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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 is the normal distribution that results from adding x+y and x[sub]y?
Mean and variance
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
X+Y and X-Y are normally distributed. - (X
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

2. What does CDF stand for?
The interest i such that 0=PE(i^)
P(between B and A)=F(B)-F(A)
Cumulative Distribution Function
Technology space limits

3. What does CLT stand for?
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.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

4. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
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.
OEC = W1X/Xbsl + W2Nbsl/N
Mean =0 Variance =1

5. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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) 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

6. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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?'

7. If you have a two values on a CDF what is the probability of getting a value between them?
P(between B and A)=F(B)-F(A)
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)
(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

8. TIES Step 8: Selecting Technology

9. TIES Step 6: Identify Technology
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
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

10. 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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Active UTE (additive) - Product UTE (multiplicative)
(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. 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?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
RDTE - Investment/Acquisition - Operations and Support - Disposal
(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
Sample size is 4 - the sample is the sum of the five dice.

12. TIF

13. Direct Operating Costs
X~N(0 -1)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

14. In what regions of the graph is UTE applicable?
Regions 1 to 3.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
is bottom- up - you look at certain technologies and see what improvements they offer

15. 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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
To analytically answer 'How much design margin is really necessary?'
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

16. What is the difference between price and cost?
Mean =0 Variance =1
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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.

17. Why is the normal distribution useful or important?

18. What does the CLT state - be specific!
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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

19. What is the definition of CDF?
Does not have 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
It gives the probability that a value will be met or exceeded.
Technology space limits

20. interval scale
Has a natural zero - is a cardinal scale
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.
Does not have a natural zero - is a cardinal scale

21. TIES Step 7: Assess Technology
Mean and variance
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
Mean =0 Variance =1
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

22. 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) 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
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

23. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
Allows designer to assess feasibility of design
X~N(0 -1)
Sample size is 4 - the sample is the sum of the five dice.

24. What are properties of a CDF?
Does not have a natural zero - is a cardinal scale
Range is always between zero and 1 monotonically increasing
RDTE - Investment/Acquisition - Operations and Support - Disposal
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

25. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
CDF= ?_(-8)^8
P(between B and A)=F(B)-F(A)
is bottom- up - you look at certain technologies and see what improvements they offer

26. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
CDF= ?_(-8)^8
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.
is bottom- up - you look at certain technologies and see what improvements they offer

27. How do you get the CDF from the PDF?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
CDF= ?_(-8)^8
A pareto frontier represents points of a non - dominated solution based on preferences

28. How is inflation measured?

29. What are K- factors applied to?
Gaussian Distribution
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
OEC = W1X/Xbsl + W2Nbsl/N
Technology space limits

30. Why use uniform dist for input variables (Gap Analysis)
Allows designer to assess feasibility of design
P(between B and A)=F(B)-F(A)
OEC = W1X/Xbsl + W2Nbsl/N
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

31. Assumptions Used in TOPSis...
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Mean =0 Variance =1
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(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

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

33. What are the different types of UTEs?
PE(i)=?Ft
It gives the probability that a value will be met or exceeded.
Active UTE (additive) - Product UTE (multiplicative)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

34. Why do we use a sample?
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.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

35. Indirect Operating Cost
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

36. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

37. What is another name for a normal distribution?
Gaussian Distribution
To analytically answer 'How much design margin is really necessary?'
Mean and variance
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

38. TIES Step 4: Investigate Design Space
X+Y and X-Y are normally distributed. - (X
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
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. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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
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

40. TIES Step 5: Feasible?
Does not have a natural zero - is a cardinal scale
Scaling parameters photographically scale the size of the vehicle to take full advantage of technology -(e.g. increase CL -> Can decrease S -> Decreases D -> Decreases Fuel Consumed -> etc...) This assumes that the physics of the problem remains the
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
A pareto frontier represents points of a non - dominated solution based on preferences

41. What is TCM? What is the size and what value can it take?
Technique for Order Preference by Similarity to Ideal Solution
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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
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

42. What is the equation for present equivalent value? Define variables.
Has a natural zero - is a cardinal scale
Technology space limits
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
PE(i)=?Ft

43. Why are scaling parameters important?
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
(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
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

44. What is satisficing - what is optimizing?
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.

45. What is probability density contour plot
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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

46. What is the equation for the learning curve?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
No way to tell without more information. It depends on the relation between s12+s22 and s32
Regions 1 to 3.

47. What two variables are necessary to define a normal distribution?
Mean and variance
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

48. Write down a formula for a normal distribution
Technique for Order Preference by Similarity to Ideal Solution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

49. 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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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

50. What is the goal of probabilistic design?