DoE (Design of Experiments)

DoE is an intelligent, structured and efficient methodology for designing and implementing experimental plans and analysing experimental results. The course covers the basics of designing experiments to examine the factors affecting the overall variability in the process and to evaluate the data obtained from these experiments. The objective is to identify those components of variability that are most significant. The basic models of experiments and their corresponding evaluation procedures based on analysis of variance (ANOVA) will be presented. Individual models will be demonstrated on specific examples, so that participants can use these model examples in their own practice.

Online termíny
Obsahová náplň školenia
Harmonogram školenia
Organizačné pokyny
Časté otázky
+421 908 345 320

Course content

Introduction to DoE
Basic concepts of experimental design, problem formulation, general linear model, analysis of variance, least squares method
Classical experimental strategies
The principles of DoE
Understanding experimental analysis - main and interactive effects, experimental error, graphs with normal probability, residual analysis
Identification of the variables that have the greatest impact on product quality
One-factor proposals, two-factor, repetitive, non-repetitive factors, general factor proposals, random blocks
Partial factor proposals, 2k and 3k proposals, 2k-p, 3k-p proposals, creation of these proposals
Analysis of optimization proposals: main effects, interactions, square effects, response area ANOVA
Practical examples and DoE training

Designed for

Additional information

Training Schedule - Open Public Online Term
Testing the training connection	from 07:45 *
Training program	08:00 - 12:00
Lunch break	12:00 - 12:30
Training program	12:30 - 14:00
Processing a case study / test	after 14:00