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A hybrid wrapper–filter approach to detect the source(s) of out-of-control signals in multivariate manufacturing process
13 references·0 citing·49 second hop
A hybrid wrapper–filter approach to detect the source(s) of out-of-control signals in multivariate manufacturing process (2014)A hybrid wrapper–filter approach to detec…Feature selection in bankruptcy prediction (2008)Feature selection in bankrupt…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…Artificial neural networks to classify mean shifts from multivariate χ2 chart signals (2004)Artificial neural networks to…An integrated systems approach to process control and maintenance (2004)An integrated systems approac…Using novelty detection to identify abnormalities caused by mean shifts in bivariate processes (2003)Using novelty detection to id…Analysis of variations in a multi-variate process using neural networks (2003)Analysis of variations in a m…Using principal component analysis in process performance for multivariate data (2000)Using principal component ana…Decomposition of T 2 for Multivariate Control Chart Interpretation (1995)Decomposition of T 2 for Mult…A Multivariate Exponentially Weighted Moving Average Control Chart (1992)A Multivariate Exponentially …Identification of out of control quality characteristics in a multivariate manufacturing environment (1991)Identification of out of cont…Comparisons of MultivariateCUSUMCharts (1990)Comparisons of MultivariateCU…Selecting Out of Control Variables With the T 2 Multivariate Quality Control Procedure (1987)Selecting Out of Control Vari…An Application of Multivariate Quality Control to Photographic Processing (1957)An Application of Multivariat…Multivariate Generalizations of Cumulative Sum Quality-Control Schemes (1988)Multivariate Control Charts for Individual Observations (1992)A Practical Approach for Interpreting Multivariate T2 Control Chart Signals (1997)High-Dimensional Process Monitoring and Fault Isolation via Variable Selection (2009)Multivariate Statistical Process Control Using LASSO (2009)Financial Ratios As Predictors of Failure (1966)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Two credit scoring models based on dual strategy ensemble trees (2011)The effect of feature selection on financial distress prediction (2014)Financial credit risk assessment: a recent review (2015)Control Chart Tests Based on Geometric Moving Averages (1959)Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)Multivariate SPC Methods for Process and Product Monitoring (1996)Control Chart Tests Based on Geometric Moving Averages (2000)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)Introduction to Statistical Quality Control (1992)Factory Physics : Foundations of Manufacturing Management (1995)The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance (2000)From process logic to business logic—A cognitive approach to business process management (2005)Joint economic design of EWMA control charts for mean and variance (2006)Do it separately or simultaneously—An empirical analysis of a conjoint implementation of TQM and TPM on plant performance (2011)Process Capability Indices (1986)Process Capability Indices. 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References

  • 1992A Multivariate Exponentially Weighted Moving Average Control Chart1,231 cited
  • 1990Comparisons of MultivariateCUSUMCharts520 cited
  • 1995Decomposition of T 2 for Multivariate Control Chart Interpretation397 cited
  • 2008Feature selection in bankruptcy prediction246 cited
  • 2000Using principal component analysis in process performance for multivariate data145 cited
  • 2004An integrated systems approach to process control and maintenance136 cited
  • 1991Identification of out of control quality characteristics in a multivariate manufacturing environment132 cited
  • 1987Selecting Out of Control Variables With the T 2 Multivariate Quality Control Procedure120 cited
  • 2007A neural network ensemble-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes96 cited
  • 2004Artificial neural networks to classify mean shifts from multivariate χ2 chart signals72 cited
  • 1957An Application of Multivariate Quality Control to Photographic Processing70 cited
  • 2003Using novelty detection to identify abnormalities caused by mean shifts in bivariate processes54 cited
  • 2003Analysis of variations in a multi-variate process using neural networks46 cited

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