Douglas Montgomery's Introduction to Statistical Quality Control

Brenda S. Ramirez, Jose G. Ramirez

Description

Master Statistical Quality Control using JMP !

Using examples from the popular textbook by Douglas Montgomery, Introduction to Statistical Quality Control: A JMP Companion demonstrates the powerful Statistical Quality Control (SQC) tools found in JMP. Geared toward students and practitioners of SQC who are using these techniques to monitor and improve products and processes, this companion provides step-by-step instructions on how to use JMP to generate the output and solutions found in Montgomery’s book.

The authors combine their many years of experience as passionate practitioners of SQC and their expertise using JMP to highlight the recent advances in JMP’s Analyze menu, and in particular, Quality and Process.

Key JMP platforms include:

• Control Chart Builder
  
• CUSUM Control Chart
  
• Control Chart (XBar, IR, P, NP, C, U, UWMA, EWMA, CUSUM)
  
• Process Screening
  
• Process Capability
  
• Measurement System Analysis
  
• Time Series
  
• Multivariate Control Chart
  
• Multivariate and Principal Components
  
• Distribution

For anyone who wants to learn how to use JMP to more easily explore data using tools associated with Statistical Process Control, Process Capability Analysis, Measurement System Analysis, Advanced Statistical Process Control, and Process Health Assessment, this book is a must!

Sujets

• Statistical process control

Informations

• Publié par: SAS Institute
• Date de parution: 04 octobre 2018
• Nombre de lectures: 0
• EAN13: 9781635268232
• Langue: English
• Poids de l'ouvrage: 22 Mo

Extrait

The correct bibliographic citation for this manual is as follows: Ramirez, Brenda S., M.S., and Jose G., Ramirez, Ph.D. 2018. Douglas Montgomery s Introduction to Statistical Quality Control: A JMP Companion . Cary, NC: SAS Institute Inc.
Douglas Montgomery s Introduction to Statistical Quality Control: A JMP Companion
Copyright 2018, SAS Institute Inc., Cary, NC, USA
978-1-63526-022-9 (Hard copy) 978-1-63526-825-6 (Web PDF) 978-1-63526-823-2 (epub) 978-1-63526-824-9 (mobi)
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Contents
Foreword
About This Book
Acknowledgments

Chapter 1: Using This Book
Overview
Chapter Contents
Chapter Layout
JMP Software and JMP Tables
Typographical Conventions
Chapter 2: Overview of Statistical Quality Control Topics and JMP
Overview
Statistical Process Control
Measurement System Analysis
Process Health Assessment
Chapter 3: Control Charts for Variables
Overview
Variables Control Chart Review
JMP Variables Control Chart Platforms
Examples from ISQC Chapter 6
Statistical Insights
Chapter 4: Control Charts for Attributes
Overview
Attributes Control Chart Review
JMP Attributes Control Chart Platforms
Examples from ISQC Chapter 7
Statistical Insights
Chapter 5: Process and Measurement System Capability Analysis
Overview
Process and Measurement System Capability Analysis Review
JMP Process Capability and MSA Platforms
Examples from ISQC Chapter 8
Statistical Insights
Chapter 6: Process Health Assessment
Overview
Process Health Assessment Review
JMP Platforms for Process Health Assessments
Examples for Chapter 6
Statistical Insights
Chapter 7: Cumulative Sum and Exponentially Weighted Moving Average Control Charts
Overview
CUSUM and EWMA Control Chart Review
JMP Small Shift Detection Control Chart Platforms
Examples from ISQC Chapter 9
Statistical Insights
Chapter 8: Other Univariate Statistical Process Monitoring and Control Techniques
Overview
Special Topics Review
JMP Platforms for Monitoring Autocorrelated Processes
Examples from ISQC Chapter 10
Statistical Insights
Chapter 9: Multivariate Process Monitoring and Control
Overview
Multivariate Process Monitoring Review
JMP Multivariate Monitoring Platforms
Examples from ISQC Chapter 11
Statistical Insights
References
Foreword

Statistical Process Control or SPC has been called one of the greatest technological innovations of the 20 th century. I think this is because the techniques have a sound intuitive basis, are straightforward mathematically, and have broad applicability to a wide range of industrial and business environments, including but not limited to manufacturing, process development, product design, supply chain operations, financial operations, health care, logistics and distribution, and many other transactional and service operations. The application of SPC along with other techniques for quality and business improvement have led to significantly improved quality and reliability of many products and services and contributed in an important way to business success and economic development.
Two other innovations have also played a key role in the successful deployment of SPC and other quality improvement tools. These are the use of deployment frameworks, the most successful of which in my view is Six Sigma, and computer software. Because SPC can be very data-intensive appropriate software is essential to any successful application, and JMP is an outstanding package. It has all of the fundamental and advanced techniques that are necessary to a successful SPC implementation.
The authors have done an excellent job of demonstrating how the key ideas of SPC in my book, both basic Shewhart control charts, and more advanced techniques, can be implemented in JMP. The software package has a logical design and the authors provide detailed step-by-step help along with screen shots and output from JMP to guide the reader to successful use of the technology. In many places they also provide additional insights about the methodology or extensions of some of the basic ideas that are extremely useful to the practitioner. The authors have an extensive background in the application of these methods across a variety of industrial and business settings, and this comes through clearly in the writing. Some of their own innovations such as measures of process stability are included and thoroughly illustrated in the book.
I highly recommend this book. It is well-written, and provides clear, authoritative guidance on the implementation of SPC through the JMP software package. Even if you are an experienced JMP user you will find the book a rewarding and useful reference. For new users, the book is an invaluable aid that will quickly facilitate your successful use of the SPC toolkit.

Douglas C. Montgomery
Regents Professor of Industrial Engineering
ASU Foundation Professor of Engineering
Ira A. Fulton School of Engineering
Arizona State University, Tempe, AZ
About This Book
Why Statistical Quality Control?
What comes to mind when you think of statistical quality control (SQC)? The Encyclopedia Britannica defines this phrase as the use of statistical methods in the monitoring and maintaining of the quality of products and services. This definition is in line with our initial exposure to SQC during our college years, in classes like Statistical Process Control. These ideas continued to take shape when we studied for the American Society for Quality Certified Quality Engineering exam, which had us memorize numerous facts about different statistical quality tools. But it was not until we started using these tools and techniques in a real-world manufacturing environment that we truly understood their impact on improving products and processes.
Thirty years and several industries later, we have become great stewards of SQC techniques, and their use and application have become second nature. Therefore, when we were asked to author a companion book to Prof. Montgomery s Introduction to Statistical Quality Control (ISQC), we enthusiastically agreed. Like many, we were introduced to his work through his many books. They are among our favorites because they are very readable, practical, and relevant, not only to the industries that we have worked in but also to the engineers and scientists with whom we often interact. This is no coincidence since Professor Montgomery holds BS, MS, and PhD degrees, all in engineering, and has spent many years both as a professor of Industrial Engineering and Statistics at Arizona State University and as a practitioner collaborating with people in industry.
The synergy between engineering, science, and statistics is always found in Prof. Montgomery s teachings. Take ISQC, for example. This book provides applications for many of the common SPC techniques using data sources from well-known manufacturing and business processes. For example, the book educates the reader about XBar and Range charts using dimensional measurements from a Hard-Bake process, C charts are applied to nonconformities on a printed circuit board, and we interpret the results of an attribute gauge capability analysis to unde