Statgraphics Centurion XV - Professional Edition
Six Sigma Tools
The STATGRAPHICS Professional edition tools for implementing Six Sigma include:
- Process Capability Analysis
- Statistical Process Control Charts
- Basic Statistical Methods
- Analysis of Variance and Regression Analysis
- Design of Experiments
- Life Data Analysis and Reliability
- Time Series Analysis and Forecasting
- Measurement Systems Analysis
- Six Sigma Quality Assessment
The general layout of the Six Sigma menu is:
Define
- Quality Function Deployment, Cost of Quality Trend Analysis, Cause-and-Effect Diagrams, Process Maps
Measure
- Scatterplots, Exploratory Plots, Time Sequence Plots, Gage Studies for Variables and Attributes, Sample Size Determination
Analyse
- One Variable Analysis, Capability Analysis for Variables, Capability Analysis for Attributes, Multivariate Capability Analysis, Distribution Fitting, Two Sample Comparisons, Multiple Sample, Comparisons, Comparison of Rates and Proportions, Outlier Identification, Multivariate Methods, Reliability and Life Data Analysis
Improve
- Regression Analysis for Measurement Data, Regression Analysis for Attribute Data, Life Data Regression, Analysis of Variance, Design of Experiments, Screening, Response Surface, and Mixture Designs, D-Optimal Designs, Inner and Outer Arrays, Designs for Categorical Variables, Multiple Response Optimisation
Control
- Phase II Control Charts, Multivariate Control Charts, Acceptance Sampling, Classification Methods
Forecast
- Descriptive Time Series Methods, Smoothing, Seasonal Decomposition, Forecasting
SnapStats
- One Sample Analysis, Two Sample Comparison, Paired Sample Comparison, Multiple Sample Comparison, Curve Fitting, Capability Assessment (Individuals), Capability Assessment (Grouped Data), Gage R&R, Automatic Forecasting
Tools
- Expression Evaluator, Six Sigma Calculator, Probability Distributions, Interpolation, Surface and Contour Plots, Custom Charts
If the quality of your products and services depends on the joint properties of multiple variables, you will also need the tools for Multivariate Six Sigma.
Multivariate Six Sigma is an extension of the traditional Six Sigma methodologies to deal with processes in which multiple response variables are measured and in which the quality of a product depends on the joint values of those variables or attributes. Rather than concentrating on each response variable separately using univariate methods, multivariate statistical methods are employed to explain the multiple responses as an integrated whole. In complex processes in which the variables exhibit strong correlations, misleading results can be obtained if the multiple responses are not considered together.
STATGRAPHICS contains a powerful set of procedures for implementing Multivariate Six Sigma. Among the tools provided are:
Multivariate Graphical Displays
- Includes tools such as radar plots, glyphs, matrix plots, draftsman and casement plots.
Multivariate Capability Analysis
- Estimates the joint probability that a set of variables will be within established specifications based on a multivariate normal distribution.
The StatAdvisor
- This procedure determines the percentage of items beyond a set of multivariate specification limits.
Multivariate Control Charts
- Plots a T-squared chart, control ellipse, or Multivariate EWMA control chart to detect variation attributable to special causes.
Neural Network Classifier
- Classifies observations into groups based upon the values of multiple response variables.
Multivariate Calibration
- Uses Partial Least Squares to analyse data in which there are more variables than observations.
Principal Components Analysis
- Derives linear combinations of multiple responses that describe the principal variation amongst multiple response variables.
Multiple Response Optimisation
- Provides a procedure for maximising the desirability of multiple responses after a designed experiment has been performed.
White Paper: Integrating STATGRAPHICS into a Six-Sigma Program
Comparison Chart: STATGRAPHICS and Minitab