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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. Does TIES use MADM or MODM? Why?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Mean and variance
OEC = W1X/Xbsl + W2Nbsl/N
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

2. 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
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.
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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

3. Ratio scale
Has a natural zero - is a cardinal scale
Technique for Order Preference by Similarity to Ideal Solution
X~N(0 -1)
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

4. What is the equation for the learning curve?
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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(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
Has a natural zero - is a cardinal scale

5. What are the three snapshots of UTE?
(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
X~N(0 -1)
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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

6. Other than infusing technologies - how can you create design space?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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^)
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

7. What is probability density contour plot
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
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
The interest i such that 0=PE(i^)
is bottom- up - you look at certain technologies and see what improvements they offer

8. What does the CLT state - be specific!
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
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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

9. 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
Cumulative Distribution Function
P(between B and A)=F(B)-F(A)

10. If you have a two values on a CDF what is the probability of getting a value between them?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
P(between B and A)=F(B)-F(A)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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

11. Why are scaling parameters important?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

12. What is the normal distribution that results from adding x+y and x[sub]y?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Active UTE (additive) - Product UTE (multiplicative)
X+Y and X-Y are normally distributed. - (X
Technique for Order Preference by Similarity to Ideal Solution

13. What is the goal of robust design?

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14. What two variables are necessary to define a normal distribution?
Mean and variance
Technology space limits
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

15. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
Cumulative Distribution Function
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee

16. $/RPM Equation
It can be continuous or discrete
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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Regions 1 to 3.

17. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
X+Y and X-Y are normally distributed. - (X
OEC = W1X/Xbsl + W2Nbsl/N
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Technique for Order Preference by Similarity to Ideal Solution

18. In what regions of the graph is UTE applicable?
Determine the design space - baseline Method: Morphological Matrix
Regions 1 to 3.
The interest i such that 0=PE(i^)
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

19. What does CDF stand for?
Cumulative Distribution Function
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

20. Indirect Operating Cost
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
A pareto frontier represents points of a non - dominated solution based on preferences

21. 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.
Technology space limits
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.
Cumulative Distribution Function

22. Weaknesses of TOPSis...
A pareto frontier represents points of a non - dominated solution based on preferences
P(between B and A)=F(B)-F(A)
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
It can be continuous or discrete

23. What is TCM? What is the size and what value can it take?
Regions 1 to 3.
Has a natural zero - is a cardinal 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
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.

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

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25. TIES Step 8: Selecting Technology

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26. What can management do to mitigate the risk associated with infusing new technologies?
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
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

27. What is another name for a normal distribution?
Gaussian Distribution
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

28. interval scale
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
A pareto frontier represents points of a non - dominated solution based on preferences
Does not have a natural zero - is a cardinal scale
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

29. Assumptions Used in TOPSis...
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
Has a natural zero - is a cardinal scale
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

30. TIES Step 4: Investigate Design Space
Central limit theorem
OEC = W1X/Xbsl + W2Nbsl/N
X~N(0 -1)
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.

31. TIES Step 6: Identify Technology
It gives the probability that a value will be met or exceeded.
P(between B and A)=F(B)-F(A)
(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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

32. What does TOPSIS stand for?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Technique for Order Preference by Similarity to Ideal Solution
(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
RDTE - Investment/Acquisition - Operations and Support - Disposal

33. MADM
X+Y and X-Y are normally distributed. - (X
RDTE - Investment/Acquisition - Operations and Support - Disposal
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.
Regions 1 to 3.

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

35. What does CLT stand for?
Central limit theorem
Mean =0 Variance =1
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

36. 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
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.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Mean and variance

37. What are properties of a CDF?
Range is always between zero and 1 monotonically increasing
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.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Technology space limits

38. TIES Step 7: Assess Technology
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.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

39. TIES Step 5: Feasible?
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
Mean =0 Variance =1
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

40. TIES
is bottom- up - you look at certain technologies and see what improvements they offer
Mean =0 Variance =1
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

41. Show and explain a pareto frontier
It gives the probability that a value will be met or exceeded.
A pareto frontier represents points of a non - dominated solution based on preferences
(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
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

42. What is the definition of inflation?
Active UTE (additive) - Product UTE (multiplicative)
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

43. What is TRL? Range? What does a high TRL mean?
Has a natural zero - is a cardinal scale
No way to tell without more information. It depends on the relation between s12+s22 and s32
Mean and variance
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

44. How do you get the CDF from the PDF?
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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
CDF= ?_(-8)^8
It gives the probability that a value will be met or exceeded.

45. What can be done about uncertainty in requirement?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
CDF= ?_(-8)^8
P(between B and A)=F(B)-F(A)

46. Write down a formula for a normal distribution
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

47. 3 Probabilistic Design Methods
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

48. 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.
RDTE - Investment/Acquisition - Operations and Support - Disposal
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

49. With 15 technologies - what is the number of possible combinations?
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
It can be continuous or discrete
#=2^n = 2^15

50. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
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
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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