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Nonparametric quality control charts based on the sign statistic
Authors:Raid W Amin  Marion R Reynolds Jr  Bakir Saad
Institution:1. Dept. of Mathematics &2. Statistics , Univ. of West Florida , Pensacola, FL, 32514;3. Departments of Statistics and Forestry , Virginia Polytechnic Instit. &4. State Univ , Blacksburg, VA, 24061;5. Dept. of Business Administration , Alabama State University , Montgomery, AL, 36101-0271
Abstract:Nonparametric control chart are presented for the problem of detecting changes in the process median (or mean), or changes in the process variability when samples are taken at regular time intervals. The proposed procedures are based on sign-test statistics computed for each sample, and are used in Shewhart and cumulative sum control charts. When the process is in control the run length distributions for the proposed nonparametric control charts do not depend on the distribution of the observations. An additional advantage of the non-parametric control charts is that the variance of the process does not need to be established in order to set up a control chart for the mean. Comparisons with the corresponding parametric control charts are presented. It is also shown that curtailed sampling plans can considerably reduce the expected number of observations used in the Shewhart control schemes based on the sign statistic.
Keywords:Average Run Length  Cumulative Sum  Process Control  Sign Test  Sign Chart  Curtailed Sampling
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