Multivariate Statistical Process Control Charts: An Overview

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial lest squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.quality control, process control, multivariate statistical process control, Hotelling's T-square, CUSUM, EWMA, PCA, PLS

Data Analytics and Managing Health and Medical Care

The purpose is to introduce the demand for the quality movement practice in problems associated with public health diagnostic testing and other health related problems We examine problems involving 1 Multivariate control charts which simultaneously monitor correlated variables 2 we explain why the scale on multivariate control charts is unrelated to the scale of the individual Variables control charts and 3 discover that out of control signals in multivariate charts do not reveal which variable or combination of variables causes the signal and application of quality monitoring New methods provide methods for MPC charts focus on the average run length as the decision factor We indicate that other decision criteria in multivariate control charts are availableand these methods can be useful in evaluating the design and implementation of multivariate charts in special circumstance

Process Control, the Bull Whip Effect and the Supply Chain

The purpose is to introduce the demand for statistical quality control practice in the supply chain environment. We show both the need and application of these measures, especially the need for multivariate quality concepts to reduce the costs of operating supply chains, to control the flow throughout the supply chain and in the dynamic behavior of supply chains to utilize concepts associated with multivariate methods and auto correlated variables. We note that the quality output is as important as the “bull whip” efficiency in the supply chain

The Quality Movement in the Supply Chain Environment

The purpose is to introduce the demand for the quality movement practice in the supply chain environment. We show both the need and application of these measures, especially the need for multivariate quality concepts to reduce the costs of operating supply chains, to control the flow throughout the supply chain. The purpose is to reduce costs in the supply chain system and improve the probability of meeting the “due time.

Method of lines and runge-kutta method in solving partial differential equation for heat equation

Solving the differential equation for Newton’s cooling law mostly consists of several fragments formed during a long time to solve the equation. However, the stiff type problems seem cannot be solved efficiently via some of these methods. This research will try to overcome such problems and compare results from two classes of numerical methods for heat equation problems. The heat or diffusion equation, an example of parabolic equations, is classified into Partial Differential Equations. Two classes of numerical methods which are Method of Lines and Runge-Kutta will be performed and discussed. The development, analysis and implementation have been made using the Matlab language, which the graphs exhibited to highlight the accuracy and efficiency of the numerical methods. From the solution of the equations, it showed that better accuracy is achieved through the new combined method by Method of Lines and Runge-Kutta method

The Quality Movement in Hospital Care

The purpose is to introduce the demand for the quality movement practice in hospital care. We show both the need and application of quality monitoring, especially the need monitoring activities having auto correlated data flows of which there are many in the hospital environment. The goal is to control the flow of quality care data in the dynamic behavior of these systems of acre in hospitals. These monitoring systems are designed to control and improve changes in the hospital care environment