Design For Six Sigma Statistics
Inside the Book
Unique Features of This Book
- Step-by-step recipes for each tool
- Explanations of how to use common software applications (Microsoft Excel, MINITAB, or Crystal Ball) for each tool
- Tables and flowcharts to help select the most appropriate tool
- Confidence intervals presented with the estimators they support
- Examples from Six Sigma and DFSS applications
Table of Contents
- Chapter 1: Engineering in a Six Sigma Company
- Chapter 2: Visualizing Data
- Chapter 3: Describing Random Behavior
- Chapter 4: Estimating Population Properties
- Chapter 5: Assessing Measurement Systems
- Chapter 6: Measuring Process Capability
- Chapter 7: Detecting Changes
- Chapter 8: Detecting Changes in Discrete Data
- Chapter 9: Detecting Changes in Nonnormal Data
- Chapter 10: Conducting Efficient Experiments
- Chapter 11: Predicting the Variation Caused by Tolerances
59 Tools for Diagnosing and Solving Problems in DFSS Initiatives
- 1: Run chart
- 2: Scatter plot
- 3: IX,MR control chart
- 4: Dot graph
- 5: Boxplot
- 6: Histogram
- 7: Stem-and-leaf display
- 8: Isogram
- 9: Tukey mean-difference plot
- 10: Multi-vari plot
- 11: Laws of probability
- 12: Hypergeometric distribution
- 13: Binomial distribution
- 14: Poisson distribution
- 15: Normal distribution
- 16: Sample mean with confidence interval
- 17: Sample standard deviation with confidence interval
- 18: Rational subgrouping
- 19: Control charts for variables
- 20: Statistical tolerance intervals
- 21: Exponential distribution
- 22: Weibull distribution
- 23: Failure rate estimation with confidence interval
- 24: Binomial proportion estimation with confidence interval
- 25: Control charts for attributes
- 26: Poisson rate estimation with confidence interval
- 27: Variable Gage R&R study
- 28: Attribute agreement study
- 29: Attribute gage study
- 30: Control chart interpretation
- 31: Measures of potential capability with confidence intervals
- 32: Measures of actual capability with confidence intervals
- 33: Process capability study
- 34: DFSS scorecard
- 35: One-sample c2 test
- 36: F test
- 37: Bartlett's and Levene's tests
- 38: One-sample t test
- 39: Two-sample t test
- 40: Paired-sample t test
- 41: One-way analysis of variance
- 42: One-sample binomial proportion test
- 43: Two-sample binomial proportion test
- 44: One-sample Poisson rate test
- 45: c2 test of association
- 46: Fisher's one-sample sign test
- 47: Wilcoxon signed rank test
- 48: Tukey end-count test
- 49: Kruskal-Wallis test
- 50: Goodness of fit test
- 51: Box-Cox transformation
- 52: Johnson transformation
- 53: Two-level modeling experiments
- 54: Screening experiments
- 55: Central composite and Box-Behnken experiments
- 56: Worst-case analysis
- 57: Root-sum-square analysis
- 58: Monte Carlo analysis
- 59: Stochastic optimization