Some quality control schemes have been developed when several related quality characteristics are to be monitored. The familiar multivariate process monitoring and control procedure is the Hotelling’s T 2 control chart for monitoring the mean vector of the process. It is a direct analog of the univariate shewhart x̄ chart. As in the case of univariate, the ARL improvements are very important par...

Quality of ore varies in the complete spectrum of mining operations. Depending upon the quality control practices at mines, grade variation may follow a systematic pattern or an erratic fluctuation. The different statistical quality control techniques, especially control charts, are used for continuous monitoring of grade variation. The main purpose of the application of control charts is to id...

In many industrial and medical applications observations are censored either due to inherent limitations or cost/time considerations. For example, with many products their lifetimes are sufficiently long that it is infeasible to test all products until failure even using accelerated testing. As a result, often a limited stress test is performed and only a proportion of the true failure times ar...

The most commonly used statistical process control charts to detect special causes are Shewhart and Cusum charts. However, the Cuscore chart is a contemporary alternative that is especially well suited for detecting special causes that can be modeled in advance based on their characteristic effect on the system. In this paper, we develop the appropriate Cuscore statistic and the required contro...

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...

In this research, we propose the new mixed control chart called Moving Average-Cumulative Sum (MA-CUSUM) used for monitoring parameter changes in asymmetrical and symmetrical processes. Its efficiency was compared with that of Shewhart, Cumulative (CUSUM), Average (MA), Sum-Moving (CUSUM-MA) charts by using their average run lengths (ARLs), standard deviation length (SDRL), median (MRL) via Mon...

Nonparametric control charts are presented in order to figure out the problem of detecting changes in the process median (or mean)‎, ‎or changes in the variability process where there is limited knowledge regarding the underlying process‎. ‎When observations are reported imprecise‎, ‎then it is impossible to use classical nonparametric control charts‎. ‎This paper is devoted to the problem of c...

Lindley distribution is a continuous with various applications some of which are in medicine, genetics, epidemiology, biology, finance and actuarial sciences, ecology, meteorology, sociology, demography, agriculture, hydrology, geosciences, reliability engineering, life testing survival analysis, airborne systems communications, environmental studies modeling describing human mistakes, strikes,...