NIST logo
*
Bookmark and Share

Statistical Process Monitoring for Autocorrelated Data Project

Summary:

Develop statistical approaches to monitor process mean, process variability, and process capability indices for autocorrelated data.

Description:

Process monitoring is very important for industries. Statistical methodologies have been used to monitor various production process successfully. The majority of statistical process monitoring techniques assume that the process data are free of autocorreation. However, this assumption isfrequently invalid in many manufacturing processes and other processes. Under such conditions, the traditional statistical monitoring methodologies are not effective. The impetus of this project is to develop new statistical methodlogies to apply to the autocorrelated data.

 

Major Accomplishments:

  • Zhang, N. F. and Pintar, A. L. (2014) Monitoring process variability for stationary process data, Quality and Reliability Engineering International.
  • Winkel, P. and Zhang, N. F. (2012) Statistical process control in clinical medicine, a book chapter in "Statistical Methods in Healthcare", ed. Faltin, Kenett and Ruggeri, Wiley.
  • Winkel, P. and Zhang, N. F. (2008) Statistical process control in medicine - the peril of risk adjustment, a book chapter in Encyclopedia of Statistics in Quality and Reliability, Wiley.
  • Zhang, N. F. (2006) The batched moving averages of measurement data and their applications in data treatment, Measurement, 39, 864-875.
  • Winkel, P. and Zhang, N. F. (2005) The effect of uncertainty components such as recalibration on the performance of quality control charts, Scandinavian Journal of Clinical and Laboratory Investigation, 65, 707-720.
  • Zhang, N. F. and Winkel, P. (2004) Serial correlation of quality control data on the use of proper control charts, Scandinavian Journal of Clinical and Laboratory investigation, 64, 195-204.
  • Zhang, N. F. (2001) Combining process capability indices from a sequence of independent samples, International Journal of Production research, 39(13), 2769-2781.
  • Zhang, N. F. (2000) Statistical control charts for monitoring the mean of a stationary process, Journal of Statistical Computation and Simulation, 66, 249-258.
  • Zhang, N. F. (1998) Estimating process capability indices for autocorrelated data, Journal of Applied Statistics, 25(4), 559-574.
  • Zhang, N. F. (1998) A statistical control chart for stationary process data, Technometrics, 40(1), 24-38.
  • Zhang, N. F. (1997) Detection capability of residual control chart for statioanry process data, 24(4), 475-492.
  • Zhang, N. F. (1997) Autocorrelation analysis of some linear transfer function models and its applications in the dynamic process system, Lectures in Applied Mathematics, 33, 385-399, American Mathematical Society.
  • Zhang, N. F. and Pollard, J. P. (1994) Analysis of autocorrelations in dynamic processes, Technometrics, 36, 354-368.
  • Lead Organizational Unit:

    itl
    Contact

    Nien-fan Zhang
    (301)975-2853
    nien-fan.zhang@nist.gov

    100 Bureau Drive, M/S 8980
    Gaithersburg, MD 20899-8980