The exponentially weighted moving average (EWMA) control chart is a popular tool used to monitor and identify slight unnatural variations in the manufacturing, industrial, service processes. In general, charts operate under assumption of normality observation attention quality feature, but it not easy maintain this practice. such situations, data random processes are correlated data, as stock p...

Control limits in traditional Multivariate Quality Control Charts (MQCC), such as Hotelling's T control chart, Multivariate Cumulative Sum (MCUSUM) and Multivariate Exponentially-Weighted Moving Average (MEWMA) control charts are based on multivariate normal assumption. This assumption is not usually satisfied, especially in real life applications. The purpose of a control chart based on suppor...

The problem of quickest change detection with a wireless sensor node is studied in this paper. The sensor that is deployed to monitor the environment has limited energy constraint to the classical quickest change detection problem. We consider the “censoring” strategy at the sensor side, i.e., the sensor selectively sends its observations to the decision maker. The quickest change detection pro...

in many industrial and non-industrial applications the quality of a process or product is characterized by a relationship between a response variable and one or more explanatory variables. this relationship is referred to as profile. in the past decade, profile monitoring has been extensively studied under the normal response variable, but it has paid a little attention to the profile with the ...

In this paper, we study the quickest change detection with mismatched post-change models. A change point is the time instant at which the distribution of a random process changes. The objective of quickest change detection is to minimize the detection delay of an unknown change point under certain performance constraints, such as average run length (ARL) to false alarm or probability of false a...

AN OPTIMIZATION OF ON-LINE MONITORING OF SIMPLELINEAR AND POLYNOMIAL QUALITY FUNCTIONSbyGALAL M. ABDELLADecember 2011Advisor: Dr. Kai YangMajor: Industrial EngineeringDegree: Doctor of PhilosophyThis research aims to introduce a number of contributions for enhancingthe statistical performance of some of Phase II linear and polynomial profilemonitoring tec...

In statistical process control, the control charts are an effective tool to monitor process. When is examined based on exponential family distributed response variable along with a single explanatory variable, generalized linear model (GLM) provides better estimates and GLM-based preferred. This study designed propose using different link functions (i.e., logit, probit, c-log-log, cauchit) bina...

Development of an efficient process monitoring system has always received great attention. Previous studies revealed that the coefficient variation (CV) is important in ensuring quality, especially for a where its mean and variance are highly correlated. The fact almost all industrial involves minimum two or more related quality characteristics being monitored simultaneously, this paper incorpo...

Quick detection of an assignable cause is necessary for process accuracy with respect to the specifications. The aim this study monitor time and magnitude processes based on unit-interval data. To end, maximum exponentially weighted moving average (Max-EWMA) control chart simultaneous monitoring event proposed. be precise, beta unit gamma distributions are considered develop Max-EWMA chart. cha...

In some statistical process control applications, a relationship between a response variable and an explanatory variable referred to as profile characterize the quality of a process or product and should be monitored over time. Many researches have been done in this area but in most of them, the successive observations in different levels of the explanatory variables are assumed to be independe...