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First Course in Quality Engineering Integrating Statistical and Management Methods of Quality

ISBN-10: 0131472011
ISBN-13: 9780131472013
Edition: 2006
List price: $122.00
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Description: This volume contains virtually all the information an engineer would need to function as a quality engineer. The author covers management methods and statistical methods of quality in an integrative manner nbsp; unlike other books on the subject,  More...

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Book details

List price: $122.00
Copyright year: 2006
Publisher: Prentice Hall PTR
Publication date: 1/17/2006
Binding: Hardcover
Pages: 528
Size: 7.50" wide x 9.75" long x 1.00" tall
Weight: 1.980
Language: English

This volume contains virtually all the information an engineer would need to function as a quality engineer. The author covers management methods and statistical methods of quality in an integrative manner nbsp; unlike other books on the subject, which focus primarily on one of the two areas of quality. Illustrates the use of quality methods with many real world examples drawn from the authorrsquo;s consulting work. Helps students understand and solve real problems with mini projects throughout. Uses a reader-friendly writing style that makes material more approachable and encourages self-study. Covers the must-know fundamentals of probability and statistics in one chapter (Chapter 2). Makes extensive use of computer software to illustrate the use of computer in solving quality problems. A useful reference for engineers and technical personnel in industry wanting to learn the tools of quality; also for candidates preparing for the exams to qualify as a certified quality engineer (CQE) of the Am. Soc. Of Quality.

