Process Control and Capability

This 4-day track provides participants with a comprehensive toolkit for understanding and applying SPC. The track covers the data analysis techniques necessary to validate if a measurement system is reliable, plus teaches how to determine if a process is stable and how to quantify if a process is capable of meeting customer specifications.

Participants will learn how to understand and apply SPC by covering the data analysis techniques necessary to validate if a measurement system is reliable, determine if a process is stable, and quantify if a process is capable of meeting customer specifications. Analytical and statistical principles will be presented through real-world case studies, examples, and exercises.

 

This course is most appropriate for QA managers, CQI coordinators, process engineers, and other quality professionals who need to understand SPC and how each of the tools are integrated into successful manufacturing processes.

Learning Track

DAYS 1-2

In this 2-day foundational course you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling graphs, and export results. Analyze a variety of real world data sets to learn how to align your applications with the right statistical tool, and interpret statistical output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important statistical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.

This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly found in manufacturing, engineering, and research and development endeavors.

Topics Include:

Importing and Formatting Data
Bar Charts
Histograms
Boxplots
Pareto Charts
Scatterplots
Tables and Chi-Square Analysis
Measures of Location and Variation

t-Tests
Proportion Tests
Tests for Equal Variance
Power and Sample Size
Correlation
Simple Linear and Multiple Regression
One-Way ANOVA
Multi-Variable ANOVA

Summary Report for SupplrA
Interaction Plot for PntWear - Data Means

DAY 3

Develop the necessary skills to successfully evaluate and certify manufacturing and engineering measurement systems. Learn the basic fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control manufacturing processes. Develop the skills to know when and where to use the various types of control charts available in Minitab for your own processes.

Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications. The course emphasis is placed on teaching quality tools as they relate to manufacturing processes.

Topics Include:

Gage R&R
Destructive Testing
Gage Linearity and Bias
Attribute Agreement
Variables and Attribute Control Charts
Capability Analysis for Normal, Nonnormal, and Attribute Data

Process Capability Sixpack Report for Thickness

DAY 4

Continue to build on the fundamental concepts taught in the Manufacturing Statistical Quality Analysis course by learning additional tools that help to improve and control your processes. Develop the necessary skills to successfully evaluate and certify manufacturing and engineering measurement systems with multiple gages or locations on a part. Learn how to evaluate a random sample of product from a lot to determine whether to accept or reject the entire lot. Expand your knowledge of control charting to handle rare events and time weighted data.

Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications. The course emphasis is placed on teaching quality tools as they relate to manufacturing processes.

Topics Include:

Gage R&R Expanded
Orthogonal Regression
Tolerance Intervals
Acceptance Sampling
Between-Within Analysis
Control Charts including EWMA, Short-Run, CUSUM, and Rare Events

Average Outgoing Quality Curve