Univariate and Multivariate Statistical Process Control

Univariate and Multivariate Statistical Process Control
Author: Murat Caner Testik
Publisher: LAP Lambert Academic Publishing
Total Pages: 92
Release: 2010-10
Genre:
ISBN: 9783838311043

Univariate and multivariate quality control charts are important tools for process/product monitoring and improvement. This monograph offers the developments and analyses of univariate and multivariate control charts, which are based on a generalized likelihood ratio (GLR) approach. It is commonly assumed that a process fault may shift the mean of a monitored statistic persistently to an unknown but constant value. However, there are situations such that a mean change is not constant but time varying. Incorporating a priori knowledge of a fault signature, a univariate GLR control chart is investigated for monitoring fault signatures. The GLR methodology can also be used in developing multivariate process control charts. Here, the GLR methodology is used to unify the development of various multivariate extensions to the CUSUM control charts. In addition to the GLR control charts under a normal distribution model, another GLR control chart is also proposed for monitoring a non- homogenous Markovian queuing system.

Multivariate Statistical Process Control with Industrial Applications

Multivariate Statistical Process Control with Industrial Applications
Author: Robert L. Mason
Publisher: SIAM
Total Pages: 276
Release: 2002-01-01
Genre: Technology & Engineering
ISBN: 9780898718461

This applied, self-contained text provides detailed coverage of the practical aspects of multivariate statistical process control (MVSPC)based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. The authors, leading researchers in this area who have developed major software for this type of charting procedure, provide valuable insight into the T2 statistic. Intentionally including only a minimal amount of theory, they lead readers through the construction and monitoring phases of the T2 control statistic using numerous industrial examples taken primarily from the chemical and power industries. These examples are applied to the construction of historical data sets to serve as a point of reference for the control procedure and are also applied to the monitoring phase, where emphasis is placed on signal location and interpretation in terms of the process variables.

Multivariate Total Quality Control

Multivariate Total Quality Control
Author: Carlo Lauro
Publisher: Springer Science & Business Media
Total Pages: 247
Release: 2012-12-06
Genre: Business & Economics
ISBN: 3642487106

In the last decades, the production of goods and the offer of services have become quite complex activities mostly because of the markets globalisation, of the continuous push to the innovation and of the constant requests from more and more demanding markets. The main objective of a company system has become the achievement of the quality for the business management cycle. This cycle goes from the design (Plan) to the production (Do), from the control (Check) to the man agement (Action), as well as to the marketing and distribution. Nowadays, the Total Quality of the company system is evaluated, according to the ISO 9000 regulations, in terms of its capacity to adjust the design and the pro duction to the needs expressed (explicitly or implictly) by the final users of a product/service. In this process, the use of statistical techniques is essential not only in the classical approach of Quality Control of a product but also, and most importantly, in the Quality Design oriented to the satisfaction of customers. Thus, Total Quality refers to the global capacity of a company to fit its system to the real needs of its customers by designing products which are able to match the customers' taste and by implementing a statistical control of both the product and the Customer Satisfaction. In such a process of design and evaluation, several statistical variables are involved and with a different nature (numerical, categorical, ordinal).

Multivariate Statistical Process Control with Industrial Applications

Multivariate Statistical Process Control with Industrial Applications
Author: Robert L. Mason
Publisher: SIAM
Total Pages: 271
Release: 2002-01-01
Genre: Technology & Engineering
ISBN: 0898714966

Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.

Multivariate Quality Control

Multivariate Quality Control
Author: Camil Fuchs
Publisher: CRC Press
Total Pages: 224
Release: 1998-04-22
Genre: Business & Economics
ISBN: 148227373X

Provides a theoretical foundation as well as practical tools for the analysis of multivariate data, using case studies and MINITAB computer macros to illustrate basic and advanced quality control methods. This work offers an approach to quality control that relies on statistical tolerance regions, and discusses computer graphic analysis highlightin

Multivariate Statistical Process Control Charts

Multivariate Statistical Process Control Charts
Author: Sotiris Bersimis
Publisher:
Total Pages: 0
Release: 2007
Genre:
ISBN:

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.

Introduction to Statistical Process Control

Introduction to Statistical Process Control
Author: Peihua Qiu
Publisher: CRC Press
Total Pages: 520
Release: 2013-10-14
Genre: Business & Economics
ISBN: 1482220415

A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon

Multivariate Statistical Quality Control Using R

Multivariate Statistical Quality Control Using R
Author: Edgar Santos-Fernández
Publisher: Springer Science & Business Media
Total Pages: 134
Release: 2012-09-22
Genre: Computers
ISBN: 1461454530

​​​​​The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.