Evaluating Statistical Methods Practiced in Two Important Areas of Quality Improvement

1998 ◽  
pp. 313-324
Author(s):  
Subir Ghosh ◽  
Luis A. Lopez
Keyword(s):  
Quality Improvement ◽  
Statistical Methods

scholarly journals Quality Control in Production Processes

2016 ◽  
Vol 19 (3) ◽  
pp. 77-83 ◽  
Author(s):  
Miroslav Prístavka ◽  
Martina Kotorová ◽  
Radovan Savov
Keyword(s):  
Quality Control ◽  
Quality Improvement ◽  
Quality Management ◽  
Statistical Methods ◽  
Developed Countries ◽  
Basic Knowledge ◽  
Root Cause ◽  
Production Processes ◽  
Basic Quality ◽  
Quality Tools

AbstractThe tools for quality management are used for quality improvement throughout the whole Europe and developed countries. Simple statistics are considered one of the most basic methods. The goal was to apply the simple statistical methods to practice and to solve problems by using them. Selected methods are used for processing the list of internal discrepancies within the organization, and for identification of the root cause of the problem and its appropriate solution. Seven basic quality tools are simple graphical tools, but very effective in solving problems related to quality. They are called essential because they are suitable for people with at least basic knowledge in statistics; therefore, they can be used to solve the vast majority of problems.

Introduction to Data Mining and its Applications to Manufacturing

2008 ◽  
pp. 146-168 ◽  
Author(s):  
Jose D. Montero
Keyword(s):  
Data Mining ◽  
Quality Improvement ◽  
Statistical Methods ◽  
Business Intelligence ◽  
Computational Intelligence ◽  
Data Warehousing ◽  
Great Promise ◽  
Main Stream ◽  
Manufacturing Companies ◽  
Using Data

This chapter provides a brief introduction to data mining, the data mining process, and its applications to manufacturing. Several examples are provided to illustrate how data mining, a key area of computational intelligence, offers a great promise to manufacturing companies. It also covers a brief overview of data warehousing as a strategic resource for quality improvement and as a major enabler for data mining applications. Although data mining has been used extensively in several industries, in manufacturing its use is more limited and new. The examples published in the literature of using data mining in manufacturing promise a bright future for a broader expansion of data mining and business intelligence in general into manufacturing. The author believes that data mining will become a main stream application in manufacturing and it will enhance the analytical capabilities in the organization beyond what is offered and used today from statistical methods.

Statistical Methods for Quality Improvement

1990 ◽  
Vol 22 (1) ◽  
pp. 79-80
Author(s):  
Lloyd S. Nelson
Keyword(s):  
Quality Improvement ◽  
Statistical Methods

Introduction to Data Mining and its Applications to Manufacturing

2011 ◽  
pp. 144-166
Author(s):  
Jose D. Montero
Keyword(s):  
Data Mining ◽  
Quality Improvement ◽  
Statistical Methods ◽  
Business Intelligence ◽  
Computational Intelligence ◽  
Data Warehousing ◽  
Great Promise ◽  
Main Stream ◽  
Manufacturing Companies ◽  
Using Data

This chapter provides a brief introduction to data mining, the data mining process, and its applications to manufacturing. Several examples are provided to illustrate how data mining, a key area of computational intelligence, offers a great promise to manufacturing companies. It also covers a brief overview of data warehousing as a strategic resource for quality improvement and as a major enabler for data mining applications. Although data mining has been used extensively in several industries, in manufacturing its use is more limited and new. The examples published in the literature of using data mining in manufacturing promise a bright future for a broader expansion of data mining and business intelligence in general into manufacturing. The author believes that data mining will become a main stream application in manufacturing and it will enhance the analytical capabilities in the organization beyond what is offered and used today from statistical methods.

Quality Improvement through Statistical Methods

Technometrics ◽  
1998 ◽  
Vol 40 (4) ◽  
pp. 358
Author(s):  
Eric R. Ziegel ◽  
Bovas Abraham
Keyword(s):  
Quality Improvement ◽  
Statistical Methods
Sign in / Sign up

Export Citation Format

Share Document