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Fundamentals of Quality Control and Improvement 5th edition [Kõva köide]

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(Auburn University)
  • Formaat: Hardback, 800 pages, kõrgus x laius x paksus: 10x10x10 mm, kaal: 454 g
  • Ilmumisaeg: 29-Jun-2021
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119692334
  • ISBN-13: 9781119692331
Teised raamatud teemal:
Fundamentals of Quality Control and Improvement 5th editionSuurem pilt
  • Formaat: Hardback, 800 pages, kõrgus x laius x paksus: 10x10x10 mm, kaal: 454 g
  • Ilmumisaeg: 29-Jun-2021
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119692334
  • ISBN-13: 9781119692331
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781119692331.html
Märksõnad:

The newest edition of an insightful and practical statistical approach to quality control and management

In the newly revised and thoroughly updated Fifth Edition of Fundamentals of Quality Control and Improvement, accomplished academic, consultant, and author Dr. Amitava Mitra delivers a comprehensive and quantitative approach to quality management techniques. The book demonstrates how to integrate statistical concepts with quality assurance methods, incorporating modern ideas, strategies, and philosophies of quality management.

You'll discover experimental design concepts and the use of the Taguchi method to incorporate customer needs, improve lead time, and reduce costs. The new edition also includes brand-new case studies at the end of several chapters, references to the statistical software Minitab 19, and chapter updates that add discussions of trending and exciting topics in quality control.

The book includes access to supplementary material for instructors consisting of a new instructor's solutions manual and PowerPoint slides, as well as access to data sets for all readers.

Readers will also benefit from the inclusion of:

  • A thorough introduction to the evolution of quality and definitions of quality, quality control, quality assurance, quality circles, and quality improvement teams
  • An exploration of customer needs and market share, as well as the benefits of quality control and the total quality system
  • Practical discussions of quality and reliability, quality improvement, product and service costing, and quality costs
  • A concise treatment of how to measure quality costs, the management of quality, and the interrelationship between quality and productivity

Perfect for upper-level undergraduate and graduate students in quality control and improvement, the Fifth Edition of Fundamentals of Quality Control and Improvement will also earn a place in the libraries of business students and those undertaking training programs in Six Sigma.

Preface xix
About the Companion Website xxiii
PART I PHILOSOPHY AND FUNDAMENTALS
1(150)
1 Introduction to Quality Control and the Total Quality System
3(44)
1-1 Introduction and
Chapter Objectives
3(1)
1-2 Evolution of Quality Control
4(3)
1-3 Quality
7(5)
Quality Characteristics
8(1)
Variables and Attributes
8(1)
Defects
9(1)
Standard or Specification
9(1)
Quality of Design
10(1)
Quality of Conformance
10(1)
Quality of Performance
11(1)
1-4 Quality Control
12(1)
Off-Line Quality Control
12(1)
Statistical Process Control
12(1)
Acceptance Sampling Plans
13(1)
1-5 Quality Assurance
13(1)
1-6 Quality Circles and Quality Improvement Teams
