The design of control charts in statistical quality control addresses the optimal selection of the design parameters such as the sampling frequency and the control limits; and includes sensitivity analysis with respect to system parameters such as the various process parameters and the economic costs of sampling. The advent of more complicated control chart schemes has necessitated the use of M...

A multivariate control chart is proposed to detect changes in the process dispersion of multiple correlated quality characteristics. We focus on individual observations, where we monitor data vector-by-vector rather than (rational) subgroups. The developed by applying logarithm diagonal elements estimated covariance matrix. Then, this vector incorporated an exponentially weighted moving average...

This paper examines the ability of several models to generate optimal hedge ratios. Statistical models employed include univariate and multivariate GARCH models, and exponentially weighted and simple moving averages. The variances of the hedged portfolios derived using these hedge ratios are compared with those based on market expectations implied by the prices of traded options. One-month and ...

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 ...

This work presents an exponentially weighted moving average (EWMA)-based synthesised control scheme for a process with outliers. Based on experience, some processes occasionally have outliers. The use of traditional mean ( X ) and range (R) control charts (denoted as X=R) for monitoring process mean and variance leads to high-level false alarms. In this study, the fast-detection technique (EWMA...

In many count data sets, an item may have more than one defect that causes the item to be defective. The Poisson EWMA scheme cannot be used to monitor such defects. The geometric-Poisson exponentially weighted moving average (EWMA) chart has been shown to be an effective scheme to monitor the number of defects over time. In these applications, it is assumed that the process parameters are known...

Abstract This study aim to propose a moving average control chart explicit formula based on the Generalized Poisson distribution ( MA GP ) and compare performance of with that Shewhart C ). The run length ARL is used consider performance. results indicated superior for detecting small shifts. Practitioners will find this be accurate as well simple apply use.

Control charts have been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior and quality improvement. In particular, multivariate control charts have been effectively used when a process involves a number of correlated process variables. Most existing multivariate control charts were developed using the assumption of normally distributed pro...

The modified exponentially weighted moving-average (modified EWMA) control chart is an improvement on the traditional EWMA chart. Herein, we provide more details about using various values of additional design parameter for detecting small-to-moderate shifts in process mean autoregressive fractionally integrated (ARFI(p, d)) with exponential white noise running thereon. statistical performances...

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...