For freshman/sophomore level introductory courses in SPC (Statistical Process
Control), Statistical Quality Control or Quality Control found in two and
four-year college curriculums, and in industrial training programs.
This “mathematics-friendly” text introduces students to basic concepts and
applications of Statistical Process Control (SPC). Students get a solid
foundation in control charts—including setting scales, charting, interpreting,
and analyzing process capability. Problem-solving techniques are emphasized, and
all learning is linked to the implementation of SPC in the workplace.
Table of Contents：
1. Introduction to Quality Concepts and
Statistical Process Control.
What is Quality? Definitions of Quality. The
Need for SPC. Prevention Versus Detection. SPC Goals. The Basic Tools for SPC.
Statistical Process Control Techniques. Applying SPC to an Existing
Manufacturing Process. Designed Experiments. The Quality Toolbox.
Striving for Quality: Management's Problem and Management's Solution.
Management's Problem. Management's Dilemma.
Leadership by Management. Deming's Contribution to Quality. Deming's 14 Points
for Management. Deming's Seven Deadly Diseases. Crosby's Approach. A Comparison
of Deming's 14 Points and Crosby's 14 Steps. Which Way to Top Quality? Pitfalls
in the Quest for Quality. Total Quality Management (TQM). The Malcolm Baldrige
National Quality Award. Total Customer Satisfaction. ISO-9000. The Service
3. Introduction to Variation and Statistics.
Measurement Concepts. Special-Cause and
Common-Cause Variation. The Variation Concepts. Distributions and SPC Goals.
Basic Statistical Concepts. Distributions and Three Standard Deviations.
4. Organization of Data: Introduction to
Tables, Charts, and Graphs.
Stemplots. Frequency Distributions and Tally
Charts. Histograms. Pareto Charts. Flowcharts. Storyboards. The Cause-and-Effect
Diagrams. Checksheets. Scatterplots.
5. Introduction to Probability
and the Normal Probability Distribution.
Probability. Compound Probability. Counting with
Permutations and Combinations. The Binomial Distribution. The Hypergeometric
Distribution. Probability Distributions. The Normal Probability Distribution.
The Application of the Central Limit Theorem.
6. Introduction to
heControl Chart Concept. Preparation for Control
Charting. Control Charts and Run Charts. The Basic x–bar and R Charts.
The x–bar and R Chart Procedure. The Continuation Control Chart. The
Capability Analysis. Six-Sigma.
7. Additional Control Charts for
The Median and Range Chart (x–bar and R).
x–bar and s Charts. Coding Data. A Modified x–bar and R Chart for
Small Sets of Data. The Nominal x–bar and R Chart. The Transformation
x–bar and R Chart. Control Chart Selection.
8. Variables Charts
for Limited Data.
Precontrol or Rainbow Charts. A Compound
Probability Application. Modified Precontrol for Tight Control. Charts for
9. Attributes Control Charts.
The Four Types of Attributes Charts. The p
Chart. The np Chart. The c Chart. The u Chart. SPC Applied to the Learning
Process. Technology in SPC.
10. Interpreting Control Charts.
The Random Distribution of Points. Freaks.
Binomial Distribution Applications. Freak Patterns. Shifts. Runs and Trends.
Time and Control Chart Patterns. Cycles. Grouping. Instability. Stable Mixtures.
Stratification. Using Control Chart Patterns in Problem Solving.
The Problem-Solving Sequence. Teamwork for
Problem Solving. Brainstorming. Using Problem-Solving Tools. Mistake Proofing.
Problem Solving in Management. JIT (Just-in-time). Problem Solving in the
12. Gauge Capability.
Preparations for a Gauge Capability Study. The
Gauge Capability Procedure. Analysis of R and R with Accuracy and Stability:
Maximum Possible Deflection. The Elimination of Gauge Variation From Process
Variation. Indecisive Gauge Readings.
13. Acceptance Sampling.
The Sampling Dilemma. Random Sampling. Operating
Characteristic Curves. The Average Outgoing Quality Curve. MLT-STD-105D for
Inspection by Attributes. The Average Proportion Defective. Vendor Certification
and Control Chart Monitoring.
Appendix A: Basic Math Concepts.
Signed Numbers. Variables. Order of Operations.
Inequalities. Using the Statistical Calculator.
Appendix B: Charts and Tables.
Formulas and Constants for Control Charts. The G
Chart. The Normal Distribution Table (Tail Area). The Normal Distribution Table
(Center Area). The Normal Distribution Table (Left Area). Process
Appendix C: Glossary of Symbols.
D: Lab Exercises. Answers to Odd Exercises.