The Burr type XII has been studied for various applications of lifetime modelings. However, control charts related to the Burr type XII percentiles have not been seen in the literature. In this paper, three control charts for the Burr type XII percentiles are investigated. An extensive Monte Carlo simulation study is conducted to compare among the Shewhart-type chart, and parametric bootstrap c...

Methods of statistical process control were briefly investigated in the field of educational measurement as early as 1999. However, only the use of a cumulative sum chart was explored. In this article other methods of statistical quality control are introduced and explored. In particular, methods in the form of Shewhart mean and standard deviation charts are introduced as techniques for ensurin...

Monitoring Markov Dependent Observations with a Log-Likelihood Based CUSUM Shabnam Mousavi and Marion R. Reynolds, Jr. Department of Statistics, The Pennsylvania State University, University Park, PA 16802-2111, U.S.A., Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany, Departments of Statistics and Forestry, Virginia Polytechnic Institute and State University, B...

Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, are not appropriately used here. In this paper, we propose a new asymmetric EWMA ...

In this paper, we evaluate the capability to detect traffic anomalieswith Shewhart, CUSUM, andEWMA control charts. In order to cope with seasonal variation and serial correlation, control charts are not applied to traffic measurement time-series directly, but to the prediction errors of exponential smoothing and Holt-Winters forecasting. The evaluation relies on flow data collected in an ISP ba...

Duncan first proposed the economic design of x control charts in 1956 to control normal process means and ensure that an economic design control chart actually lowers the cost, compared with a Shewhart control chart. Many authors have studied the control charts from economic viewpoint from then on. An economic design does not consider the statistical properties, such as type I or type II error ...

While researchers and practitioners may seamlessly develop methods of detecting outliers in control charts under a univariate setup, screening multivariate pose serious challenges. In this study, we propose robust chart based on the Stahel-Donoho estimator (SDRE), whilst process parameters are estimated from phase-I. Through intensive Monte-Carlo simulation, study presents how estimation presen...

− The traditional control charts are based on the assumption that the measurement data relating to the average of each subgroup of the parameters under observation of a specific quality characteristic of product, process, system or service, are reported regardless of time stability of its own parameters. This condition is generally not verified in real cases, where we should take into account t...

although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. identifying the real time of the process changes is known as change-point estimation problem. there are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. in this paper we propose a novel appro...