There have been changes since the companies realized important role of quality improvement in their success. If they are able to produce high products and satisfy demands, then can survive competitive global markets. Quality applications aim decrease variability, which leads less cost, production time, number defects, scrap, rework more customer satisfaction. be improved by reducing product var...

The share nature of the transmission channel in IEEE 802.11 makes the network vulnerable to several attacks like the MAC layer misbehavior which can be similar to denial of service attack. In this way cheating node by choosing smaller backoff timer attempts to increase its resources at the expense to other stations which respect the protocol. In this paper, we suggest a novel detection scheme o...

Shewhart charts are the most commonly utilised control for process monitoring in industries with assumption that underlying distribution of quality characteristic is normal. However, this may not always hold true practice. In paper, weighted-variance mean developed and their population standard deviation estimated using three subgroup scale estimators, namely deviation, median absolute trimmed ...

Often the least appropriate assumption in traditional control charting technology is that process data constitute a random sample. In reality most process data are correlated—either temporally, spatially, or due to nested sources of variation. One approach to monitoring temporally correlated data uses a control chart on the forecast errors from a time series model of the process with, possibly,...

The presence of asymmetric data in production processes or service operations has prompted the development new monitoring schemes. In this article, an adapted version exponentially weighted moving averages (EWMA) control chart with dynamic limits is proposed to monitor mean samples from skew-normal distribution. detection ability online was investigated by simulating average run length (ARL) pe...

This paper develops a model for the analysis and design of a CUSUM chart for monitoring the process mean in short production runs and proposes statistical measures of performance that are appropriate when the process is not operating indefinitely. The model can be used to evaluate the performance of the CUSUM scheme for any given set of chart parameters and thus allows comparisons with Shewhart...

Under estimated in-control parameters, the Phase II control chart performance is expected to vary among practitioners due to the use of different Phase I data sets. Accordingly, the typical measure of Phase II control chart performance, the average run length (ARL), becomes a random variable. In the literature, control charts with estimated parameters were assessed and the appropriate amounts o...

multivariate control charts such as hotelling`s t^ 2 and x^ 2 are commonly used for monitoring several related quality characteristics. these control charts use correlation structure that exists between quality characteristics in an attempt to improve monitoring. the purpose of this article is to discuss some issues related to the g chart proposed by levinson et al. [9] for detecting shifts in ...

Monitoring the coefficient of variation (CV) is a successful approach to Statistical Process Control when the process mean and standard deviation are not constant. In recent years the CV has been investigated by many researchers as the monitored statistic for several control charts. Viewed under this perspective, this paper presents a new efficient method to monitor the CV by means of Run Rules...