Engineering Tool: Introduction to Design of Experiments (DOE)

Abstract

The course introduces to linear and non-linear modelling of processes via "Design of Experiments". DOE is an actively generated regression analysis for fast and economic determination of input parameters to achieve an optimal output with a reduced number of experiments.

Objective

The students gain insight into theory and practice of DOE. They learn the most important terms, DOE types, full and fractional-factorial modelling and what has to be respected during the factor selection and investigational procedure, everything enriched by a practical exercise. The course provides indispensable basic knowledge for target-oriented scientific experimentation.

Content

1. Einführung - T&E, OFAT, DOE, Vorteile von DOE - Auffrischung Multiple Regression - Multiple Regression vs DOE - DOE Typen: Screening, Refining, Optimizing 2. Theoretische Grundlagen - Vertiefung refining DOE - Voll-, teilfaktorielle DOE, confounding - Design generator, design resolution, factor levels, blocking - Beta-Risiko, Power, Replicates, Repeats, Mid-Points, Lack-of-fit 3. Versuchsplanung und -durchführung, Resultatanalyse - CNX Variablen - Experiment set-up mittels Software - Main effects, interaction plots - Modellreduzierung, Residualanalyse - Response optimizer - Einblick in die nicht-lineare Modellierung 4. Praktische Übung "Katapultschiessen" - Prozessverständnis - Versuchsdurchführung - Auswertung, Modellbildung, Wettbewerb

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