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Answer 50 questions in 15 minutes.
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Match each statement with the correct term.
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1. What is the goal of probabilistic design?

2. TIES Step 8: Selecting Technology

3. What does TOPSIS stand for?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Technique for Order Preference by Similarity to Ideal Solution
Mean and variance
A pareto frontier represents points of a non - dominated solution based on preferences

4. Define fixed cost and variable cost.
A probability density contour plot is a visualization method for Joint probability density function (a 2D representation). Their shapes (contour shapes) tell if the metric analyzed in each axis are correlated or not (Circular -> no correlation) (elli
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Cumulative Distribution Function

5. What are the different types of UTEs?
Technology Readiness Level Ranges 1-9 - where 1 means that the basic principle have been observed and reported and 9 means the technology has had successful missions A high tech means the technology is pretty developed and should be (or is) ready for
It gives the probability that a value will be met or exceeded.
Active UTE (additive) - Product UTE (multiplicative)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

6. interval scale
Provide for rapid trade- off capability between the three elements and search for feasible solutions - Allow graphical visualization of the combined space - Address mission requirements ambiguity and technology uncertainty.
is bottom- up - you look at certain technologies and see what improvements they offer
Optimizing - finds the set of criteria that maximizes or minimizes a design criteria or several design criteria - Satisficing - finds the conditions where the constraints or requires are met but no optimization occurs.
Does not have a natural zero - is a cardinal scale

7. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
As you add n number of identical & independent distributions (IIDs) together - as n --> inf - the resulting distribution will be normal - regardless of the shape of the IIDs
OEC = W1X/Xbsl + W2Nbsl/N
Inflation is the decrease in the buying power/value of money. It is caused by the when amount of available money changes wrt amount of product/services available
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

8. TIES Step 4: Investigate Design Space
Trying to determine the metric values for any combination of design variables/ what the metrics are as a function of design variables Method: RSE: Response Surface Eqn.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Sample size is 4 - the sample is the sum of the five dice.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

9. 3 Measures of Central Tendency (& Defs)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Trying to determine the metric values for any combination of design variables/ what the metrics are as a function of design variables Method: RSE: Response Surface Eqn.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

10. MADM
Sample size is 4 - the sample is the sum of the five dice.
A technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
A pareto frontier represents points of a non - dominated solution based on preferences

11. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
It can be continuous or discrete
is bottom- up - you look at certain technologies and see what improvements they offer
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

12. TIES Step 7: Assess Technology
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

13. Name the advantages of UTE.
Provide for rapid trade- off capability between the three elements and search for feasible solutions - Allow graphical visualization of the combined space - Address mission requirements ambiguity and technology uncertainty.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
is bottom- up - you look at certain technologies and see what improvements they offer
As you add n number of identical & independent distributions (IIDs) together - as n --> inf - the resulting distribution will be normal - regardless of the shape of the IIDs

14. Assumptions Used in TOPSis...
Has a natural zero - is a cardinal scale
Cumulative Distribution Function
The interest i such that 0=PE(i^)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

15. What is TIM? What is the size and what value can it take?

16. What is TRL? Range? What does a high TRL mean?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
PE(i)=?Ft
(1) Identify potential technologies that may improve technical & economical feasibility (2) Establish physical compatibility rules for diff techs (3) Determine expected impact (improvements and degradations) to systems of interest Method: TRL - Techn
Technology Readiness Level Ranges 1-9 - where 1 means that the basic principle have been observed and reported and 9 means the technology has had successful missions A high tech means the technology is pretty developed and should be (or is) ready for

17. Direct Operating Costs
As you add n number of identical & independent distributions (IIDs) together - as n --> inf - the resulting distribution will be normal - regardless of the shape of the IIDs
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
A pareto frontier represents points of a non - dominated solution based on preferences
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

18. What is TCM? What is the size and what value can it take?
Technology Compatability Matrix - For n techs - is nxn matrix - Tells whether the intersecting technologies are compatible - It only has 0s and 1s - 0 means the technologies are not compatible with each other - 1 means techs are compatible with each
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology

19. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Scaling parameters photographically scale the size of the vehicle to take full advantage of technology -(e.g. increase CL -> Can decrease S -> Decreases D -> Decreases Fuel Consumed -> etc...) This assumes that the physics of the problem remains the
(1) Identify potential technologies that may improve technical & economical feasibility (2) Establish physical compatibility rules for diff techs (3) Determine expected impact (improvements and degradations) to systems of interest Method: TRL - Techn
No way to tell without more information. It depends on the relation between s12+s22 and s32

20. TIF

21. What are properties of a CDF?
Range is always between zero and 1 monotonically increasing
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Technology Readiness Level Ranges 1-9 - where 1 means that the basic principle have been observed and reported and 9 means the technology has had successful missions A high tech means the technology is pretty developed and should be (or is) ready for

22. How do you get the CDF from the PDF?
Central limit theorem
Technology Compatability Matrix - For n techs - is nxn matrix - Tells whether the intersecting technologies are compatible - It only has 0s and 1s - 0 means the technologies are not compatible with each other - 1 means techs are compatible with each
CDF= ?_(-8)^8
Has a natural zero - is a cardinal scale

23. What does the CLT state - be specific!
CDF= ?_(-8)^8
As you add n number of identical & independent distributions (IIDs) together - as n --> inf - the resulting distribution will be normal - regardless of the shape of the IIDs
Select final tech comb. For any multi attribute - constraint - or criteria problem - the selection of the 'best' family of alternatives is inherently subjective. Various selection techniques are used to provide decision maker with extensive info. Met
Central limit theorem

