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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 are properties of a CDF?
X~N(0 -1)
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Range is always between zero and 1 monotonically increasing
Central limit theorem

2. What can management do to mitigate the risk associated with infusing new technologies?
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
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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

3. TIES Step 5: Feasible?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Has a natural zero - is a cardinal scale
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
OEC = W1X/Xbsl + W2Nbsl/N

4. With 15 technologies - what is the number of possible combinations?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
To analytically answer 'How much design margin is really necessary?'
#=2^n = 2^15
It gives the probability that a value will be met or exceeded.

5. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
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
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.
OEC = W1X/Xbsl + W2Nbsl/N

6. 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.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Technique for Order Preference by Similarity to Ideal Solution
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

7. interval scale
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
#=2^n = 2^15
Determine the design space - baseline Method: Morphological Matrix
Does not have a natural zero - is a cardinal scale

8. Ratio scale
Has a natural zero - is a cardinal scale
OEC = W1X/Xbsl + W2Nbsl/N
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

9. 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
Sample size is 4 - the sample is the sum of the five dice.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Cumulative Distribution Function

10. TIES Step 1: Problem Definition
No way to tell without more information. It depends on the relation between s12+s22 and s32
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Sample size is 4 - the sample is the sum of the five dice.

11. Name the advantages of UTE.
A technique used to determine the best alternative with all interactions between the constraints. Used for product 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.
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

12. What is the equation for present equivalent value? Define variables.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
PE(i)=?Ft
Active UTE (additive) - Product UTE (multiplicative)
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

13. 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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal

14. What are the three snapshots of UTE?
Allows designer to assess feasibility of design
(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 related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Range is always between zero and 1 monotonically increasing

15. What two variables are necessary to define a normal distribution?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Mean and variance
P(between B and A)=F(B)-F(A)
Technology space limits

16. What is the definition of ROI?
CDF= ?_(-8)^8
The interest i such that 0=PE(i^)
Does not have a natural zero - is a cardinal scale
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

17. Assumptions Used in 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
No way to tell without more information. It depends on the relation between s12+s22 and s32
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

18. 3 Measures of Central Tendency (& Defs)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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
Central limit theorem
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.

19. $/RPM Equation
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(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

20. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
OEC = W1X/Xbsl + W2Nbsl/N
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.

21. TIF

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22. What is another name for a normal distribution?
Gaussian Distribution
Regions 1 to 3.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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

23. Does TIES use MADM or MODM? Why?
Has a natural zero - is a cardinal scale
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
To analytically answer 'How much design margin is really necessary?'
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

24. What are the four difference life cycle costs?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
RDTE - Investment/Acquisition - Operations and Support - Disposal
Does not have a natural zero - is a cardinal scale
To analytically answer 'How much design margin is really necessary?'

25. Why is learning curve used (or what is it?)
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.
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
#=2^n = 2^15

26. What does CDF stand for?
Cumulative Distribution Function
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

27. Other than infusing technologies - how can you create design space?
(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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Regions 1 to 3.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

28. What can be done about uncertainty in requirement?
A pareto frontier represents points of a non - dominated solution based on preferences
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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
Does not have a natural zero - is a cardinal scale

29. What is the definition of CDF?
Gaussian Distribution
It gives the probability that a value will be met or exceeded.
To analytically answer 'How much design margin is really necessary?'
F(x)=1/(s(2p)^(.5) )exp?(-(x-

30. 8 Steps in TIES
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) 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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

31. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
OEC = W1X/Xbsl + W2Nbsl/N
Regions 1 to 3.

32. In what regions of the graph is UTE applicable?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
(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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Regions 1 to 3.

33. What is TRL? Range? What does a high TRL mean?
Does not have a natural zero - is a cardinal scale
Sample size is 4 - the sample is the sum of the five dice.
A probability density contour plot is a visualization method for Joint probability density function (a 2D representation). Their shapes (contour shapes) tell if the metric analyzed in each axis are correlated or not (Circular -> no correlation) (elli
Technology 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

34. Show and explain a pareto frontier
F(x)=1/(s(2p)^(.5) )exp?(-(x-
A pareto frontier represents points of a non - dominated solution based on preferences
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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

35. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

36. TIES
is bottom- up - you look at certain technologies and see what improvements they offer
(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 Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Mean and variance

37. How is inflation measured?

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38. What are the parameters for a standard normal distribution?
Technology space limits
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Mean =0 Variance =1
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

39. What is TCM? What is the size and what value can it take?
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
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
Range is always between zero and 1 monotonically increasing
To analytically answer 'How much design margin is really necessary?'

40. What is the notation for a standard normal distribution?
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
A pareto frontier represents points of a non - dominated solution based on preferences
X~N(0 -1)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

41. What is the normal distribution that results from adding x+y and x[sub]y?
X+Y and X-Y are normally distributed. - (X
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Active UTE (additive) - Product UTE (multiplicative)
Does not have a natural zero - is a cardinal scale

42. TIES Step 4: Investigate Design Space
The interest i such that 0=PE(i^)
Mean =0 Variance =1
is bottom- up - you look at certain technologies and see what improvements they offer
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.

43. TIES Step 3: Model and Simulation
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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
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

44. What does CLT stand for?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Mean and variance
Range is always between zero and 1 monotonically increasing
Central limit theorem

45. What is probability density contour plot
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Sample size is 4 - the sample is the sum of the five dice.
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
P(between B and A)=F(B)-F(A)

46. What does TOPSIS stand for?
Technique for Order Preference by Similarity to Ideal Solution
(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
Does not have a natural zero - is a cardinal scale

47. What are K- factors applied to?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Technology space limits
Mean =0 Variance =1
PE(i)=?Ft

48. Why are scaling parameters important?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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 technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

49. TIES Step 6: Identify Technology
Active UTE (additive) - Product UTE (multiplicative)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
(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

50. Define fixed cost and variable cost.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
No way to tell without more information. It depends on the relation between s12+s22 and s32
(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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers