Foreword |
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xv | |
Introduction |
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1 | (1) |
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1 | (1) |
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Conventions Used in This Book |
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2 | (1) |
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3 | (1) |
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How This Book Is Organized |
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3 | (1) |
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3 | (1) |
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Part II: Understanding and Enacting the Breakthrough Strategy (Dmaic) |
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4 | (1) |
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Part III: The Six Sigma Tool and Technology Landscape |
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4 | (1) |
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Part IV: The Part of Tens |
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4 | (1) |
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4 | (1) |
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5 | (2) |
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7 | (54) |
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9 | (18) |
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The Managerial Perspective |
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11 | (5) |
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Radical corporate success |
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12 | (1) |
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Bridge between science and leadership |
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12 | (1) |
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Management system orientation |
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13 | (3) |
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The Technical Perspective |
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16 | (11) |
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Product, service, and transactional quality |
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17 | (3) |
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The journey from one to many |
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20 | (2) |
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Watch out for the wiggie, bump, and jitter |
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22 | (1) |
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Why six and why sigma? (Putting the pieces together) |
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23 | (4) |
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Examing the Principles and Language of Six Sigma |
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27 | (14) |
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It All Begins with One Simple Equation: Y = f(X) + ε |
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27 | (2) |
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29 | (3) |
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29 | (1) |
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30 | (1) |
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Beware superstitious delusions (that is, correlation doesn't imply causation) |
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30 | (2) |
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32 | (4) |
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33 | (1) |
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Where does variation come from? |
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34 | (1) |
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Getting variation right is everything |
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35 | (1) |
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36 | (2) |
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36 | (1) |
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The answer begins with the data |
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37 | (1) |
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The bottom line on measurement |
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38 | (1) |
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38 | (3) |
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The ``vital few'' versus the ``trivial many'' |
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39 | (1) |
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40 | (1) |
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Pinpointing the Essentials of Six Sigma |
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41 | (20) |
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The Project Strategy: Dmaic |
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41 | (2) |
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43 | (3) |
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Thinking for breakthrough |
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43 | (1) |
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Processing for breakthrough |
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44 | (1) |
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Designing for breakthrough |
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44 | (1) |
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Managing for breakthrough |
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45 | (1) |
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The People: Who You Need to Know |
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46 | (9) |
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In Six Sigma, everyone's a leader |
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46 | (5) |
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Number-crunching karate: Black Belts and their brethren |
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51 | (3) |
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Bringing the team together |
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54 | (1) |
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The Lifecycle of a Six Sigma Initiative |
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55 | (6) |
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Initialize: Ready . . . Aim |
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55 | (1) |
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Deploy: Setting it all in motion |
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56 | (1) |
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Implement: Forging first successes |
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57 | (1) |
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Expand: Taking it everywhere |
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58 | (1) |
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Sustain: The self-healing culture |
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58 | (3) |
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Part II: Understanding and Enacting the Breakthrough Strategy (Dmaic) |
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61 | (180) |
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Finding the Pain --- Defining Projects |
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63 | (22) |
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64 | (2) |
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64 | (1) |
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The problem transformation |
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65 | (1) |
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65 | (1) |
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Your Needs, My Needs, What Are They? |
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66 | (19) |
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Aligning Six Sigma with strategy |
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67 | (2) |
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Using a business case writing tool for project identification |
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69 | (2) |
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Six Sigma project definition |
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71 | (4) |
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75 | (10) |
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85 | (38) |
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The 1, 2, 3s of Statistics |
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85 | (10) |
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86 | (1) |
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87 | (1) |
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What does it mean? Measures of variation location |
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88 | (3) |
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How much variation is there? |
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91 | (4) |
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The Long and Short of Variation |
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95 | (8) |
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96 | (3) |
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Shift happens: Long-term variation |
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99 | (2) |
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Be all you can be: Entitlement |
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101 | (2) |
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A Picture's Worth a Thousand Words |
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103 | (20) |
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Plotting and charting data |
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103 | (14) |
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Hindsight is 20/20: Behavior charts |
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117 | (6) |
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123 | (26) |
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Specifications: The Voice of the Customer |
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123 | (5) |
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How close is close enough? Or why specifications? |
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124 | (1) |
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124 | (1) |
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Do you do the Rumba? Creating realistic specifications |
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125 | (1) |
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Don't push that big red button! What happens when you exceed a specification |
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126 | (2) |
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Capability: Comparing the Voice of the Customer to the Voice of the Process |
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128 | (21) |
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128 | (5) |
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133 | (5) |
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Linking yield and defect rate |
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138 | (1) |
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138 | (6) |
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144 | (3) |
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Prescribing a capability improvement plan |
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147 | (2) |
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Separating the Wheat from the Chaff |
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149 | (20) |
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150 | (2) |
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Attribute or category data |
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150 | (1) |
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Continuous or variable data |
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151 | (1) |
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Avoiding Illusion: Measurement System Capability Analysis |
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152 | (9) |
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Sources of measurement system variation |
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154 | (2) |
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Measuring measurements: Measurement system analysis (MSA) |
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156 | (5) |
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161 | (2) |
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Let the data do the talking |
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162 | (1) |
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162 | (1) |
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163 | (6) |
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Go with what you have: Observational studies |
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163 | (2) |
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Digging in: Identifying potential sources of variation through graphical analysis |