Introduction to Quality
A Historical Overview
A Note About "Quality Engineering"
Defining Quality
Product Quality vs. Service Quality
The Total Quality System
Total Quality Management
Economics of Quality
Quality, Productivity, and Competitive Position
Quality Costs
A Case Study in Quality Costs
Success Stories
Cadillac Motor Car Company (Winner of the 1990 MBNQA)
Boeing Airlift and Tanker Programs (Winner of the 1998 MBNQA)
Mini-Project 1.1
Mini-Project 1.2
Statistics for Quality
Variability in Populations
Some Definitions
Empirical Methods for Describing Populations
The Frequency Distribution
The Histogram
The Cumulative Frequency Distribution
Numerical Methods for Describing Populations
Calculating the Average and Standard Deviation
Other Graphical Methods
Stem-and-Leaf Diagram
Box-and-Whisker Plot
Other Numerical Measures
Measures of Location
Measures of Dispersion
Exercise in Empirical Methods
Mathematical Models for Describing Populations
Definition of Probability
Computing the Probability of an Event
Theorems on Probability
Counting the Sample Points in a Sample Space
Exercises in Probability
Probability Distributions
Random Variable
Probability Mass Function
Probability Density Function
The Cumulative Distribution Function
The Mean and Variance of a Distribution
Some Important Probability Distributions
The Binomial Distribution
The Poisson Distribution
The Normal Distribution
Distribution of the Sample Average X
The Central Limit Theorem
Exercise in Probability Distributions
Inference of Population Quality from a Sample
Confidence Intervals
CI for the [mu] of a Normal Population When [sigma] Is Known
Interpretation of CI
CI for [mu] When [sigma] Is Not Known
CI for [sigma superscript 2] of a Normal Population
Hypothesis Testing
Test Concerning the Mean [mu] of a Normal Population When [sigma] Is Known
Why Place the Claim Made About a Parameter in H[subscript 1]?
The Three Possible Alternate Hypotheses
Test Concerning the Mean [mu] of a Normal Population When [sigma] Is Not Known
Test for Difference of Two Means When [sigma]s Are Known
Tests for Normality
Use of the Normal Probability Plot
Normal Probability Plot on the Computer
A Goodness-of-Fit Test
The P Value
Exercises in Inference Methods
Mini-Project 2.1
Mini-Project 2.2
Quality in Design
Planning for Quality
The Product Creation Cycle
Product Planning
Finding Customer Needs
Quality Function Deployment
Reliability Fundamentals
Product Design
Parameter Design
Design of Experiments
Tolerance Design
Failure Mode and Effect Analysis
Concurrent Engineering
Process Design
The Process Flow Chart
Process Parameter Selection: Experiments
Floor Plan Layout
Process FMEA
Process Control Plan
Other Process Plans
Mini-Project 3.1
Mini-Project 3.2
Mini-Project 3.3
Quality in Production: Process Control-I
Process Control
The Control Charts
A Typical Control Chart
Measurement Control Charts
X- and R-Charts
A Few Notes About the X- and R-Charts
X- and S-Charts
Attribute Control Charts
The P-Chart
The C-Chart
Some Special Attribute Control Charts
The P-Chart with Varying Sample Size
The nP-Chart
The Percent Defectives Chart (100P-Chart)
The U-Chart
A Few Notes About the Attribute Control Charts
Summary of Control Charts
Implementing SPC on Processes
Process Capability
Capability of a Process with Measurable Output
Capability Indices C[subscript p] and C[subscript pk]
Capability of a Process with Attribute Output
Measurement System Analysis
Properties of Instruments
Measurement Standards
Evaluating an Instrument
Mini-Project 4.1
Mini-Project 4.2
Quality in Production: Process Control-II
Derivation of Limits
Limits for the X-Chart
Limits for the R-Chart
Limits for the P-Chart
Limits for the C-Chart
Operating Characteristics of Control Charts
Operating Characteristics of an X-Chart
OC Curve of an R-Chart
Average Run Length
OC Curve of a P-Chart
OC Curve of a C-Chart
Measurement Control Charts for Special Situations
X- and R-Charts When Standards for [mu] and/or [sigma] Are Given
Control Charts for Slow Processes
Control Chart for Individuals (X-Chart)
Moving Average and MR Charts
The Exponentially Weighted Moving Average Chart
Control Charts for Short Runs
The DNOM Chart
The Standardized DNOM Chart
Topics in Process Capability
The C[subscript pm] Index
Confidence Interval for Capability Indices
Motorola's 6[sigma] Capability
Topics in Design of Experiments
Analysis of Variance
The General 2[subscript k] Design
2[superscript 4] Design
Fractional Factorials: One-Half Fractions
Mini-Project 5.1
Mini-Project 5.2
Managing for Quality
Managing Human Resources
Importance of Human Resources
Quality Leadership
Customer Focus
Open Communications
Education and Training
Motivation Methods
Principles of Management
Strategic Planning for Quality
History of Planning
Making the Strategic Plan
Strategic Plan Deployment
Mini-Project 6.1
Quality in Procurement
Importance of Quality in Supplies
Establishing a Good Supplier Relationship
Essentials of a Good Supplier Relationship
Single vs. Multiple Suppliers
Choosing a Supplier
Certifying a Supplier
Specifying the Supplies Completely
Auditing the Supplier
Supply Chain Optimization
Using Statistical Sampling for Acceptance
The Need for Sampling Inspection
Single Sampling Plans for Attributes
The Operating Characteristic Curve
Designing an SSP
Double Sampling Plans for Attributes
Average Outgoing Quality Limit
Some Notes About Sampling Plans
Continuous Improvement of Quality
The Need for Continuous Improvement
The Problem-Solving Methodology
Deming's PDCA Cycle
Juran's Breakthrough Sequence
The Generic Problem-Solving Methodology
Quality Improvement Tools
Cause-and-Effect Diagram
Pareto Analysis
Control Charts
Scatter Plots
Regression Analysis
Correlation Analysis
Term Project 8.1
A System for Quality
The Systems Approach
Dr. Deming's System
Long-Term Planning
Cultural Change
Prevention Orientation
Quality in Procurement
Continuous Improvement
Training, Education, Empowerment, and Teamwork
Dr. Juran's System
Quality Planning
Quality Control
Quality Improvement
Dr. Feigenbaum's System
Baldrige Award Criteria
Strategic Planning
Customer and Market Focus
Measurement, Analysis, and Knowledge Management
Human Resource Focus
Process Management
Business Results
ISO 9000 Quality Management Systems
The ISO 9000-2000 Family of Standards
The Eight Quality Management Principles
Documentation in ISO 9000
ISO 9001-2000 Requirements
Quality Management System
Management Responsibility
Resource Management
Product Realization
Measurement, Analysis, and Improvement
The Six Sigma System
Six Themes of Six Sigma
The 6[sigma] Measure
The Three Strategies
The Two Improvement Processes
The Five-Step Road Map
The Organization for Six Sigma
Summary of Quality Management Systems
Mini-Project 9.1
Mini-Project 9.2
Statistical Tables
Answers to Selected Exercises

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