Tampere University of Technology
Feihu Zhao
Tampere University of Technology
Lecture 01
1. Phases of Design
2. Moore’s Law
The complexity for minimum component costs has increased at a rate of roughly a factor of two
per year; Certainly over the short term this rate can be expected to continue, if not to increase.
Over the longer term, the rate of increase is a bit more uncertain, although there is no reason to
believe it will not remain nearly constant for at least 10 years.
3. Ray Kurzweil’s Theory of the Technology Singularity
Ray Kurzweil has suggested that the human race will soon (by the mid 21st Centry) evolve into
transhumant immortal humanoid robots which will work to eventually turn the entire universe into
a gigantic supercomputer. He also suggest that this supercomputer will be able to reverse entropy
so that the immortal robots can live inside the supercomputer in virtual reality forever.
3.Some examples
Music Media; Applying information technology at cars; Communication with computer in the
past, now and in the future; etc.
Tampere University of Technology
Lecture 02
1.New Product Development Task
At the beginning of product development, a market report should be made, considering the
following questions:
(1) What the customer want to have; (2) What competitors can offer; (3) Where we have new
thought; (4) where there is our target groups; (5) Which phase of life our other products are;
(6) What advantages the new product could bring.
2. Expected Commercial Value of the Product
3. Stages
(1) Skethcing Phase; (2) Outlining Phase; (3) Finishing Phase.
4. Nature of Design
yr = Set of requirements; y= Expected system characteristics; x= Information describing the
design; f= function mapping design x to system characteristics; f-1= ideal design.
5.Example of design matrix
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Lecture 03
1. Allometric Models, Modeling Scale Dependency
2. Linear Regression
yi= axi+b+εi
Estimate for coefficient a and b, in which the residual εi is minimal.
3.Allometric Models, Power Model
(1) An Allometric relationship often has the form : yi=bi
j 1
Which also can be written as: log(yi)=bi+  mij log( x j )
j 1
eg. Electrical motor, weight/power
4. Model Representation
 x
y=y0 
 x0
y  a0
x0 dy
y 0 dx
5.General Representation for the Multi Variable Model
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Lecture 04
1.Design Matrix
Connect system properties to system parameters.
2. Axiomatic Design
Axiom1: Independence Axiom;
Axiom2: Good design has low information content.
eg. Aeroplane:
3. Taguchi-method
(1) The object of taguchi-method is to determine the values of parameters the designer can
choose so that a maxium performance will be reached with minimum distance for variation in
condition and production parameters.
(2) The number which appears in the matrix tells the number of the tests to be performed.
Number 1 and Number 2 in the matrix represent the levels of parameters, in this case small
and big values. The test result Y is the quality property of the product which an attempt is
made to optimize.
4. Relationship between customer properties to computer properties
eg. An electrical motorcycle
In the system characteristics such as: Range; Acceleration; Maxium Speed; Operational Cost;
Final Cost.
Tampere University of Technology
Lecture 05
1. Sensitivity Analysis
y=f(x)-----Nonlinear Function
Here, Jacobian J is also identical to the sensitivity matrix k.
2.Normalized Sensitivities
xi y i
y i x j
Result in dimensionless values in a operating point.
3. Relative Sensitivities
In this way, the sum of elements in one row is one and it is easier to get an overview of the
relative importance of different parameters. This is refered here as the Relative Sensitivity.
4. Aggregated Design Impact Matrix
(1) Add absolute values of all sensitivities to avoid of the drawback that while adding
parameters together, they will cancel each other.
(2) In this way, the matrix when shown at the top level will have the same appearance
regardless of how detailed the underlying system is.
5. System Characteristics Correlation (SCC)
(1) Completely aligned: correlation=1;Orthogonal: correlation=0; Point in the opposite
direction: correlation=-1.
6. System Characteristics Dependencies(SCD)
(1) SCD is used for measuring what areas can be improved without scarifying too much in
other areas when setting up the requirement for designing.
(2) SCDik 
j 1
0 0
ij kj
Tampere University of Technology
Lecture 06
1. Concept Generation
(1) Black Box as a starting point:
(2) Realization of functions can be distributed as a chain of sub-functions:
2. Function Means Tree
Enable systematic searching of alternative concepts:
Tampere University of Technology
Lecture 07
1. Fault Tree Analysis(FTA)
Procedure of FTA:
(1) Define the system of interest; (2) Define the TOP event for the analysis; (3) Define the
tree top structure; (4) Expand each branch in successive levels of detail; (5) Solve the fault
tree for the combinations of events contributing to the top event; (6) Identify important
dependent failure potentials and adjust the model appropriately; (7) Perform quantitative
analysis.(if necessary); (8) Use the results in decision making.
eg. risk of fire:
2. Reliability Calculation
(1) If the system is described by the equation a=bcd (like the eg. of risk of fire), the
propability of top level event can be written as: λa =λbλcλd
where, λx is propability that event x will occur.
(2) If the system is described by the equation: a=b+c+d (or a=-((-b)+(-c)+(-d))
where, -x is the inverse of x and hence the propability of –x is: λ-x =(1- λx); λa
3.Mean Time Between Failures(MTBF)
MTBF=1/ λ
Failure rate λ express number of failures in total time.
MTBF is used as a measure of reliability
Tampere University of Technology
Lecture 08
1. Testing the Control Center of the Load
Problem: How to ensure that the module software functions correctly in all situation?
Control system between all kinds of softwares should be tested. And the structure of testing
system is like following figure.
2. Product Modeling
Several modeling approaches:
(1)Graphical ’high level of abstraction’ representations; (2) Some are standardized and
available in commercial software based tools; (3) Other technical modeling and simulation
tools, such as: MATLAB, CAD/CAM etc. are developed.
3.Requirement Representation
Processes: (1) Elicitation; (2) Analysis; (3) Specification; (4) Validation.
4. Sate Diagram
How to create state diagram?
(1) Find all relevant states and transitions; (2) For each state, define (a.) all possible state
transitions, (b.) triggers for all transitions.
5. UML
(1) Why use UML? (a) Help to reduce cost and time-to-market;(b) Help managing a complex
project architecture; (c) Help to convey ideas between developers/designers/etc.
(2) Take example of coffee machine:
Coins Return (Functionality)
Buys a cup of coffee
Porter: Brew a cup of coffee
add substance
Keep track
Choose machine
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