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Design of Experiments

 

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Statistical Process Control ] SPC for the Process Industries ] Working with Data ] Design of Experiments ]

Overview

Designed experiments are powerful tools for improving products and processes. Using designed experiments it is possible to determine the cause and effect relationship between controllable variables and output characteristics.  Output characteristics can include quality, cost and performance areas.

The workshop is structured to enable a participant to plan, execute and analyze various designed experiments.  The workshop includes hands-on experience with a catapult that simulates a manufacturing process. Design-Expert® software is used in the class to maximize the learning experience. Students are given a 90-day trial version of the software and a 20 % discount for purchase.  Participants will develop a designed experiment plan they can run at the workplace.

Participants

Engineers and managers from manufacturing, product development, research and quality functions.

Seminar Objectives

To enable engineers and managers to improve processes through the use of designed experiments. Specific results include:

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Basic understanding of experimental design

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Ability to identify key process and product variables

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Understanding of sequential experimentation and how to determine the most economical design that will meet objectives

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How to plan and conduct an experiment

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Testing underlying assumptions

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Improved analysis and presentation of results

Time

Four days

Outline Introduction

Role of Experimental Design in Industry

Basic Statistical Concepts

Numerical statistics
Normal Distribution

Simple Comparative Experiments and Statistics Fundamentals

Alpha and Beta risk
Comparisons of Means, Variances

Single-Factor Experiments

Randomization
Analysis of Variance (ANOVA)
Multiple Comparisons
Replication and Sample Size

Randomized Block & Latin Square Designs

Factorial Experiments

Concept of Factorials
Design Issues
Analysis of Interactions
Blocking, Confounding Schemes
Table of + - signs
Three Factor Factorial
Model Evaluation
Sparsity of Effects Principle
Addition of Center Points

Fractional Factorials

Fractional Factorials
Design Resolution
Projection Property
Sequential Experimentation
Plackett-Burman Designs

Process Optimization

Empirical Optimization
Response Surface Methods
Central Composite Design
Box-Behnken Design
Mixture Designs

Planning Experiments

All workshops can be held on-site!
For a rate quote call
860-940-7799
or e-mail:
  info@mesacg.com

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Last modified: January 16, 2008