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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. 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.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

2. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
Mean =0 Variance =1
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

3. 4 Measures of Dispersion
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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
The interest i such that 0=PE(i^)
Has a natural zero - is a cardinal scale

4. How is inflation measured?

5. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
No way to tell without more information. It depends on the relation between s12+s22 and s32
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
Technology space limits

6. What are the three snapshots of UTE?
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
P(between B and A)=F(B)-F(A)
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

7. If you have a two values on a CDF what is the probability of getting a value between them?
Mean and variance
P(between B and A)=F(B)-F(A)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

8. What does CLT stand for?
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
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
Central limit theorem

9. How do you get the CDF from the PDF?
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.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
CDF= ?_(-8)^8

10. 8 Steps in TIES
(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.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
(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

11. 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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

12. What can management do to mitigate the risk associated with infusing new technologies?
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
Sample size is 4 - the sample is the sum of the five dice.
Range is always between zero and 1 monotonically increasing
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

13. What is the definition of CDF?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Determine the design space - baseline Method: Morphological Matrix
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
It gives the probability that a value will be met or exceeded.

14. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Range is always between zero and 1 monotonically increasing
RDTE - Investment/Acquisition - Operations and Support - Disposal
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.

15. MODM
Has a natural zero - is a cardinal scale
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Cumulative Distribution Function

16. What are properties of a CDF?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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
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

17. Show and explain a pareto frontier
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
A pareto frontier represents points of a non - dominated solution based on preferences
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

18. TIES Step 5: Feasible?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Central limit theorem
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

19. Define fixed cost and variable cost.
Regions 1 to 3.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

20. What is the definition of ROI?
The interest i such that 0=PE(i^)
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.
A pareto frontier represents points of a non - dominated solution based on preferences

21. Why is learning curve used (or what is it?)
(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
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.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

22. What is probability density contour plot
Trying to determine the metric values for any combination of design variables/ what the metrics are as a function of design variables Method: RSE: Response Surface Eqn.
A 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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

23. Assumptions Used in TOPSis...
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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)
OEC = W1X/Xbsl + W2Nbsl/N

24. 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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
No way to tell without more information. It depends on the relation between s12+s22 and s32

25. What is the goal of probabilistic design?

26. 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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
is bottom- up - you look at certain technologies and see what improvements they offer
Range is always between zero and 1 monotonically increasing

27. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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

28. Does TIES use MADM or MODM? Why?
X~N(0 -1)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

29. TIF

30. What is TCM? What is the size and what value can it take?
Technique for Order Preference by Similarity to Ideal Solution
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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

31. Indirect Operating Cost
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Cumulative Distribution Function
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

32. interval scale
Does not have a natural zero - is a cardinal scale
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Active UTE (additive) - Product UTE (multiplicative)
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

33. 3 Probabilistic Design Methods
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
#=2^n = 2^15

34. What does TOPSIS stand for?
The interest i such that 0=PE(i^)
#=2^n = 2^15
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
Technique for Order Preference by Similarity to Ideal Solution

35. What are the four difference life cycle costs?
RDTE - Investment/Acquisition - Operations and Support - Disposal
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Gaussian Distribution
PE(i)=?Ft

36. Why do we use a sample?
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 sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

37. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
It can be continuous or discrete
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
A pareto frontier represents points of a non - dominated solution based on preferences

38. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
PE(i)=?Ft
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

39. Why use uniform dist for input variables (Gap Analysis)
X~N(0 -1)
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.
Allows designer to assess feasibility of design
Does not have a natural zero - is a cardinal scale

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

41. What are the different types of UTEs?
Technique for Order Preference by Similarity to Ideal Solution
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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.
Active UTE (additive) - Product UTE (multiplicative)

42. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Mean and variance
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
No way to tell without more information. It depends on the relation between s12+s22 and s32
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

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

44. TIES Step 4: Investigate Design Space
is bottom- up - you look at certain technologies and see what improvements they offer
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
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.
X+Y and X-Y are normally distributed. - (X

45. TIES Step 3: Model and Simulation
Mean and variance
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.
Technique for Order Preference by Similarity to Ideal Solution
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

46. Ratio scale
Has a natural zero - is a cardinal scale
is bottom- up - you look at certain technologies and see what improvements they offer
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

47. What are K- factors applied to?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Active UTE (additive) - Product UTE (multiplicative)
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 space limits

48. What is another name for a normal distribution?
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
Mean and variance
Gaussian Distribution
P(between B and A)=F(B)-F(A)

49. What can be done about uncertainty in requirement?
Technique for Order Preference by Similarity to Ideal Solution
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

50. What is the definition of inflation?
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
Has a natural zero - is a cardinal scale
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Does not have a natural zero - is a cardinal scale