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1. In what regions of the graph is UTE applicable?
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
Regions 1 to 3.
The interest i such that 0=PE(i^)

2. TIES Step 7: Assess Technology
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
#=2^n = 2^15
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.
Active UTE (additive) - Product UTE (multiplicative)

3. Define fixed cost and variable cost.
Mean and variance
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

4. What does TOPSIS stand for?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Technique for Order Preference by Similarity to Ideal Solution
CDF= ?_(-8)^8

5. MADM
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Allows designer to assess feasibility of design
(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.

6. What is TIM? What is the size and what value can it take?
Sample size is 4 - the sample is the sum of the five dice.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Cumulative Distribution Function

7. Name the advantages of UTE.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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
Allows designer to assess feasibility of design
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.

8. TIES Step 6: Identify Technology
The interest i such that 0=PE(i^)
(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
Does not have a natural zero - is a cardinal scale
RDTE - Investment/Acquisition - Operations and Support - Disposal

9. Why is learning curve used (or what is it?)
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Central limit theorem
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

10. What is the difference between price and cost?
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
It can be continuous or discrete
Determine the design space - baseline Method: Morphological Matrix

11. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
To analytically answer 'How much design margin is really necessary?'
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

12. What are properties of a CDF?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Range is always between zero and 1 monotonically increasing

13. TIES Step 5: Feasible?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Mean and variance
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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

14. What are the parameters for a standard normal distribution?
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.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Mean =0 Variance =1

15. What is the equation for the learning curve?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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
Does not have a natural zero - is a cardinal scale

16. 4 Measures of Dispersion
Allows designer to assess feasibility of design
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
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
X+Y and X-Y are normally distributed. - (X

17. Write down a formula for a normal distribution
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-
It can be continuous or discrete

18. What does CLT stand for?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Central limit theorem
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
RDTE - Investment/Acquisition - Operations and Support - Disposal

19. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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.
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 that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.

20. 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?
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
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
Sample size is 4 - the sample is the sum of the five dice.
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

21. What are the four difference life cycle costs?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Sample size is 4 - the sample is the sum of the five dice.
Gaussian Distribution
Determine the design space - baseline Method: Morphological Matrix

22. 8 Steps in TIES
Gaussian Distribution
(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
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Sample size is 4 - the sample is the sum of the five dice.

23. What two variables are necessary to define a normal distribution?
Mean =0 Variance =1
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
Mean and variance
X+Y and X-Y are normally distributed. - (X

24. 3 Measures of Central Tendency (& Defs)
P(between B and A)=F(B)-F(A)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

25. What is the notation for a standard normal distribution?
It gives the probability that a value will be met or exceeded.
PE(i)=?Ft
Regions 1 to 3.
X~N(0 -1)

26. What can be done about uncertainty in requirement?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

27. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
Cumulative Distribution Function
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
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.

28. If you have a two values on a CDF what is the probability of getting a value between them?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
(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
P(between B and A)=F(B)-F(A)
Range is always between zero and 1 monotonically increasing

29. What is the goal of robust design?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
It can be continuous or discrete
Gaussian Distribution
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.

30. interval scale
Regions 1 to 3.
Does not have a natural zero - is a cardinal scale
X~N(0 -1)
OEC = W1X/Xbsl + W2Nbsl/N

31. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
(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)
(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

32. What does CDF stand for?
Cumulative Distribution Function
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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

33. What is probability density contour plot
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) End result not intuitive (2) Heavily reliant on weights - which are subjective
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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

34. $/RPM Equation
(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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
F(x)=1/(s(2p)^(.5) )exp?(-(x-

35. What is satisficing - what is optimizing?
OEC = W1X/Xbsl + W2Nbsl/N
(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
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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.

36. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
No way to tell without more information. It depends on the relation between s12+s22 and s32
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
(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

37. How do you get the CDF from the PDF?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
CDF= ?_(-8)^8
Mean and variance
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

38. Show and explain a pareto frontier
A pareto frontier represents points of a non - dominated solution based on preferences
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
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)

39. What is TRL? Range? What does a high TRL mean?
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
CDF= ?_(-8)^8
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

40. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Sample size is 4 - the sample is the sum of the five dice.

41. TIES
Technique for Order Preference by Similarity to Ideal Solution
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.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

42. What are K- factors applied to?
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.
Technology space limits
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Range is always between zero and 1 monotonically increasing

43. What is the definition of inflation?
is bottom- up - you look at certain technologies and see what improvements they offer
(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
#=2^n = 2^15
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

44. What are the different types of UTEs?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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
Active UTE (additive) - Product UTE (multiplicative)

45. Does TIES use MADM or MODM? Why?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to 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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

46. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
It gives the probability that a value will be met or exceeded.
(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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

47. TIES Step 1: Problem Definition
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.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Range is always between zero and 1 monotonically increasing
Mean =0 Variance =1

48. 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)
Central limit theorem
Does not have a natural zero - is a cardinal scale
CDF= ?_(-8)^8

49. What is TCM? What is the size and what value can it take?
Range is always between zero and 1 monotonically increasing
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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

50. What is the definition of ROI?
(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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
The interest i such that 0=PE(i^)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

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