A BUSINESSWEEK BESTSELLER Bestselling Lean Six Sigma author Michael George provides the first pocket guide for deployers of Lean Six Sigma The Lean Six Sigma Pocket Toolbook blends Lean and Six Sigma tools and concepts, providing expert advice on how to determine which tool within a family is best for different purposes. Packed with detailed examples and step-bystep instructions, it's the ideal handy reference guide to help Green and Black Belts make the transition from the classroom to the field. Features brief summaries and examples of the 70 most important tools in Lean Six Sigma, such as Pull, Heijunka, and Control Charts Groups tools by purpose and usage Offers a quick, easy reference on using the DMAIC improvement cycle Provides comprehensive coverage in a compact, portable format Provides the tools for implementing Lean Six Sigma - what they are, how they work, and which to use. This book presents the tools and concepts needed to understand, implement, and leverage Lean Six Sigma. It provides analyses of nearly 100 tools and methodologies - from DMAIC and Pull Systems to Control Charts and Pareto Charts. Chapter 1: Using DMAIC to Improve Speed, Quality, and Cost 1(26) Define 4(4) Measure 8(4) Analyze 12(2) Improve 14(3) Control 17(3) Kaizen DMAIC 20(6) Project selection 26(1) Chapter 2: Working With Ideas 27(6) Brainstorming 27(3) Affinity diagrams 30(1) Multivoting 31(2) Chapter 3: Value Stream Mapping and Process Flow Tools 33(1) Process mapping 34(2) Process observation 36(2) SIPOC 38(1) Process mapping steps 39(3) Transportation and spaghetti (workflow) diagrams 42(1) Swim-lane (deployment) flowcharts 43(2) Value stream maps (basic) 45(4) Flowchart and value stream symbols 49(1) Value-add (VA) vs. non-value-add (NVA) analysis 49(3) Time value maps 52(1) Value-add chart (task time or take time chart) 53(2) Chapter 4: Voice of the Customer (VOC) 55(14) Customer segmentation 56(2) Sources of customer data 58(1) Collecting VOC: Interviews 59(1) Collecting VOC: Point-of-use observation 60(1) Collecting VOC: Focus groups 61(1) Collecting VOC: Surveys 62(2) Kano analysis 64(3) Developing critical-to-quality requirements 67(2) Chapter 5: Data Collection 69(35) Types of data 70(1) Input vs. output data 71(1) Data collection planning 72(2) Measurement selection matrix 74(1) Stratification factors 75(1) Operational definitions 76(1) Cautions on using existing data 77(1) Making a checksheet 78(1) Basic checksheets 79(1) Frequency plot checksheet 80(1) Traveler checksheet 80(1) Location checksheet 81(1) Sampling basics 81(2) Factors in sample selection 83(1) Stable process (and population) sampling 84(1) Formulas for determining minimum sample size (population or stable process) 85(2) Measurement System Analysis (MSA) and Gage R&R Overview 87(1) Gage R&R: Collecting the data 88(2) Interpreting Gage R&R Results 90(6) MSA: Evaluating bias 96(1) MSA: Evaluating stability 97(2) MSA: Evaluating discrimination 99(1) MSA for attribute/discrete data 100(4) Chapter 6: Descriptive Statistics and Data Displays 104(13) Statistical term conventions 105(1) Measures of central tendency (mean, median, mode) 106(2) Measures of spread (range, variance, standard deviation) 108(2) Boxplots 110(1) Frequency plot (histogram) 111(3) Normal distribution 114(1) Non-normal distributions and the Central Limit Theorem 114(3) Chapter 7: Variation Analysis 117(24) Review of variation concepts 118(1) Time series plots (Run charts) 119(2) Run chart table 121(1) Control chart basics 122(1) Selecting a control chart 123(1) Control charts for continuous data 123(2) Subgrouping for continuous data 125(2) Control limit formulas for continuous data 127(1) Factors for Control Chart Formulas 128(1) Creating an ImR Chart 128(1) Creating X,R charts or X,S charts 129(1) Control charts for attribute data 130(2) Creating p-, np-, c-, and u-charts 132(1) Control limit formulas for attribute data 132(1) Assumptions for interpreting control charts 133(1) Interpreting control charts (Tests for Special Cause Variation) 133(2) Background on process capability calculations 135(2) Confusion in short-term vs. long-term process capability calculations 137(1) Calculating process capability 138(3) Chapter 8: Identifying and Verifying Causes 141(56) PART A: Identifying potential causes 141(8) Pareto charts 142(3) 5 Whys 145(1) Cause-and-effect diagrams (fishbone or Ishikawa diagrams) 146(2) C&E Matrix 148(1) PART B: Tools for confirming causal effects 149(48) Stratified data charts 150(2) Testing quick fixes or obvious solutions 152(2) Scatter plots 154(2) Hypothesis testing overview 156(1) Confidence intervals 157(1) Type I and Type II errors, Confidence, Power, and p-values 158(2) Confidence intervals and sample size 160(1) t-test Overview 161(1) 1-Sample t-test 162(1) 2-Sample t-test 163(2) Overview of correlation 165(1) Correlation statistics (coefficients) 166(1) Regression overview 167(1) Simple linear regression 168(1) Multiple regression 169(4) ANOVA (ANalysis Of VAriance) 173(1) One-way ANOVA 174(4) Degrees of Freedom 178(1) ANOVA assumptions 179(1) Two-way ANOVA 180(2) Chi-Square test 182(2) Design of Experiments (DOE) notation and terms 184(1) Planning a designed experiment 185(4) DOE: Full-factorial vs. Fractional-factorials (and notations) 189(3) Interpreting DOE results 192(3) Residual analysis in hypothesis testing 195(2) Chapter 9: Reducing Lead Time and Non-Value-Add Cost 197(44) Basic Lean concepts 199(2) Metrics of time efficiency 201(2) Time Traps vs. Capacity Constraints 203(1) Identifying Time Traps and Capacity Constraints 204(2) 5S Overview 206(1) Implementing 5S 207(6) Generic Pull System 213(3) Replenishment Pull Systems 216(3) Two-Bin Replenishment System 219(3) Computing minimum safe batch sizes 222(1) Four Step Rapid Setup Method 223(4) Adapting Four Step Rapid Setup for service processes 227(1) Total Productive Maintenance (TPM) 228(4) Mistake proofing & prevention (Poky yoke) 232(2) Process balancing design principles 234(1) Work cell optimization 235(2) Visual Process Controls 237(4) Chapter 10: Complexity Value Stream Mapping and Complexity Analysis 241(12) Product/service family grid 242(1) Complexity Value Stream Map (CVSM) 243(2) Process Cycle Efficiency (PCE) 245(1) The Complexity Equation 245(1) Complexity matrix 246(1) PCE destruction calculations (for a Complexity Matrix) 247(1) Substructure analysis 248(2) What-if' analyses with Complexity Matrix data 250(3) Chapter 11: Selecting and Testing Solutions 253(24) Sources of solution ideas 254(1) Benchmarking 254(1) Tips on solution selection 255(1) Developing and using evaluation criteria 256(2) Solution selection matrix 258(3) Pairwise ranking 261(3) Cost evaluation 264(1) Impact/effort matrix 264(1) Pugh matrix 265(4) Other evaluation techniques 269(1) Controls assessment matrix 269(1) Failure Modes and Effects Analysis (FMEA) 270(3) Pilot testing 273(4) Index 277