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165 | (4) |
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Quantifying the Critical Few |
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169 | (26) |
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169 | (11) |
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Viva Las Vegas: The central limit theorem |
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170 | (1) |
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How sure are you? Confidence intervals |
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171 | (1) |
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Confidence intervals for means |
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172 | (4) |
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Confidence intervals for standard deviations |
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176 | (2) |
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Four out of five recommend: Confidence intervals for proportions |
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178 | (2) |
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Understanding Relationships |
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180 | (15) |
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180 | (3) |
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183 | (12) |
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195 | (22) |
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Why Experiment? The Improvement Power of Six Sigma Experiments |
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195 | (3) |
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What is an experiment, anyway? |
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195 | (1) |
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The purpose of Six Sigma experiments |
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196 | (1) |
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197 | (1) |
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The end game of Six Sigma experiments |
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197 | (1) |
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Look Before You Leap: Experimental Considerations |
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198 | (4) |
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Frankenstein should have planned |
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198 | (2) |
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Simple, sequential, and systematic is best |
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200 | (2) |
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202 | (14) |
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202 | (4) |
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206 | (1) |
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207 | (9) |
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You've Only Just Begun --- More Topics in Experimentation |
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216 | (1) |
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217 | (24) |
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The Need for Control Planning |
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217 | (4) |
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The process management summary |
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219 | (1) |
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219 | (2) |
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Statistical Process Control |
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221 | (1) |
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Monitoring the Process: Control Chart Basics |
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222 | (8) |
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Understanding control limits |
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223 | (3) |
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Using control charts to keep processes on track |
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226 | (1) |
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Using control charts to detect patterns, shifts, and drifts |
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227 | (2) |
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Collecting data for control charts |
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229 | (1) |
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Control Charts for Continuous Data |
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230 | (5) |
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Individuals and moving range chart (I -- MR) |
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232 | (2) |
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Averages and ranges chart (X -- R chart) |
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234 | (1) |
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Averages and standard deviation chart (X -- S) |
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235 | (1) |
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Control Charts for Attribute Data |
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235 | (4) |
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The p chart for attribute data |
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237 | (1) |
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The u chart for attribute data |
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238 | (1) |
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Poka-Yoke (Mistake-Proofing) |
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239 | (2) |
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Part III: The Six Sigma Tool and Technology Landscape |
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241 | (60) |
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Identifying Six Sigma Practitioner Tools |
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243 | (40) |
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The Practitioner's Toolkit |
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244 | (1) |
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Process Optimization Tools |
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245 | (22) |
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246 | (2) |
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What's critical? Look in the CT Tree |
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248 | (3) |
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251 | (5) |
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256 | (2) |
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Cause-and-effect (C&E) matrix |
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258 | (1) |
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259 | (1) |
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Fmea: Failure mode effects analysis |
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260 | (2) |
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Kiss and tell: Capability-complexity analysis |
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262 | (2) |
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264 | (1) |
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265 | (2) |
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Statistical Analysis Tools |
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267 | (11) |
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268 | (1) |
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A picture's worth a thousand . . . dollars |
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268 | (2) |
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270 | (1) |
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Analysis of variance: Anova |
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271 | (1) |
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271 | (1) |
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272 | (1) |
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How capable is your process? |
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273 | (2) |
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275 | (1) |
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275 | (1) |
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276 | (1) |
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Measurement systems analysis |
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276 | (2) |
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278 | (1) |
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278 | (5) |
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278 | (2) |
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280 | (3) |
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Mastering Six Sigma Manager Tools |
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283 | (18) |
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284 | (3) |
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285 | (1) |
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Types of management tools |
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286 | (1) |
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Through the Looking Glass |
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287 | (1) |
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288 | (7) |
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289 | (1) |
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290 | (1) |
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291 | (2) |
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Project planning and tracking |
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293 | (2) |
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295 | (3) |
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298 | (1) |
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299 | (2) |
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Part IV: The Part of Tens |
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301 | (18) |
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Ten Best Practices of Six Sigma |
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303 | (6) |
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303 | (1) |
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304 | (1) |
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304 | (1) |
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305 | (1) |
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305 | (1) |
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306 | (1) |
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Align Projects with Key Goals |
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306 | (1) |
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306 | (1) |
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307 | (1) |
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Unleash Everyone's Potential |
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307 | (2) |
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309 | (4) |
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309 | (1) |
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309 | (1) |
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310 | (1) |
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Focusing On Isolated Areas |
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310 | (1) |
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310 | (1) |
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311 | (1) |
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Blindly Believing Your Measurement System |
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311 | (1) |
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``Remind Me Again, Is It CLs or SLs?'' |
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312 | (1) |
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Exaggerated Opportunity Counts |
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312 | (1) |
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Not Leveraging Technology |
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312 | (1) |
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Ten Places to Go for Help |
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313 | (6) |
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313 | (1) |
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314 | (1) |
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Associations and Professional Societies |
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314 | (1) |
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314 | (1) |
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315 | (1) |
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316 | (1) |
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316 | (1) |
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317 | (1) |
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317 | (1) |
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318 | (1) |
Appendix: Glossary |
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319 | (10) |
Afterword |
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329 | (2) |
Index |
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331 | |