…A distance-based control chart for monitoring multivariate processes using support vector machines (2016)A distance-based control char…Variation source identification for deep hole boring process of cutting-hard workpiece based on multi-source information fusion using evidence theory (2014)Variation source identificati…Identification and quantification of concurrent control chart patterns using extreme-point symmetric mode decomposition and extreme learning machines (2014)Identification and quantifica…Monitoring and diagnosing of mean shifts in multivariate manufacturing processes using two-level selective ensemble of learning vector quantization neural networks (2013)Monitoring and diagnosing of …Autoregressive coefficient-invariant control chart pattern recognition in autocorrelated manufacturing processes using neural network ensemble (2013)Autoregressive coefficient-in…Multivariate Control Charts for Individual Observations (1992)High-Dimensional Process Monitoring and Fault Isolation via Variable Selection (2009)Multivariate Statistical Process Control Using LASSO (2009)Multivariate SPC Methods for Process and Product Monitoring (1996)Wavelet-based multiscale statistical process monitoring: A literature review (2004)Multivariate Quality Control (2013)Multivariate Quality Control (1947)A Review and Analysis of Cause-Selecting Control Charts (1993)A Comparison of Multivariate Control Charts for Individual Observations (1996)An Approach to the Probability Distribution of Cusum Run Length (1972)A review of multivariate control charts (1995)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)Control Chart Tests Based on Geometric Moving Averages (1959)Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)Control Chart Tests Based on Geometric Moving Averages (2000)CONTINUOUS INSPECTION SCHEMES (1954)Quality Control and Industrial Statistics. (1967)Quality, productivity, and competitive position (1982)A Note on Multivariate CUSUM Procedures (1987)Regression Adjustment for Variables in Multivariate Quality Control (1993)Multivariate SPC Charts for Monitoring Batch Processes (1995)A Review and Perspective on Control Charting with Image Data (2011)Some Current Directions in the Theory and Application of Statistical Process Monitoring (2014)Overview of PCA-Based Statistical Process-Monitoring Methods for Time-Dependent, High-Dimensional Data (2015)Time-Series Modeling for Statistical Process Control (1988)Statistical process control as a tool for research and healthcare improvement (2003)A Rank-Based Multivariate CUSUM Procedure (2001)Designing a Multivariate EWMA Control Chart (1997)
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References

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  • 1992A Multivariate Exponentially Weighted Moving Average Control Chart1,231 cited
  • 1988Multivariate Generalizations of Cumulative Sum Quality-Control Schemes720 cited
  • 2000Kollár Ádám Ferenc levelezése613 cited
  • 1990Comparisons of MultivariateCUSUMCharts520 cited
  • 1947Multivariate Quality Control-illustrated by the air testing of sample bombsights471 cited
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  • 2007A neural network ensemble-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes96 cited
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  • 2006On‐line Identification and Quantification of Mean Shifts in Bivariate Processes using a Neural Network‐based Approach

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85 cited
  • 2002Mean shifts detection and classification in multivariate process: a neural-fuzzy approach67 cited
  • Cited by

    • 2016A distance-based control chart for monitoring multivariate processes using support vector machines55 cited
    • 2021Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective52 cited
    • 2014Identification and quantification of concurrent control chart patterns using extreme-point symmetric mode decomposition and extreme learning machines45 cited
    • 2013Autoregressive coefficient-invariant control chart pattern recognition in autocorrelated manufacturing processes using neural network ensemble42 cited
    • 2014Variation source identification for deep hole boring process of cutting-hard workpiece based on multi-source information fusion using evidence theory34 cited
    • 2020A condition monitoring approach for machining process based on control chart pattern recognition with dynamically-sized observation windows33 cited
    • 2013Monitoring and diagnosing of mean shifts in multivariate manufacturing processes using two-level selective ensemble of learning vector quantization neural networks26 cited
    • 2019One‐sided control chart based on support vector machines with differential evolution algorithm26 cited
    • 2020Using Random Forest to Interpret Out-of-Control Signals11 cited