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Machine learning–driven in situ process monitoring with vibration frequency spectra for chemical mechanical planarization
12 references·0 citing·42 second hop
Machine learning–driven in situ process monitoring with vibration frequency spectra for chemical mechanical planarization (2020)Machine learning–driven in situ process m…Wafer quality monitoring using spatial Dirichlet process based mixed-effect profile modeling scheme (2018)Wafer quality monitoring usin…Introduction to Statistical Process Control (2013)Introduction to Statistical P…Multiscale monitoring of autocorrelated processes using wavelets analysis (2012)Multiscale monitoring of auto…On Nonparametric Statistical Process Control of Univariate Processes (2011)On Nonparametric Statistical …Distribution-free monitoring of univariate processes (2011)Distribution-free monitoring …A Review of Statistical Methods for Quality Improvement and Control in Nanotechnology (2009)A Review of Statistical Metho…Wavelet-based SPC procedure for complicated functional data (2005)Wavelet-based SPC procedure f…Wavelet-based multiscale statistical process monitoring: A literature review (2004)Wavelet-based multiscale stat…Nonparametric Control Charts: An Overview and Some Results (2001)Nonparametric Control Charts:…A review of neural networks for statistical process control (1998)A review of neural networks f…Introduction to Statistical Quality Control (1992)Introduction to Statistical Q…A comparison of neural networks to SPC charts (1991)A comparison of neural networ…CONTINUOUS INSPECTION SCHEMES (1954)Optimal Stopping Times for Detecting Changes in Distributions (1986)A new exponentially weighted moving average control chart for monitoring the coefficient of variation (2014)An Adaptive Sampling Strategy for Online High-Dimensional Process Monitoring (2014)Distribution‐free Phase II CUSUM Control Chart for Joint Monitoring of Location and Scale (2014)Cumulative Sum Charts and Charting for Quality Improvement (1998)Adaptive Phase II Nonparametric EWMA Control Chart with Variable Sampling Interval (2014)Rank-based EWMA procedure for sequentially detecting changes of process location and variability (2016)A Cramér-von Mises test-based distribution-free control chart for joint monitoring of location and scale (2017)Time Series Analysis: Forecasting and Control (1977)The Exponentially Weighted Moving Average (1986)A Multivariate Exponentially Weighted Moving Average Control Chart (1992)Decision tree based control chart pattern recognition (2008)Statistical process control for monitoring non-linear profiles using wavelet filtering and B-Spline approximation (2008)Big Data? Statistical Process Control Can Help! (2019)Synthetic neural networks for process control (1989)Using radial basis function neural networks to recognize shifts in correlated manufacturing process parameters (1998)Support vector machines for recognizing shifts in correlated and other manufacturing processes (2002)Artificial neural networks to classify mean shifts from multivariate χ2 chart signals (2004)On-Line Monitoring When the Process Yields a Linear Profile (2000)Introduction to Statistical Quality Control (2001)Statistical Process Monitoring of Nonlinear Profiles Using Wavelets (2009)Time series forecasting based on wavelet filtering (2015)Research Issues and Ideas in Statistical Process Control (1999)Controversies and Contradictions in Statistical Process Control (2000)A kernel-distance-based multivariate control chart using support vector methods (2003)A Multivariate Sign EWMA Control Chart (2011)Some Current Directions in the Theory and Application of Statistical Process Monitoring (2014)Introduction to Quality Engineering: Designing Quality into Products and Processes (1986)Introduction to Quality Engineering: Designing Quality Into Products and Processes (1989)Design and Analysis of Experiments (2005)Online parameter estimation and run-to-run process adjustment using categorical observations (2010)Economic Control of Quality of Manufactured Product. (1932)Statistical Quality Control (1990)Designing production systems for quality: Research opportunities from an automotive industry perspective (2003)A hybrid learning-based model for on-line detection and analysis of control chart patterns (2005)A survey of control-chart pattern-recognition literature (1991–2010) based on a new conceptual classification scheme (2012)Time-Series Modeling for Statistical Process Control (1988)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)Some perspectives on nonparametric statistical process control (2018)Nonparametric (distribution-free) control charts: An updated overview and some results (2019)
this work references cited by second hop

References

  • 1992Introduction to Statistical Quality Control7,842 cited
  • 2013Introduction to Statistical Process Control453 cited
  • 2001Nonparametric Control Charts: An Overview and Some Results363 cited
  • 1998A review of neural networks for statistical process control151 cited
  • 2004Wavelet-based multiscale statistical process monitoring: A literature review144 cited
  • 2011On Nonparametric Statistical Process Control of Univariate Processes141 cited
  • 2005Wavelet-based SPC procedure for complicated functional data99 cited
  • 1991A comparison of neural networks to SPC charts85 cited
  • 2011Distribution-free monitoring of univariate processes51 cited
  • 2009A Review of Statistical Methods for Quality Improvement and Control in Nanotechnology49 cited
  • 2012Multiscale monitoring of autocorrelated processes using wavelets analysis23 cited
  • 2018Wafer quality monitoring using spatial Dirichlet process based mixed-effect profile modeling scheme16 cited

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