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Provided by: Launsby Consulting

Design of Experiments elearning course

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Training Provided by Launsby Consulting

This session is geared toward the technician, engineer, scientist or manager who wants to understand how to conduct simple (but powerful) designed experiments without unnecessary statistical rigor.

Finding time for a three to five day seminar is becoming increasingly difficult. Travel problems associated with seminar attendance have increased dramatically. On-Line learning provides a cost-effective means to obtain the design of experiments knowledge you need. The course utilizes audio, video, text and graphics to provide the student with the ultimate on-line learning experience.

Training Avaliability and Delivery

This is primarily online training
on-line e-learning cbt (computer based)This is an online eLearning or CBT training program
Contact Launsby Consulting for more information
Course Level:introductory
Schedule:flexible
Training Presented in:English

Related Keywords:  design of experiments   elearning   on-line   experimental design   taguchi   doptimal   anova   anom   regression analysis 

Training Program Details


Module 1 (The Simple Facts)
DOE Definition

Process Diagram
Inputs and Outputs
Responses
Factors

Example
Factor Levels
Tree Diagram
Full Factorial Design
Design Matrix
Orthogonal Design

Data Collection

Analysis
Pareto Chart
Main Effects Plot
Hitting a Target
Contour Plot

Confirmation Runs

Module 2 (Fractional Factorial Designs)
Interactions
Definition
Example

Aliasing
Definition
Example

Fractional Factorial Example
Factors
Worksheet
Data Entry
Pareto Chart

Analysis of Variance
Squared Multiple R
P(2 tail) values
F ratio
P value

Contour Plot

Confirmation Runs

Module 3 (Optimizing Several Responses)
Multiple Responses

Mt. Bike Tire Example
Factors and Responses
Factor Levels
Design Matrix

Potential Data Collection Problems
Measurement Errors
Errors In Conducting the Experiment
Wrong assumptions regarding interactions
Process Changes
Extrapolation

Desirability Functions
Definition
Steps

Tire Example (Continued)
Data Entry
ANOVA (Tensile Strength)
ANOVA (Hardness)
Prediction Equation
Response Surface Plot
Contour Plot (Tensile Strength)
Contour Plot (Hardness)
Contour Plot (Both)

Confirmation Runs

Summary


Module 4 (Other Design Types)
Plackett-Burman Design
Example Matrix

Taguchi Designs
L4
L8
L9
L18
L12

Signal To Noise Ratio
Smaller Is Better
Larger Is Better
Nominal Is Better

Modeling Designs
Box-Behnken
Central Composite

D-optimal Designs

Summary

Module 5 (Variance Reduction)
Types of Factors
Affect the average
Affect the variation
Affect average and variation
Have no effect

Example - "Hitting the Target"
Design Matrix
Pareto Chart
Hit a Target Screen
Confirmation Runs

Example - "Reducing Variation"
Pareto Chart
Main Effects Plot
Contour Plot
Confirmation Runs
Summary

Module 6 (Using DOE Wisdom software)
Opening Software

Design Definition Screen
Experimental Objective
Factor Definition
Response Definition
Design Types

Worksheet Window

Data Definition Window

Statistical Analysis
ANOVA
Hit a Target

Graphical Analysis
Pareto Chart
Scatter Plot
Main Effects Plot
Interaction Plot
Contour Plot
Response Surface Graph

Confirmation Runs
Summary

Module 7 (Using Minitab Software)
Opening Minitab Software

Starting A New Project
Experimental Objectives
Design Type
Factor Definition

Data Window
Response Definition
Printing a Worksheet
Data Entry

Analysis
Pareto Chart
Normal Probability Chart
Estimated Effects and Coefficients Table
Fit a New Model
Residual Plot
Main Effects Plot
Interaction Plot
Contour Plot
Surface Plot
Conclusion

About Launsby Consulting - Training Provider

Launsby Consulting - Since 1991, Launsby Consulting has provided applications oriented training, software, books, tools and consulting services in the areas of Design of Experiments, Process Validation, Statistical Process Control, Six Sigma, Neural Networks, Fuzzy Logic, Design for Six Sigma and Data Mining. We are committed to provide training, consulting services, software and tools that help companies meet...

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