14(1)
1-7 Customer Needs and Market Share
15(1)
Kano Model
15(1)
1-8 Benefits of Quality Control and the Total Quality System
16(2)
Total Quality System
17(1)
1-9 Quality and Reliability
18(1)
1-10 Quality Improvement
18(1)
1-11 Product and Service Costing
19(4)
Activity-Based Costing
20(3)
1-12 Quality Costs
23(4)
Prevention Costs
23(1)
Appraisal Costs
23(1)
Internal Failure Costs
24(1)
External Failure Costs
24(1)
Hidden Failure Costs
24(1)
Quality Costs Data Requirements
24(2)
Process Cost Approach
26(1)
1-13 Measuring Quality Costs
27(4)
Impact of Quality Improvement on Quality Costs
29(2)
1-14 Management of Quality
31(3)
1-15 Quality and Productivity
34(3)
Effect on Cost
34(1)
Effect on Market
34(3)
1-16 Total Quality Environmental Management
37(10)
Green Supply Chain
39(1)
Summary
40(1)
Key Terms
41(1)
Exercises
41(5)
References
46(1)
2 Some Philosophies and Their Impact on Quality
47(42)
2-1 Introduction and
Chapter Objectives
47(1)
2-2 Service Industries and Their Characteristics
47(6)
Differences in the Manufacturing and Service Sectors
49(1)
Service Quality Characteristics
50(2)
Measuring Service Quality
52(1)
Techniques for Evaluating Service Quality
52(1)
2-3 Model for Service Quality
53(3)
2-4 W. Edwards Deming's Philosophy
56(19)
Extended Process
57(1)
Deming's 14 Points for Management
58(14)
Deming's Deadly Diseases
72(3)
2-5 Philip B. Crosby's Philosophy
75(3)
Four Absolutes of Quality Management
76(1)
14-Step Plan for Quality Improvement
76(2)
2-6 Joseph M. Juran's Philosophy
78(4)
Quality Trilogy Process
79(1)
Quality Planning
79(1)
Quality Control
80(1)
Quality Improvement
81(1)
2-7 The Three Philosophies Compared
82(7)
Definition of Quality
82(1)
Management Commitment
82(1)
Strategic Approach to a Quality System
83(1)
Measurement of Quality
83(1)
Never-Ending Process of Improvement
83(1)
Education and Training
83(1)
Eliminating the Causes of Problems
84(1)
Goal Setting
84(1)
Structural Plan
84(1)
Summary
85(1)
Key Terms
85(1)
Exercises
86(2)
References
88(1)
3 Quality Management: Practices, Tools, and Standards
89(62)
3-1 Introduction and
Chapter Objectives
89(1)
3-2 Management Practices
90(9)
Total Quality Management
90(2)
Vision and Quality Policy
92(2)
Balanced Scorecard
94(2)
Performance Standards
96(3)
3-3 Quality Function Deployment
99(7)
QFD Process
100(6)
3-4 Benchmarking and Performance Evaluation
106(9)
Benchmarking
107(3)
Quality Auditing
110(2)
Vendor Selection and Certification Programs
112(1)
Vendor Rating and Selection
112(3)
3-5 Health Care Analytics
115(9)
Health Care Analytics and Big Data
116(1)
Uniqueness of Health Care
116(5)
Challenges in Health Care Quality
121(3)
3-6 Tools for Continuous Quality Improvement
124(13)
Pareto Diagrams
124(1)
Flowcharts
124(2)
Cause-and-Effect Diagrams
126(1)
Scatterplots
126(1)
Multivariable Charts
127(2)
Matrix and Three-Dimensional Plots
129(2)
Failure Mode and Effects Criticality Analysis
131(6)
3-7 International Standards ISO 9000 and Other Derivatives
137(14)
Features of ISO 9000
137(1)
Other Industry Standards
138(1)
Case Study
139(4)
Summary
143(1)
Key Terms
144(1)
Exercises
145(4)
References
149(2)
PART II STATISTICAL FOUNDATIONS AND METHODS OF QUALITY IMPROVEMENT
151(134)
4 Fundamentals of Statistical Concepts and Techniques in Quality Control and Improvement
153(80)
4-1 Introduction and
Chapter Objectives
154(1)
4-2 Population and Sample
154(1)
4-3 Parameter and Statistic
154(1)
