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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. Show and explain a pareto frontier
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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

2. 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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

3. 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
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

4. Why use uniform dist for input variables (Gap Analysis)
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.
Regions 1 to 3.
Allows designer to assess feasibility of design
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

5. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

6. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
F(x)=1/(s(2p)^(.5) )exp?(-(x-

7. What can management do to mitigate the risk associated with infusing new technologies?
Determine the design space - baseline Method: Morphological Matrix
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Sample size is 4 - the sample is the sum of the five dice.

8. If you have a two values on a CDF what is the probability of getting a value between them?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
P(between B and A)=F(B)-F(A)
It gives the probability that a value will be met or exceeded.
To analytically answer 'How much design margin is really necessary?'

9. How is inflation measured?

10. Indirect Operating Cost
(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
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

11. Other than infusing technologies - how can you create design space?
X~N(0 -1)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

12. 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?
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
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
Does not have a natural zero - is a cardinal scale
Sample size is 4 - the sample is the sum of the five dice.

13. MADM
It gives the probability that a value will be met or exceeded.
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.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

14. What is the normal distribution that results from adding x+y and x[sub]y?
X+Y and X-Y are normally distributed. - (X
(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)
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

15. What is TCM? What is the size and what value can it take?
Determine the design space - baseline Method: Morphological Matrix
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
Does not have a natural zero - is a cardinal scale
Technology space limits

16. What does CLT stand for?
The interest i such that 0=PE(i^)
Cumulative Distribution Function
Central limit theorem
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

17. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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.
Sample size is 4 - the sample is the sum of the five dice.

18. What does TOPSIS stand for?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Active UTE (additive) - Product UTE (multiplicative)
Technique for Order Preference by Similarity to Ideal Solution

19. TIF

20. What can be done about uncertainty in requirement?
(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.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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

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.
(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
Has a natural zero - is a cardinal scale
Allows designer to assess feasibility of design

22. 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
(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
Does not have a natural zero - is a cardinal scale
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

23. 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
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
Regions 1 to 3.
is bottom- up - you look at certain technologies and see what improvements they offer

24. interval scale
Regions 1 to 3.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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.
Does not have a natural zero - is a cardinal scale

25. TIES Step 4: Investigate Design Space
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
No way to tell without more information. It depends on the relation between s12+s22 and s32
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.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

26. TIES Step 1: Problem Definition
P(between B and A)=F(B)-F(A)
is bottom- up - you look at certain technologies and see what improvements they offer
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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.

27. What is the definition of CDF?
is bottom- up - you look at certain technologies and see what improvements they offer
It gives the probability that a value will be met or exceeded.
RDTE - Investment/Acquisition - Operations and Support - Disposal
X+Y and X-Y are normally distributed. - (X

28. TIES Step 7: Assess Technology
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. 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
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.

29. What is the definition of inflation?
To analytically answer 'How much design margin is really necessary?'
Central limit theorem
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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

30. What is another name for a normal distribution?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
CDF= ?_(-8)^8
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Gaussian Distribution

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

32. What is TRL? Range? What does a high TRL mean?
Sample size is 4 - the sample is the sum of the five dice.
Does not have a natural zero - is a cardinal scale
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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

33. 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
Active UTE (additive) - Product UTE (multiplicative)
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

34. Direct Operating Costs
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

35. What is the goal of probabilistic design?

36. Why is learning curve used (or what is it?)
Determine the design space - baseline Method: Morphological Matrix
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Technology space limits

37. 3 Measures of Central Tendency (& Defs)
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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

38. Why do we use a sample?
Central limit theorem
It can be continuous or discrete
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: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee

39. TIES Step 2: Design Space Conception
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Technology space limits
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Determine the design space - baseline Method: Morphological Matrix

40. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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

41. What are properties of a CDF?
To analytically answer 'How much design margin is really necessary?'
No way to tell without more information. It depends on the relation between s12+s22 and s32
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

42. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Technique for Order Preference by Similarity to Ideal Solution
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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
No way to tell without more information. It depends on the relation between s12+s22 and s32

43. TIES Step 3: Model and Simulation
Does not have a natural zero - is a cardinal scale
No way to tell without more information. It depends on the relation between s12+s22 and s32
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

44. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
PE(i)=?Ft
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

45. What are K- factors applied to?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Technology space limits
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

46. 8 Steps in TIES
PE(i)=?Ft
(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
#=2^n = 2^15
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.

47. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
(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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
X+Y and X-Y are normally distributed. - (X

48. 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.
Does not have a natural zero - is a cardinal scale
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
X+Y and X-Y are normally distributed. - (X

49. 3 Probabilistic Design Methods
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Active UTE (additive) - Product UTE (multiplicative)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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

50. What is the notation for a standard normal distribution?
X~N(0 -1)
Technology space limits
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
RDTE - Investment/Acquisition - Operations and Support - Disposal