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1. What are properties of a CDF?
Range is always between zero and 1 monotonically increasing
Has a natural zero - is a cardinal scale
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
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

2. interval scale
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
Does not have a natural zero - is a cardinal scale
CDF= ?_(-8)^8
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

3. What are the parameters for a standard normal distribution?
Cumulative Distribution Function
Range is always between zero and 1 monotonically increasing
PE(i)=?Ft
Mean =0 Variance =1

4. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
Does not have a natural zero - is a cardinal scale
(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) 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

5. What is the goal of robust design?

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6. What is another name for a normal distribution?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Gaussian Distribution
(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
Determine the design space - baseline Method: Morphological Matrix

7. What is probability density contour plot
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

8. What is the difference between price and cost?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Range is always between zero and 1 monotonically increasing
OEC = W1X/Xbsl + W2Nbsl/N

9. Indirect Operating Cost
P(between B and A)=F(B)-F(A)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Allows designer to assess feasibility of design
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

10. Other than infusing technologies - how can you create design space?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Has a natural zero - is a cardinal scale
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

11. What is the definition of ROI?
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
Determine the design space - baseline Method: Morphological Matrix
The interest i such that 0=PE(i^)
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

12. What is the equation for the learning curve?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

13. In what regions of the graph is UTE applicable?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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
Regions 1 to 3.
Technique for Order Preference by Similarity to Ideal Solution

14. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Regions 1 to 3.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

15. What are the three snapshots of UTE?
Cumulative Distribution Function
RDTE - Investment/Acquisition - Operations and Support - Disposal
Technology space limits
(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

16. MADM
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal
Gaussian Distribution

17. What is the goal of probabilistic design?

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18. 8 Steps in TIES
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
OEC = W1X/Xbsl + W2Nbsl/N
(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
Has a natural zero - is a cardinal scale

19. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
Does not have a natural zero - is a cardinal scale
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

20. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
RDTE - Investment/Acquisition - Operations and Support - Disposal
OEC = W1X/Xbsl + W2Nbsl/N
The interest i such that 0=PE(i^)

21. 4 Measures of Dispersion
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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 space limits
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

22. What is the normal distribution that results from adding x+y and x[sub]y?
Mean and variance
It can be continuous or discrete
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

23. What is satisficing - what is optimizing?
Has a natural zero - is a cardinal scale
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.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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

24. TIES Step 5: Feasible?
No way to tell without more information. It depends on the relation between s12+s22 and s32
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
PE(i)=?Ft
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

25. Show and explain a pareto frontier
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
A pareto frontier represents points of a non - dominated solution based on preferences
(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 Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

26. 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) End result not intuitive (2) Heavily reliant on weights - which are subjective
Active UTE (additive) - Product UTE (multiplicative)
OEC = W1X/Xbsl + W2Nbsl/N

27. $/RPM Equation
Cumulative Distribution Function
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

28. What are the different types of UTEs?
Central limit theorem
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Active UTE (additive) - Product UTE (multiplicative)
(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

29. Why do we use a sample?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Central limit theorem

30. What is TRL? Range? What does a high TRL mean?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Allows designer to assess feasibility of design
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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

31. Ratio scale
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
A pareto frontier represents points of a non - dominated solution based on preferences
Has a natural zero - is a cardinal scale
It gives the probability that a value will be met or exceeded.

32. What two variables are necessary to define a normal distribution?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
The interest i such that 0=PE(i^)
Technique for Order Preference by Similarity to Ideal Solution
Mean and variance

33. Does TIES use MADM or MODM? Why?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

34. MODM
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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
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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

35. What can be done about uncertainty in requirement?
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
It gives the probability that a value will be met or exceeded.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

36. TIES Step 4: Investigate Design Space
(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
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.
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
X~N(0 -1)

37. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
It can be continuous or discrete
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

38. Assumptions Used in TOPSis...
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
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

39. 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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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
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

40. What are the four difference life cycle costs?
PE(i)=?Ft
RDTE - Investment/Acquisition - Operations and Support - Disposal
(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) 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

41. What is the notation for a standard normal 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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
X~N(0 -1)
Sample size is 4 - the sample is the sum of the five dice.

42. 3 Measures of Central Tendency (& Defs)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

43. Why are scaling parameters important?
No way to tell without more information. It depends on the relation between s12+s22 and s32
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.
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

44. What can management do to mitigate the risk associated with infusing new technologies?
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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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) End result not intuitive (2) Heavily reliant on weights - which are subjective

45. Why is the normal distribution useful or important?

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46. What does CDF stand for?
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
Cumulative Distribution Function
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.
Technology space limits

47. 3 Probabilistic Design Methods
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

48. TIES
PE(i)=?Ft
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
is bottom- up - you look at certain technologies and see what improvements they offer

49. TIES Step 3: Model and Simulation
Technology space limits
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
Sample size is 4 - the sample is the sum of the five dice.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

50. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
is bottom- up - you look at certain technologies and see what improvements they offer