An Alternative Q Chart Incorporating A Robust Estimator Of Scale

In overcoming the shortcomings of the classical control charts in a short runs production, Quesenberry (1991 & 1995a – d) proposed Q charts for attributes and variables data. An approach to enhance the performance of a variable Q chart based on individual measurements using a robust estimator of scale is proposed. Monte carlo simulations are conducted to show that the proposed robust Q chart is superior to the present Q chart

A Modified \u3cem\u3eX̄\u3c/em\u3e Control Chart for Samples Drawn from Finite Populations

The X̄ chart works well under the assumption of random sampling from infinite populations. However, many process monitoring scenarios may consist of random sampling from finite populations. A modified X̄ chart is proposed in this article to solve the problems encountered by the standard X̄ chart when samples are drawn from finite populations

Modeling the Autonomic and Metabolic Effects of Obstructive Sleep Apnea: A Simulation Study

Long-term exposure to intermittent hypoxia and sleep fragmentation introduced by recurring obstructive sleep apnea (OSA) has been linked to subsequent cardiovascular disease and Type 2 diabetes. The underlying mechanisms remain unclear, but impairment of the normal interactions among the systems that regulate autonomic and metabolic function is likely involved. We have extended an existing integrative model of respiratory, cardiovascular, and sleep–wake state control, to incorporate a sub-model of glucose–insulin–fatty acid regulation. This computational model is capable of simulating the complex dynamics of cardiorespiratory control, chemoreflex and state-related control of breath-to-breath ventilation, state-related and chemoreflex control of upper airway potency, respiratory and circulatory mechanics, as well as the metabolic control of glucose–insulin dynamics and its interactions with the autonomic control. The interactions between autonomic and metabolic control include the circadian regulation of epinephrine secretion, epinephrine regulation on dynamic fluctuations in glucose and free-fatty acid in plasma, metabolic coupling among tissues and organs provided by insulin and epinephrine, as well as the effect of insulin on peripheral vascular sympathetic activity. These model simulations provide insight into the relative importance of the various mechanisms that determine the acute and chronic physiological effects of sleep-disordered breathing. The model can also be used to investigate the effects of a variety of interventions, such as different glucose clamps, the intravenous glucose tolerance test, and the application of continuous positive airway pressure on OSA subjects. As such, this model provides the foundation on which future efforts to simulate disease progression and the long-term effects of pharmacological intervention can be based

A Robust Exponentially Weighted Moving Average Control Chart for the Process Mean

To date, numerous extensions of the exponentially weighted moving average, EWMA charts have been made. A new robust EWMA chart for the process mean is proposed. It enables easier detection of outliers and increase sensitivity to other forms of out-of-control situation when outliers are present

An EWMA Control Chart for Monitoring the Mean of Skewed Populations Using Weighted Variance.

This paper discusses the use of weighted variance (wv) in setting up the limits of the exponentially weighted moving average (EWMA) chart for the monitoring of the mean of a process from a skewed population. This chart, called the WV-EWMA chart hereafter, reduces to the standard EWMA chart when the underlying distribution is symmetric

A Study On The Performances Of Mewma And Mcusum Charts For Skewed Distributions.

A multivariate chart, instead of separate univariate charts is used for a joint monitoring of several correlated variables

A Comparison Of The Performances Of Various Single Variable Charts.

Control charts are used for process monitoring and improvement in industries. Two charts are usually used in the monitoring of both the mean and variance separately

An Improved Multivariate Short Run Control Chart Based On The CUSUM Statistic

Short run control charting in necessary at the start-up of a process and at the initiation of a new process for which prior information is unavailable. Numerous univariate short run control charts have been introduced to overcome the problems faced by conventional charts in a short run environment. Most practical scenarios involve several related variables. the multivariate short run charts for individual measurements and subgrouped data were proposed so that a joint monitoring of several correlated variables can be made simultaneously in a short run environment (see[5]). This paper aims at improving the performance of the multivariate short run chart for individual measurements by using its statistics to construct a cumulative sum (CUSUM) chart