Managing, Controlling, and Improving Quality, 1st Edition
April 2010, ©2011
This book presents an organized approach to quality management, control, and improvement. Quality problems usually are the outcome of uncontrolled or excessive variability in product or service characteristics that are critical to the customer and statistical tools and other analytical methods play an important role in solving these problems. However, these techniques need to be implemented within a management structure that will ensure success. We focus on both the management structure and the statistical and analytical tools. Our approach to organizing and presenting this material is based on many years of teaching, research, and professional practice across a wide range of business and industrial settings.
1.1 The Meaning of Quality and Quality Improvement.
1.2 A Brief History of Quality Control and Improvement.
1.3 Statistical Methods for Quality Control and Improvement.
1.4 Quality and Productivity.
1.5 Quality Costs.
1.6 Legal Aspects of quality.
1.7 Implementing Quality Improvement.
Chapter 2. Management Aspects of Quality.
2.2 Quality Philosophy and Management Strategies.
2.3 The DMAIC Process.
Chapter 3. Tools and Techniques for Quality Control and Improvement.
3.2 Chance and Assignable Causes of Quality Variation.
3.3 The Control Chart.
3.4 The Rest of the Magnificent Seven.
3.5 Implementing SPC in a Quality Improvement Program.
3.6 An Application of SPC.
3.7 Applications of Quality Process and Quality Improvement Tools in Transactional
and Service Businesses.
Chapter 4. Statistical Inference about Product and Process Quality.
4.1 Describing Variation.
4.2 Probability Distributions.
4.3 The Normal Distribution.
4.4 Statistical Inference.
4.5 Statistical Inference for a Single Sample.
4.6 Statistical Inference for Two
Chapter 5. Control Charts for Variables.
5.2 and R x Charts.
5.3 and S Charts.
5.4 Shewart Control Chart for Individual Measurements.
5.5 Summary of Procedures for , R, S, and Individuals Charts.
5.6 Example Applications of , R, S, and Individuals Charts.
5.7 Cumulative Sum Control Charts.
5.8 Exponentially Weighted Moving Average Control Charts.
5.9 Process Capability Analysis Using Control Charts.
Chapter 6. Control Charts for Attributes.
6.2 The Control Chart for Fraction Nonconforming.
6.3 Control Charts for Nonconformities (Defects).
6.4 Choice between Attributes and Variables Control Charts.
6.5 Guidelines for Implementing Control Charts.
Chapter 7. Lot-by-Lot Acceptance Sampling Procedures.
7.1 The Acceptance Sampling Problem.
7.2 Single-Sampling Plans for Attributes.
7.3 Double, Multiple, and Sequential Sampling.
7.4 Military Standard 105E (ANSI/ASQC Z1.4, ISO 2859).
7.5 The Dodge–Romig Sampling Plans.
7.6 Military Standard 414 (ANSI/ASQ Z1.9).
7.7 Chain Sampling.
7.8 Continuous Sampling.
7.9 Skip-Lot Sampling Plans.
Chapter 8. Process Design and Improvement with Designed Experiments.
8.1 What Is Experimental Design?
8.2 Examples of Designed Experiments in Process and Product Improvement.
8.3 Guidelines for Designing Experiments.
8.4 The Analysis of Variance.
8.5 Factorial Experiments.
8.6 The 2k Factorial Design.
8.7 Fractional Replication of the 2k Design.
8.8 Response Surface Methods.
8.9 Robust Product and Process Design.
Chapter 9. Reliability.
9.1 Basic Concepts of Reliability.
9.2 Life Distributions.
9.3 Instantaneous Failure Rate.
9.4 Life Cycle Reliability.
9.5 Determining System Reliability from Component Reliabilities.
9.6 Life Testing and Reliability Estimation.
9.7 Availability and Maintainability.
9.8 Failure Mode and Effects Analysis.
A. I Summary of Common Probability Distribution Cities Used in Quality Control and Improvement.
A. II Cumulative Standard Normal Distribution.
A. III Percentage Points of the Distribution.
A. IV Percentage Points of the t Distribution.
A. V Percentage Points of the F Distribution.
A. VI Factors for Constructing Variables Control Charts.
Answers to Selected Exercises.
· Accessible presentation: Algebra-based, uncomplicated equations, and each topic is explained effectively. Example problems and thorough solutions help students who are new to the topic. Accessible to students in business and technology curricula, but rigorous enough for engineering students.
· Mini-Cases at the beginning of each chapter help motivate student interest and understanding of the importance and value of quality management tools and techniques.
· Software implementation: Both Minitab and SPC XL are used within the book to demonstrate modern software implementation of statistical methods in quality control and improvement. Samples of output and tips for using the software are included.
· Examples and exercises demonstrate a broad range of applications, and are presented at a diverse level to allow students to start at a level accessible to them, making it possible to build upon their skills with further problems.
· Conversational tone appeals to students.
· Appropriate depth and breadth of coverage: The subject of quality management and control is covered in depth.
· Six sigma and DMAIC: Presents in detail six sigma and the define, measure, analyze, improve, and control (DMAIC) process for quality improvement and implementation.
· Designed experiments: Demonstrates the value of designed experiments as a quality improvement tool.
· Workplace implementation is addressed.
—Dr. Byung Rae Choe, Indiana University of Pennsylvania