In order to provide a balanced protection against range of shift sizes in high-quality processes, new one-sided adaptive truncated exponentially weighted moving average (ATEWMA) control chart with known and estimated parameters is developed for monitoring time-between-events (TBE) data. A dedicated Markov chain model established evaluating the run length properties operating conditions. Further...

Recently, monitoring the process mean and variability simultaneously for multivariate processes by using a single control chart has drawn some attention. However, due to the complexity of multivariate distribution, the existing methods in the univariate processes can not be readily extended to the multivariate processes. In this paper, we propose a new single control chart which integrates the ...

BACKGROUND Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates. The severity and length of influenza outbreaks vary from year to year. Quick and reliable detection of the start of an outbreak is needed to promote public health measures. METHODS We propose the use of an exponentially weighted moving aver...

Since little attention has been devoted to multiattribute control charts in the literature, in this research a new methodology is developed to employ the multivariate exponentially weighted moving average (MEWMA) chart for multiattribute processes. Moreover, since the variable sample size and sampling interval (VSSI) MEWMA charts detect small process mean-shifts faster than the traditional MEWM...

A traditional approach to monitor both the location and the scale parameters of a quality characteristic is to use two separate control charts. These schemes have some difficulties in concurrent tracking and interpretation. To overcome these difficulties, some researchers have proposed schemes consisting only one chart. However, none of these schemes is designed to work with individual observat...

Nonparametric (distribution-free) control charts have been introduced in recent years when quality characteristics do not follow a specific distribution. When the sample selection is prohibitively expensive, we prefer ranked-set sampling over simple random because ranked set sampling-based outperform charts. In this study, proposed nonparametric homogeneously weighted moving average based on Wi...

A memory-type control chart is an important tool of statistical process for monitoring small to moderate shifts in the manufacturing process. Using prior information by Bayesian approach helpful charts. In this paper, a new hybrid exponentially weighted moving average (HEWMA) suggested under theory using ranked set sampling (RSS) schemes posterior and predictive distribution with informative di...

An effective control scheme can be instrumental in increasing productivity and reducing cost. While facing an outlier-existing process, using the mean ( X ) control chart and the range (R) control chart for monitoring the process mean and variance will lead to high level false alarms. Recently, some median ( X~ ) control charts, such as the X~ Shewhart control chart, the exponentially weighted ...

Quality control is an important role in industry for maintain quality stability. Statistical process can quickly investigate the occurrence of unforeseen causes or shifts using charts. Mixed Exponentially Weighted Moving Average - Cumulative Sum (MEC) chart a tool used to monitor and evaluate whether production not. The MEC method combination (EWMA) (CUSUM) Combining two charts aims increase se...

Monitoring complex production systems is primordial to ensure management, reliability and safety as well as maintaining the desired product quality. Early detection of emergent abnormal behaviour in monitored systems allows pre-emptive action to prevent more serious consequences, to improve system operations and to reduce manufacturing and/or service costs. This study reports the design of a ne...