SPC Demystified

This SPC training material by Quality America president Paul Keller explains how to use statistical process control (SPC) to enable data-driven decision making and gain a competitive advantage in the marketplace. Statistical Process Control Demystified is written in a step-by-step format and provides detailed instructions on how to collect and analyze process data to determine the suitability of a process in meeting requirements. Attribute and variable control charts are discussed. You'll also get details on process improvement and measurement systems analysis. Detailed examples, calculations, and statistical assumptions make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce key concepts.

• Complete instruction on interpretation of statistical control charts
• Learn how to overcome common errors in the use of SPC and general statistical analysis tools
• Understand sampling requirements and other fundamental assumptions
• See how regression analysis and designed experiments are used for process improvement
• Discover the methods for measurement systems analysis, including R&R studies
• Learn the limitations of some common continuous process improvement strategies

Sample Excerpts

Preface

Welcome to the exciting world of statistical process control! I am very pleased to write this book, as I have had passion for the subject for many years. I was first introduced to SPC over 25 years ago, as a graduate student intern at a leading computer products manufacturer. Although I had a bachelor's degree in engineering, and had worked for several years in industry, I had not been exposed to this particular type of statistical analysis. The manufacturing engineers I worked with had only limited experience, and together we persevered our way through implementing control charts on a key process. Along the way, we made what I later determined were several fundamental errors. We learned the hard way that our process suffered from issues that hadn't been discussed in our textbook examples.

I took these hard lessons back to graduate school and learned as much as I could on the techniques. I applied them myself as a quality director in a couple of manufacturing organizations. In the early 1990s, I had the chance to become the technical services director for a company that developed SPC software. In that capacity I oversaw the technical support group, working with customers as they implemented SPC in a wide variety of industries including healthcare, aviation, banking, insurance, chemical processing and manufacturing. Our customers had seemingly varied needs; in reality there were many common threads. As much as each industry felt theirs was unique, in fact they had much in common. As might be expected, the tools of SPC have application across many types of processes, with only subtle differences in use.

As I write these pages, I am now president and chief operating officer of the company. Over the past 20 years I have applied these tools internally to our key processes, to learn, improve, and predict the dynamics of our internal sales and support processes, as well as our marketing and product development efforts. SPC is an integral part of what we do, and how we remain competitive in a sometimes crowded market. It provides the fundamental backbone to our systems, to consistently meet the needs of a demanding yet appreciative audience of quality professionals. I am indebted to many of these clients, who over the years have shared their problems and experiences with me, through their technical support issues, sales inquiries or training sessions. I feel quite fortunate to have worked with so many professionals who work diligently to service their customers and seek the truth that only data can provide. I have tried to encapsulate as much of their collective experiences in this book as possible.

Examples are provided throughout this book from a wide variety of applications, including general service (or transactional) processes, healthcare process, chemical processing and manufacturing. The books' topics build on each other, so it is recommended to read each chapter in the order provided. There are a number of critical and fundamental concepts discussed in earlier chapters that are required for later chapters.

Calculations and statistical assumptions are provided as needed, with emphasis on chart application and interpretation. Examples are provided for each chart, which may be downloaded from the author's Web site at www.qualityamerica.com/downloads/SPCDemystified.htm. Given the commercial availability of inexpensive SPC software, students are expected to use statistical software to quickly calculate the statistics and draw the chart. A time-restricted license of an easy to use MS Excel add-on for SPC is available for free via the above link for users of this textbook. This commercially-available SPC software package has been confidently used by thousands of organizations worldwide to quickly perform SPC analysis.

This text may be used for training groups of SPC practitioners within an organization, or for self-study to master the tools and methodology of statistical process control.

I hope you enjoy it and have the opportunity to realize the full potential of these powerful tools.

Table of Contents

Chapter 1 Analyzing Process Data

Chapter Objectives

The Application of Statistics to Processes

A Process Defined

Population versus Process Statistics

Statistical Process Control Concepts

Requirements versus Control

Control Chart Interpretation

Reaction to Special Cause Variation

Interpretation Relative to Requirements

Summary

Quiz

Chapter 2 Data Collection

Chapter Objectives

Data Properties

Metrics

Business-Level Metrics

Operational and Process Metrics

Chart Selection

Sampling Requirements

Rational Subgroups

Subgroup Size Considerations

Frequency of Subgroup Collection

Number of Subgroups Needed

Summary

Quiz

Chapter 3 Determining Suitability to Requirements

Chapter Objectives

Overview

Capability Indices Assuming Normality of Process Data

Cp for Bilateral Specifications

Cpk Index for Bilateral or Unilateral Specifications

Interpretation

Estimating Process Variation

Errors in Estimating Process Capability

Identifying Non-Normality in Process Data

Capability Estimates for Non-Normal Processes

Process Performance Indices

Summary

Quiz

Chapter 4 Attribute Control Charts

Chapter Objectives

Description and Use

The p Chart

The Np Chart

The u chart

The c chart

Interpretation

Sampling Considerations

Summary

Quiz

Chapter 5 X Charts

Chapter Objectives

Chart Construction

Sigma Chart

Interpretation

Process Shift Example

Subgroup Formation Concerns

Multistream Processes

Autocorrelated Processes

Short Run Applications

Summary

Quiz

Chapter 6 Charts for Individuals Data

Chapter Objectives

Description and Use

Moving Average Charts

Exponentially Weighted Moving Average (EWMA) Charts

Process Capability and Distributional Assessment

Individual X Charts

Example X Chart Application in Asthma Care

Summary

Quiz

Chapter 7 Process Improvement

Chapter Objectives

Overview

Stratification

Regression Analysis

Residuals Analysis

Multiple Regression

Designed Experiments

Defining the Experiment

Analyzing Experimental Results

Summary

Quiz

Chapter 8 Measurement Systems Analysis

Chapter Objectives

Overview

Stability

Linearity

Repeatability & Reproducibility (R&R)

Range Method of R&R Analysis

Destructive Testing

ANOVA Method

Summary

Quiz

Questions and Examples from Practitioners

Final Exam

Answers to Quizzes & Final Exam

Appendix: Control Chart Constants

References