4-4 Probability
155(5)
Relative Frequency Definition of Probability
155(1)
Simple and Compound Events
155(1)
Complementary Events
156(1)
Additive Law
157(1)
Multiplicative Law
158(1)
Independence and Mutually Exclusive Events
158(2)
4-5 Descriptive Statistics: Describing Product or Process Characteristics
160(17)
Data Collection
160(2)
Measurement Scales
162(1)
Measures of Central Tendency
163(2)
Measures of Dispersion
165(5)
Measures of Skewness and Kurtosis
170(3)
Measures of Association
173(4)
4-6 Probability Distributions
177(16)
Cumulative Distribution Function
179(1)
Expected Value
179(1)
Discrete Distributions
180(4)
Continuous Distributions
184(9)
4-7 Inferential Statistics: Drawing Conclusions on Product and Process Quality
193(40)
Sampling Distributions
193(1)
Estimation of Product and Process Parameters
194(9)
Hypothesis Testing
203(13)
Summary
216(1)
Appendix: Approximations to Some Probability Distributions
216(1)
Binomial Approximation to the Hypergeometric
216(1)
Poisson Approximation to the Binomial
216(1)
Normal Approximation to the Binomial
217(1)
Normal Approximation to the Poisson
218(1)
Key Terms
219(1)
Exercises
220(12)
References
232(1)
5 Data Analyses and Sampling
233(52)
5-1 Introduction and
Chapter Objectives
233(1)
5-2 Empirical Distribution Plots
234(5)
Histograms
234(1)
Stem-and-Leaf Plots
235(1)
Box Plots
236(2)
Variations of the Basic Box Plot
238(1)
5-3 Randomness of a Sequence
239(2)
Run Chart
239(2)
5-4 Validating Distributional Assumptions
241(3)
Probability Plotting
241(3)
5-5 Transformations to Achieve Normality
244(4)
Some Common Transformations
244(1)
Power Transformations
244(1)
Johnson Transformation
245(3)
5-6 Analysis of Count Data
248(4)
Hypothesis Test on Cell Probabilities
248(1)
Contingency Tables
249(2)
Measures of Association
251(1)
5-7 Analysis of Customer Satisfaction Data
252(9)
Customer Needs and Their Level of Satisfaction
252(5)
Displaying Survey Results
257(2)
Analysis of Survey Results
259(2)
5-8 Concepts in Sampling
261(7)
Sampling Designs and Schemes
262(2)
Sample Size Determination
264(1)
Bound on the Error of Estimation and Associated Confidence Level
264(2)
Estimating the Difference of Two Population Means
266(1)
Estimating the Difference of Two Population Proportions
266(1)
Controlling the Type I Error, Type II Error, and Associated Parameter Shift
267(1)
5-9 Bayes Rule and Decision Making Based on Samples
268(4)
5-10 Deming's kp rule
272(13)
Critique of the kp Rule
273(1)
Summary
274(1)
Key Terms
275(1)
Exercises
276(7)
References
283(2)
PART III STATISTICAL PROCESS CONTROL
285(242)
6 Statistical Process Control Using Control Charts
287(24)
6-1 Introduction and
Chapter Objectives
287(2)
6-2 Causes of Variation
289(1)
Special Causes
289(1)
Common Causes
289(1)
6-3 Statistical Basis for Control Charts
289(12)
Basic Principles
289(2)
Selection of Control Limits
291(2)
Errors in Making Inferences from Control Charts
293(4)
Effect of Control Limits on Errors in Inference Making
297(1)
Warning Limits
298(1)
Effect of Sample Size on Control Limits
298(1)
Average Run Length
299(2)
6-4 Selection of Rational Samples
301(1)
Sample Size
301(1)
Frequency of Sampling
301(1)
6-5 Analysis of Patterns in Control Charts
302(4)
Some Rules for Identifying an Out-of-Control Process
302(2)
Interpretation of Plots
304(2)
Determination of Causes of Out-of-Control Points
306(1)
6-6 Maintenance of Control Charts
306(5)