24. Write down a formula for a normal distribution
X+Y and X-Y are normally distributed. - (X
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
X~N(0 -1)
F(x)=1/(s(2p)^(.5) )exp?(-(x-

25. What is the notation for a standard normal distribution?
X~N(0 -1)
Optimizing - finds the set of criteria that maximizes or minimizes a design criteria or several design criteria - Satisficing - finds the conditions where the constraints or requires are met but no optimization occurs.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
A probability density contour plot is a visualization method for Joint probability density function (a 2D representation). Their shapes (contour shapes) tell if the metric analyzed in each axis are correlated or not (Circular -> no correlation) (elli

26. What is the goal of robust design?

27. What does CDF stand for?
CDF= ?_(-8)^8
Cumulative Distribution Function
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Active UTE (additive) - Product UTE (multiplicative)

28. What is satisficing - what is optimizing?
M&S environment is needed to facilitate rapid assessments with minimal time and monetary expenditures of the alternative concepts identified in the Morphological Matrix Method: DoE
Optimizing - finds the set of criteria that maximizes or minimizes a design criteria or several design criteria - Satisficing - finds the conditions where the constraints or requires are met but no optimization occurs.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
RDTE - Investment/Acquisition - Operations and Support - Disposal

29. $/RPM Equation
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Technique for Order Preference by Similarity to Ideal Solution
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

30. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
Select final tech comb. For any multi attribute - constraint - or criteria problem - the selection of the 'best' family of alternatives is inherently subjective. Various selection techniques are used to provide decision maker with extensive info. Met
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology
Allows designer to assess feasibility of design

31. What is the definition of ROI?
The interest i such that 0=PE(i^)
Mean =0 Variance =1
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

32. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
No way to tell without more information. It depends on the relation between s12+s22 and s32
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

33. What is another name for a normal distribution?
Has a natural zero - is a cardinal scale
Gaussian Distribution
Technology Readiness Level Ranges 1-9 - where 1 means that the basic principle have been observed and reported and 9 means the technology has had successful missions A high tech means the technology is pretty developed and should be (or is) ready for
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

34. 3 Probabilistic Design Methods
Optimizing - finds the set of criteria that maximizes or minimizes a design criteria or several design criteria - Satisficing - finds the conditions where the constraints or requires are met but no optimization occurs.
Inflation is the decrease in the buying power/value of money. It is caused by the when amount of available money changes wrt amount of product/services available
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

35. What two variables are necessary to define a normal distribution?
Allows designer to assess feasibility of design
is bottom- up - you look at certain technologies and see what improvements they offer
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Mean and variance

36. What are K- factors applied to?
P(between B and A)=F(B)-F(A)
Mean =0 Variance =1
Technology space limits
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

37. Why is learning curve used (or what is it?)
RDTE - Investment/Acquisition - Operations and Support - Disposal
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

38. Why use uniform dist for input variables (Gap Analysis)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Allows designer to assess feasibility of design
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

39. TIES Step 2: Design Space Conception
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Determine the design space - baseline Method: Morphological Matrix
F(x)=1/(s(2p)^(.5) )exp?(-(x-
#=2^n = 2^15

40. TIES Step 5: Feasible?
OEC = W1X/Xbsl + W2Nbsl/N
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

41. TIES Step 6: Identify Technology
(1) Identify potential technologies that may improve technical & economical feasibility (2) Establish physical compatibility rules for diff techs (3) Determine expected impact (improvements and degradations) to systems of interest Method: TRL - Techn
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Mean =0 Variance =1

42. What is the definition of inflation?
Inflation is the decrease in the buying power/value of money. It is caused by the when amount of available money changes wrt amount of product/services available
Range is always between zero and 1 monotonically increasing
To analytically answer 'How much design margin is really necessary?'
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

43. You have a group of 5 dice. You roll the groups and sum the results of the 5 dice 4 times. What is the sample size? What are you sampling?
Sample size is 4 - the sample is the sum of the five dice.
It can be continuous or discrete
Allows designer to assess feasibility of design
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

44. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
It gives the probability that a value will be met or exceeded.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Trying to determine the metric values for any combination of design variables/ what the metrics are as a function of design variables Method: RSE: Response Surface Eqn.

45. What can management do to mitigate the risk associated with infusing new technologies?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
The interest i such that 0=PE(i^)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P

46. If you have a two values on a CDF what is the probability of getting a value between them?
P(between B and A)=F(B)-F(A)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Central limit theorem
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

47. Ratio scale
Allows designer to assess feasibility of design
CDF= ?_(-8)^8
Has a natural zero - is a cardinal scale
As you add n number of identical & independent distributions (IIDs) together - as n --> inf - the resulting distribution will be normal - regardless of the shape of the IIDs

48. How is inflation measured?

49. Other than infusing technologies - how can you create design space?
It can be continuous or discrete
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Mean =0 Variance =1

50. 4 Measures of Dispersion
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Select final tech comb. For any multi attribute - constraint - or criteria problem - the selection of the 'best' family of alternatives is inherently subjective. Various selection techniques are used to provide decision maker with extensive info. Met
Range: Gives the magnitude of the spread - min and max - Variance: Indicates how spread out the data is - Skewness: Indicates if the distribution is biased - Kurtosis: Peakness
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)