This course is designed for professionals who use quality control or SPC methods to monitor, evaluate, and improve the quality of their processes. It is an ideal statistical training module to complement or supplement corporate quality training programs and Six Sigma programs.

Learn how to use SAS/QC software to

• perform distribution and Pareto analyses
• create run charts and determine rational subgrouping strategies
• create Shewhart control charts, including specialized and advanced charts
• perform analysis of means (ANOM) and create ANOM charts
• perform graphical and statistical capability analysis.

Who should attend

Engineers, chemists, health care workers, statisticians, and others who use quality control or SPC methods in their work

Formats available	Standard Duration
Classroom:	2.0 days
Live Web Classroom:	4 half-day session(s)	System Requirements

Before attending this course, you should have

• completed SAS® Programming Introduction: Basic Concepts or SAS® Programming 1: Essentials or have equivalent knowledge
• an understanding of basic statistical concepts such as normal distribution, p-values, and ANOVA. You can gain this understanding by completing the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course.

This course addresses SAS/GRAPH, SAS/QC, SAS/STAT software.

Introduction to Statistical Process Control Techniques

• understand the terminology of statistical quality control
• differentiate between traditional SAS graphics and ODS graphics
• introduce graphical tools for distribution analysis
• apply rational sampling and subgrouping in process monitoring
• generate Pareto charts

Shewhart Control Charts

• explain goals of control charting
• differentiate between sigma limits and probability limits
• use the SHEWHART procedure to generate control charts
• differentiate between using the range and using the standard deviation to estimate sigma
• automate generation of control charts
• create e-mail notifications of out-of-control processes
• distinguish between binomial and Poisson data

Advanced Topics for Shewhart Control Charts

• understand autocorrelation in process data
• use ARIMA models to generate a control chart for autocorrelated data
• identify and describe multivariate process situations
• generate multivariate control charts with appropriate control limits
• identify situations where multiple sources of variation may be present
• generate control charts appropriate for multiple sources of variation

Analysis of Means

• compare and contrast analysis of means (ANOM) with analysis of variance and Shewhart charts
• identify the three types of ANOM charts available in the ANOM procedure
• create an ANOM chart for measurement data using multiple responses
• create ANOM charts for pre-summarized attribute data

Capability Analysis

• compare and contrast control limits and specification limits
• define capability and understand when to perform capability analyses
• introduce and demonstrate graphical capability tools available in SAS
• generate and interpret capability indices and confidence intervals
• generate and interpret other statistical capability indicators, such as percent nonconforming
• discuss the issue of subgrouping in calculating capability ratios
• calculate an alternative capability measure based on the quadratic Taguchi Loss Function