Summary
307(1)
Key Terms
307(1)
Exercises
307(3)
References
310(1)
7 Control Charts for Variables
311(94)
7-1 Introduction and
Chapter Objectives
312(1)
7-2 Selection of Characteristics for Investigation
313(1)
7-3 Preliminary Decisions
314(1)
Selection of Rational Samples
314(1)
Sample Size
315(1)
Frequency of Sampling
315(1)
Choice of Measuring Instruments
315(1)
Design of Data Recording Forms
315(1)
7-4 Control Charts for the Mean and Range
315(18)
Development of the Charts
315(6)
Variable Sample Size
321(1)
Standardized Control Charts
321(1)
Control Limits for a Given Target or Standard
322(3)
Interpretation and Inferences from the Charts
325(2)
Control Chart Patterns and Corrective Actions
327(6)
7-5 Control Charts for the Mean and Standard Deviation
333(5)
No Given Standards
334(1)
Given Standard
335(3)
7-6 Control Charts for Individual Units
338(4)
No Given Standards
339(1)
Given Standard
340(2)
7-7 Control Charts for Short Production Runs
342(2)
X- and R-Charts for Short Production Runs
342(1)
Z-MR Chart
342(2)
7-8 Other Control Charts
344(19)
Cumulative Sum Control Chart for the Process Mean
344(1)
Tabular Method
345(3)
V-Mask Method
348(3)
Cumulative Sum for Monitoring Process Variability
351(1)
Moving-Average Control Chart
351(3)
Exponentially Weighted Moving-Average or Geometric Moving-Average Control Chart
354(3)
Modified Control Chart
357(4)
Acceptance Control Chart
361(2)
7-9 Risk-Adjusted Control Charts
363(7)
Risk-Adjusted Cumulative Sum (RACUSUM) Chart
364(1)
Risk-Adjusted Sequential Probability Ratio Test (RASPRT)
365(1)
Risk-Adjusted Exponentially Weighted Moving-Average (RAEWMA) Chart
366(1)
Variable Life-Adjusted Display (VLAD) Chart
367(3)
7-10 Multivariate Control Charts
370(35)
Controlling Several Related Quality Characteristics
370(3)
Hotelling's T2 Control Chart and Its Variations
373(1)
Phase 1 and Phase 2 Charts
374(2)
Usage and Interpretations
376(1)
Individual Observations with Unknown Process Parameters
377(1)
Generalized Variance Chart
378(6)
Case Study
384(4)
Summary
388(1)
Key Terms
389(1)
Exercises
390(13)
References
403(2)
8 Control Charts for Attributes
405(66)
8-1 Introduction and
Chapter Objectives
406(1)
8-2 Advantages and Disadvantages of Attribute Charts
406(2)
Advantages
406(1)
Disadvantages
407(1)
8-3 Preliminary Decisions
408(1)
8-4 Chart for Proportion Nonconforming: p-Chart
408(17)
Construction and Interpretation
409(7)
Variable Sample Size
416(4)
Risk-Adjusted p-Charts in Health Care
420(4)
Special Considerations for p-Charts
424(1)
8-5 Chart for Number of Nonconforming Items: np-Chart
425(2)
No Standard Given
425(1)
Standard Given
426(1)
8-6 Chart for Number of Nonconformities: c-Chart
427(6)
No Standard Given
428(1)
Standard Given
428(2)
Probability Limits
430(1)
Applications in Health Care When Nonoccurence of Nonconformities Are Not Observable
431(2)
8-7 Chart for Number of Nonconformities Per Unit: u-Chart
433(6)
Variable Sample Size and No Specified Standard
433(3)
Risk-Adjusted u-Charts in Health Care
436(3)
8-8 Chart for Demerits Per Unit: U-Chart
439(3)
Classification of Nonconformities
439(1)
Construction of a U-Chart
439(3)
8-9 Charts for Highly Conforming Processes
442(5)
Transformation to Normality
442(1)
Use of Exponential Distribution for Continuous Variables
442(1)
Use of Geometric Distribution for Discrete Variables
443(1)
Probability Limits
443(2)
Applications in Health Care of Low-Occurrence Nonconformities
