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ADM

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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. interval scale
No way to tell without more information. It depends on the relation between s12+s22 and s32
Does not have a natural zero - is a cardinal scale
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
CDF= ?_(-8)^8

3. Strengths of TOPSis...
(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
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
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

4. What is satisficing - what is optimizing?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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.
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.

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

6. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
OEC = W1X/Xbsl + W2Nbsl/N
It gives the probability that a value will be met or exceeded.
Technology space limits

7. What is the difference between price and cost?
OEC = W1X/Xbsl + W2Nbsl/N
#=2^n = 2^15
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
No way to tell without more information. It depends on the relation between s12+s22 and s32

8. What is the equation for present equivalent value? Define variables.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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
PE(i)=?Ft
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

9. What is the definition of CDF?
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
Allows designer to assess feasibility of design
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
It gives the probability that a value will be met or exceeded.

10. 3 Probabilistic Design Methods
To analytically answer 'How much design margin is really necessary?'
X+Y and X-Y are normally distributed. - (X
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
It gives the probability that a value will be met or exceeded.

11. 8 Steps in TIES
(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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Allows designer to assess feasibility of design
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

12. Show and explain a pareto frontier
CDF= ?_(-8)^8
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
A pareto frontier represents points of a non - dominated solution based on preferences
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

13. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

14. What can be done about uncertainty in requirement?
Technology space limits
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
is bottom- up - you look at certain technologies and see what improvements they offer
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

15. TIES Step 3: Model and Simulation
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
(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
Mean =0 Variance =1
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

16. Write down a formula for a normal distribution
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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

17. MADM
Allows designer to assess feasibility of design
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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.
PE(i)=?Ft

18. Why use uniform dist for input variables (Gap Analysis)
(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
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
Allows designer to assess feasibility of design
Regions 1 to 3.

19. What does CDF stand for?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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.
Has a natural zero - is a cardinal scale
Cumulative Distribution Function

20. TIES Step 6: Identify Technology
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
(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

21. What are the three snapshots of UTE?
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
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.
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.
(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

22. What are the four difference life cycle costs?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
(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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

23. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
No way to tell without more information. It depends on the relation between s12+s22 and s32
Gaussian Distribution
(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
is bottom- up - you look at certain technologies and see what improvements they offer

24. Assumptions Used in TOPSis...
CDF= ?_(-8)^8
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

25. 4 Measures of Dispersion
The interest i such that 0=PE(i^)
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
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.
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

26. What is the equation for the learning curve?
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.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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

27. 3 Measures of Central Tendency (& Defs)
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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

28. Why is the normal distribution useful or important?

29. What does the CLT state - be specific!
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 related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

30. What are the different types of UTEs?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Active UTE (additive) - Product UTE (multiplicative)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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.

31. What does TOPSIS stand for?
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
P(between B and A)=F(B)-F(A)
Technique for Order Preference by Similarity to Ideal Solution

32. Weaknesses of TOPSis...
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) End result not intuitive (2) Heavily reliant on weights - which are subjective
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

33. TIES Step 1: Problem Definition
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Mean =0 Variance =1
Gaussian Distribution
RDTE - Investment/Acquisition - Operations and Support - Disposal

34. With 15 technologies - what is the number of possible combinations?
Active UTE (additive) - Product UTE (multiplicative)
A pareto frontier represents points of a non - dominated solution based on preferences
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
#=2^n = 2^15

35. What are K- factors applied to?
Active UTE (additive) - Product UTE (multiplicative)
Technology space limits
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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

36. What two variables are necessary to define a normal distribution?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Mean and variance
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.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

37. $/RPM Equation
is bottom- up - you look at certain technologies and see what improvements they offer
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.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

38. What is TRL? Range? What does a high TRL mean?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

39. How do you get the CDF from the PDF?
(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
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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
CDF= ?_(-8)^8

40. Why are scaling parameters important?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
(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
Sample size is 4 - the sample is the sum of the five dice.
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

41. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
#=2^n = 2^15
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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

42. What is the notation for a standard normal distribution?
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)
X~N(0 -1)
(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

43. What are properties of a CDF?
Range is always between zero and 1 monotonically increasing
To analytically answer 'How much design margin is really necessary?'
(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
P(between B and A)=F(B)-F(A)

44. 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
Sample size is 4 - the sample is the sum of the five dice.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Mean =0 Variance =1

45. What is probability density contour plot
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
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) 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

46. TIES Step 8: Selecting Technology

47. TIF

48. What is another name for a normal distribution?
Gaussian Distribution
P(between B and A)=F(B)-F(A)
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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.

49. TIES
is bottom- up - you look at certain technologies and see what improvements they offer
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Sample size is 4 - the sample is the sum of the five dice.

50. TIES Step 2: Design Space Conception
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
CDF= ?_(-8)^8
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Determine the design space - baseline Method: Morphological Matrix