Design of Engineering Experiments
The 2k-p Fractional Factorial Design
Text reference, Chapter 8
Motivation for fractional factorials is obvious; as the
number of factors becomes large enough to be
interesting, the size of the designs grows very quickly
IE 532
Design and Analysis of Experiment
Exam Preparation Homework
Due: 19 January 2011
Soru 1: Rassal olarak seilen 24 rencinin; birincisinde 10, ikicisinde 14 olmak zere iki
guruba blndn varsayalm. Birinci guruba sadece ders anlatlsn. kinci guruba ise d
Chapter 14
Design and Analysis
1
Design of Engineering Experiments
Nested and Split-Plot Designs
Text reference, Chapter 14
These are multifactor experiments that have some
important industrial applications
Nested and split-plot designs frequently inv
Chapter 13
Design & Analysis
1
Design of Engineering Experiments Experiments with Random Factors
Text reference, Chapter 13
Previous chapters have considered fixed factors
A specific set of factor levels is chosen for the experiment
Inference confined
Chapter 12
Design & Analysis of
Experiments 7E 2009
1
Robust Design
Goal is to make products and processes robust
or less sensitive to variability transmitted by
factors that cannot be easily controlled
Methods for RPD or robust parameter design
was dev
Chapter 11
Design & Analysis of
Experiments 7E 2009
1
Text reference, Chapter 11
Primary focus of previous chapters is
factor screening
Two-level factorials, fractional factorials are
widely used
Objective of RSM is optimization
RSM dates from the 19
Chapter 10
Design & Analysis of
Experiments 7E 2009
1
Regression models are empirical as opposed to mechanistic models
Regression modeling is often performed on undesigned or unplanned
data
Regression modeling is also used extensively to build models to d
Chapter 9
Design & Analysis of
Experiments 7E 2009
1
The 3 Factorial Design
k
Chapter 9
Design & Analysis of
Experiments 7E 2009
2
Notation
Factor levels are sometime denoted 1, 2, 3
Qualitative or categorical factors are low,
medium, high
Individual r
Design of Engineering Experiments
Blocking & Confounding in the 2k
Text reference, Chapter 7
Blocking is a technique for dealing with
controllable nuisance variables
Two cases are considered
Replicated designs
Unreplicated designs
Chapter 7
Design &
Design of Engineering Experiments
Two-Level Factorial Designs
Text reference, Chapter 6
Special case of the general factorial design; k factors,
all at two levels
The two levels are usually called low and high (they
could be either quantitative or qual
Factorial Experiments
Text reference, Chapter 5
General principles of factorial experiments
The two-factor factorial with fixed effects
The ANOVA for factorials
Extensions to more than two factors
Quantitative and qualitative factors
response curves and
Experiments with Blocking Factors
Text Reference, Chapter 4
Blocking and nuisance factors
The randomized complete block design or
the RCBD
Extension of the ANOVA to the RCBD
Other blocking scenariosLatin square
designs
Chapter 4
Design & Analysis of
Analysis of Variance
Chapter 3
Design & Analysis of Experiments
7E 2009 Montgomery
1
What If There Are More Than
Two Factor Levels?
The t-test does not directly apply
There are lots of practical situations where there are
either more than two levels of
Chapter 2 Basic Statistical Methods
Describing sample data
Random samples
Sample mean, variance, standard deviation
Populations versus samples
Population mean, variance, standard deviation
Estimating parameters
Simple comparative experiments
The hypoth