445(2)
8-10 Operating Characteristic Curves for Attribute Control Charts
447(24)
Case Study
450(5)
Summary
455(1)
Key Terms
455(1)
Exercises
456(13)
References
469(2)
9 Process Capability Analysis
471(56)
9-1 Introduction and
Chapter Objectives
471(1)
9-2 Specification Limits and Control Limits
472(1)
9-3 Process Capability Analysis
473(2)
Process Capability
474(1)
9-4 Natural Tolerance Limits
475(1)
Statistical Tolerance Limits
476(1)
9-5 Specifications and Process Capability
476(3)
9-6 Process Capability Indices
479(19)
CP Index
479(1)
Upper and Lower Capability Indices
480(1)
CPT Index
481(2)
Capability Ratio
483(1)
Taguchi Capability Index, CPM
484(1)
CPMK Index
484(1)
Confidence Intervals and Hypothesis Testing on Capability Indices
485(1)
Comparison of Capability Indices
486(4)
Effect of Measurement Error on Capability Indices
490(2)
Gage Repeatability and Reproducibility
492(1)
Evaluation of Measurement Systems
493(1)
Metrics for Evaluation of Measurement Systems
493(1)
Preparation for a Gage Repeatability and Reproducibility Study
494(3)
CP Index and the Nonconformance Rate
497(1)
9-7 Process Capability Analysis Procedures
498(2)
Estimating Process Mean and Standard Deviation
498(2)
9-8 Capability Analysis for Nonnormal Distributions
500(2)
Identification of Appropriate Distribution
500(1)
Box-Cox Transformation
500(1)
Using Attribute Charts
500(1)
Using a Nonparametric Approach
501(1)
9-9 Setting Tolerances on Assemblies and Components
502(7)
Tolerances on Assemblies and Subassemblies
502(2)
Tolerance Limits on Individual Components
504(1)
Tolerance on Mating Parts
505(3)
Nonlinear Combinations of Random Variables
508(1)
9-10 Estimating Statistical Tolerance Limits of a Process
509(18)
Statistical Tolerance Limits Based on Normal Distribution
509(1)
Nonparametric Statistical Tolerance Limits
510(1)
Case Study
511(4)
Summary
515(1)
Key Terms
516(1)
Exercises
516(9)
References
525(2)
PART IV PRODUCT AND PROCESS DESIGN
527(206)
10 Reliability
529(40)
10-1 Introduction and
Chapter Objectives
529(1)
10-2 Reliability
530(1)
10-3 Life-Cycle Curve and Probability Distributions in Modeling Reliability
530(4)
Probability Distributions to Model Failure Rate
531(3)
Availability
534(1)
10-4 System Reliability
534(8)
Systems with Components in Series
535(2)
Systems with Components in Parallel
537(2)
Systems with Components in Series and in Parallel
539(1)
Systems with Standby Components
540(2)
10-5 Operating Characteristic Curves
542(2)
10-6 Reliability and Life Testing Plans
544(8)
Types of Tests
544(2)
Life Testing Plans Using the Exponential Distribution
546(2)
Standard Life Testing Plans Using Handbook H-108
548(4)
10-7 Survival Analysis
552(17)
Estimation of the Survival Function
552(5)
Confidence Intervals for the Survival Function
557(2)
Comparion of Survival Functions of Two Groups
559(4)
Summary
563(1)
Key Terms
563(1)
Exercises
564(3)
References
567(2)
11 Experimental Design and the Taguchi Method
569(106)
11-1 Introduction and
Chapter Objectives
570(1)
11-2 Experimental Design Fundamentals
570(5)
Features of Experimentation
574(1)
11-3 Some Experimental Designs
575(20)
Completely Randomized Design
576(6)
Randomized Block Design
582(5)
Latin Square Design
587(8)
11-4 Factorial Experiments
595(28)
Two-Factor Factorial Experiment Using a Completely Randomized Design
596(4)
Two-Factor Factorial Experiment Using a Randomized Block Design
