A Practical Guide to Statistical Quality Improvement - Beauregard, Michael R.
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Présentation A Practical Guide To Statistical Quality Improvement Format Broché
- Livre Technologie
Biographie:
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Sommaire:
1 Fundamental Concepts of Total Quality Management.- 1.1 TQM-How Does It Work?.- 1.2 TQM Leaders.- 1.3 The Continuous Improvement Cycle.- 1.4 Quality-What Is It Anyway?.- 1.5 Quality Drives Productivity.- 1.6 From Product Control to Process Control.- 1.7 SPC-Why and How.- 1.8 Improving the Status Quo with Statistical Process Improvement.- 1.9 The Kaizen Mine.- 1.10 The Engineer as a Change Agent.- 2 The Basic Tools.- 2.1 Understanding Variation.- 2.2 Clarity with Flowcharts.- 2.3 Sampling.- 2.4 Data Collection Formats.- 2.5 The Power of Concentration Diagrams.- 2.6 Data Grouping: Cause and Effect Diagrams.- 2.7 Data Organization.- 2.8 Data Analysis-Measuring Variation.- 3 The Measurement System.- 3.1 The Measurement System as a Process.- 3.2 Units of Measure-Are They Adequate?.- 3.3 Components of Measurement Error.- 3.4 Level of Measurement Error.- 3.5 Measurement Consistency.- 3.6 Measurement Bias.- 3.7 Measuring Testing Variance.- 3.8 GR & R Studies-Nondestructive Tests.- 3.9 GR & R Studies-Destructive Tests.- 3.10 Signal to Noise Ratio.- 4 Statistical Process Control.- 4.1 Quality Improvement Cycles.- 4.2 Process Stability.- 4.3 Control Chart Background.- 4.4 In Control Versus In Specification.- 4.5 Process Capability.- 4.6 Control Charts for Variable Data.- 4.7 Control Charts for Attribute Data.- 4.8 Special Control Charting Techniques.- 4.9 Conformance (or Run) Charts and Precontrol Charts.- 4.10 CUSUM Charts.- 4.11 Process Targeting.- 5 Using the Tools.- 5.1 From SPC to SPI.- 5.2 Problem-Solving Techniques.- 5.3 Experimenting for Improvement.- 5.4 Tests of Significance.- 5.5 Randomized Designs.- 5.6 Factorial Experiments.- 5.7 Fractional Factorial Designs.- 5.8 Screening Experiments.- 5.9 Mixture Design Techniques.- 5.10 Response Surface Analysis.- 5.11 EVOP.- 5.12 Handling Missing Data.- 5.13 Preventive Measures.- 6 Applications.- 6.1 Overview.- 6.2 Customer Service.- 6.3 Materials Control.- 6.4 Maintenance.- 6.5 Marketing and Sales.- 6.6 Human Resources (Personnel).- 6.7 Purchasing.- 6.8 Quality Department.- 6.9 Safety and Environmental.- 6.10 Management.- Appendix A SPC.- A.1 Standard Deviation on the Normal Curve.- A.2 Process Capability Measures.- A.4 Control Chart Formulas.- A.5 Constants for Control Chart Formulas.- Appendix B Hypothesis Testing and Test Statistics.- B.1 Types of Hypothesis Testing.- B.2 Types of Tests of Significance.- B.7 Random Numbers Table.- Appendix C ANOVA Formats.- C.1 ANOVA Generic.- C.2 CRD ANOVA.- C.3 CRBD ANOVA.- C.4 Latin Square ANOVA.- C.5 Two-Factor Factorial ANOVA.- C.7 Newman-Keuls Method: Analysis of Means.- Appendix D Designed Experiments.- D.1 Latin Square Design Matrices.- D.2 Two-Level Factorial Designs.- D.6 Coefficients of Orthogonal Polynomials.- Appendix E DOE: Screening Designs.- E.1 Eight-Run Plackett-Burman Design.- E.2 Eight-Run Plackett-Burman Design Reflected and Replicated.- E.3 12-Run Plackett-Burman Design.- E.4 16-Run Plackett-Burman Design.- E.5 20-Run Plackett-Burman Design.- E.6 28-Run Plackett-Burman Design.- E.7 L4 Taguchi Design.- E.8 L8 Taguchi Design.- E.9 L12 Taguchi Design.- E.10 L16 Taguchi Design.- Appendix F Mixture Experiments.- F.1 Three-Component Simplex Design.- F.2 Four-Component Simplex Design.- F.3 Five-Component Simplex Design.- F.4 Simplex Screening Design Points.- F.5 Six-Component Simplex Screening Design.- Glossary of Symbols.- References.
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