Generally, the traditional Shewhart p chart has been developed by for charting the binomial data. This chart has been developed using the normal approximation with condition as low defect level and the small to moderate sample size. In real applications, however, are away from these assumptions due to skewness in the exact distribution. In this paper, a modified Exponentially Weighted Moving Av...

Control charts for monitoring of process variance are developed based on Shewhart, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts for mean. In all these variance control charts, log transformation of the sample variance is used. The design procedure of this chart is complex and it is poorly understood by the industry. In this paper a EWMA chart for monito...

The implementation of Statistical Quality Control (SQC) has been tracked in various areas, such as agriculture, environment, industry, and health services. employment SQC methodologies is frequently employed for monitoring identification process irregularities across fields. This research proposes implements a novel methodology agricultural areas. A control chart one the tools that facilitates ...

Abstract The Moving Average method is the most common filter in Digital Signal Processing, optimal for reducing unstable value fluctuations due to interference by maintaining accurate readings. Therefore it often used signal coding context of time (Smith, 1999). kind moving average Exponentially Weighted (EWMA) which applied a sequence random variables, calculating weighted applying weight that...

Rapidly obtaining accurate dense disparity maps has been the focus of stereo matching research. At present, approaches that achieve superior require a large amount computation, which is not suitable for practical applications. To address this issue, paper proposes an efficient local method based on adaptive exponentially weighted moving average filter and simple linear iterative clustering segm...

The general assumption for designing a multivariate control chart is that the multiple variables are independent and normally distributed. This may not be tenable in many practical situations, because with dependency often need to monitored simultaneously ensure process in-control. Gumbel’s Bivariate Exponential (GBE) distribution considered better model skewed data reliability analysis. In thi...

In certain statistical process control applications, quality of a process or product can be characterized by a function commonly referred to as profile. Some of the potential applications of profile monitoring are cases where quality characteristic of interest is modelled using binary,multinomial or ordinal variables. In this paper, profiles with multinomial response are studied. For this purpo...

OBJECTIVE This study aims to compare different control charts to monitor the nosocomial infection rate per 1,000 patient-days. METHODS The control charts considered in this study were the traditional Shewhart chart and a variation of this, the Cumulative Sum and Exponentially Weighted Moving Average charts. RESULTS We evaluated 238 nosocomial infections that were registered in the intensive...