600(6)
Role of Contrasts
606(6)
The 2k Factorial Experiment
612(4)
Confounding in 2k Factorial Experiments
616(1)
Fractional Replication in 2k Experiments
617(6)
11-5 The Taguchi Method
623(1)
11-6 The Taguchi Philosophy
624(3)
11-7 Loss Functions
627(7)
Target Is Best
628(3)
Smaller Is Better
631(1)
Larger Is Better
632(2)
11-8 Signal-to-Noise Ratio and Performance Measures
634(3)
Target Is Best
634(3)
Smaller Is Better
637(1)
Larger Is Better
637(1)
11-9 Critique of S/N Ratios
637(1)
11-10 Experimental Design in the Taguchi Method
638(16)
Orthogonal Arrays and Linear Graphs
639(10)
Estimation of Effects
649(5)
11-11 Parameter Design in the Taguchi Method
654(4)
Application to Attribute Data
656(2)
11-12 Critique of Experimental Design and the Taguchi Method
658(17)
Summary
660(1)
Key Terms
661(1)
Exercises
662(10)
References
672(3)
12 Process Modeling Through Regression Analysis
675(58)
12-1 Introduction and
Chapter Objectives
675(1)
12-2 Deterministic and Probabilistic Models
676(2)
12-3 Model Assumptions
678(2)
12-4 Least Squares Method for Parameter Estimation
680(6)
Performance Measures of a Regression Model
683(3)
12-5 Model Validation and Remedial Measures
686(4)
Linearity of Regression Function
686(1)
Constancy of Error Variance
687(2)
Normality of Error Component
689(1)
Independence of Error Components
689(1)
12-6 Estimation and Inferences from a Regression Model
690(6)
Inferences on Individual βi Parameters
691(1)
Inferences on All βi, i = 1, 2, ..., p -- 1 Parameters
691(1)
Simultaneous Inferences on Some βi, i = 1, 2, ..., p -- 1
691(1)
Hypothesis Tests on a Subset of βi Parameters
692(1)
Estimation of Mean Response
692(1)
Simultaneous Confidence Intervals for Several Mean Responses
693(1)
Prediction of Individual Observations
693(1)
Simultaneous Prediction Intervals for Several New Observations
693(3)
12-7 Qualitative Independent Variables
696(6)
Additive Model
696(1)
Interaction Model
697(5)
12-8 Issues in Multiple Regression
702(5)
Data from a Retrospective Versus Designed Experiment
702(1)
Outliers in the Space of the Independent Variables
703(1)
Outliers for the Dependent Variable
704(1)
Influential Observations
705(1)
Multicollinearity
706(1)
Detection of Multicollinearity
706(1)
Effects of Multicollinearity
707(1)
12-9 Logistic Regression
707(12)
Binary Response Variable
708(1)
Assumptions in Regression
709(3)
Nominal Polytomous Response Variable
712(3)
Ordinal Polytomous Response Variable
715(4)
12-10 Classification Problems
719(14)
Performance Measures in Classification Problems
720(2)
Tests of Association in 2 × 2 Contingency Tables
722(1)
Receiver Operating Characteristic Curve
723(2)
Summary
725(1)
Key Terms
725(1)
Exercises
726(6)
References
732(1)
Appendixes
733(22)
A-1 Cumulative Binomial Distribution
733(5)
A-2 Cumulative Poisson Distribution
738(2)
A-3 Cumulative Standard Normal Distribution
740(3)
A-4 Values of t for a Specified Right-Tail Area
743(2)
A-5 Chi-Squared Values for a Specified Right-Tail Area
745(2)
A-6 Values of F for a Specified Right-Tail Area
747(6)
A-7 Factors for Computing Centerline and Three-Sigma Control Limits
753(1)
A-8 Uniform Random Numbers
754(1)
Index 755
Amitava Mitra, PhD, is Professor in the Department of Systems and Technology and the former Associate Dean in the College of Business at Auburn University, Alabama. He has published over 70 journal articles and teaches quality assurance and improvement.