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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. 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
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
CDF= ?_(-8)^8
P(between B and A)=F(B)-F(A)

2. What are properties of a CDF?
Range is always between zero and 1 monotonically increasing
is bottom- up - you look at certain technologies and see what improvements they offer
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Regions 1 to 3.

3. What are K- factors applied to?
Technology space limits
The interest i such that 0=PE(i^)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

4. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
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.
Sample size is 4 - the sample is the sum of the five dice.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

5. What is the normal distribution that results from adding x+y and x[sub]y?
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
X+Y and X-Y are normally distributed. - (X
A pareto frontier represents points of a non - dominated solution based on preferences

6. What are the three snapshots of UTE?
PE(i)=?Ft
(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)
Does not have a natural zero - is a cardinal scale

7. Other than infusing technologies - how can you create design space?
(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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Does not have a natural zero - is a cardinal scale
Allows designer to assess feasibility of design

8. Direct Operating Costs
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.
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

9. interval scale
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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
P(between B and A)=F(B)-F(A)

10. What can management do to mitigate the risk associated with infusing new technologies?
A pareto frontier represents points of a non - dominated solution based on preferences
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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) End result not intuitive (2) Heavily reliant on weights - which are subjective

11. With 15 technologies - what is the number of possible combinations?
(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
#=2^n = 2^15
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 technique used to determine the best alternative with all interactions between the constraints. Used for product design.

12. 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.
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
Central limit theorem

13. What are the four difference life cycle costs?
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
RDTE - Investment/Acquisition - Operations and Support - Disposal
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.
F(x)=1/(s(2p)^(.5) )exp?(-(x-

14. 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)
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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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

15. Name the advantages 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
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.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Allows designer to assess feasibility of design

16. 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)
Range is always between zero and 1 monotonically increasing
No way to tell without more information. It depends on the relation between s12+s22 and s32
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.

17. 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
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
Has a natural zero - is a cardinal scale
The interest i such that 0=PE(i^)

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

19. In what regions of the graph is UTE applicable?
Active UTE (additive) - Product UTE (multiplicative)
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.
Allows designer to assess feasibility of design
Regions 1 to 3.

20. TIES Step 1: Problem Definition
X~N(0 -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.
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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

21. What is the notation for a standard normal distribution?
X~N(0 -1)
Mean =0 Variance =1
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

22. What is TCM? What is the size and what value can it take?
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 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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Allows designer to assess feasibility of design

23. What is the difference between price and cost?
(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: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
#=2^n = 2^15
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

24. What can be done about uncertainty in requirement?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
It gives the probability that a value will be met or exceeded.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

25. What is another name for a normal distribution?
Gaussian Distribution
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
The interest i such that 0=PE(i^)

26. What are the different types of UTEs?
It gives the probability that a value will be met or exceeded.
Technique for Order Preference by Similarity to Ideal Solution
Active UTE (additive) - Product UTE (multiplicative)
Mean =0 Variance =1

27. TIES Step 3: Model and Simulation
(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
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.
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
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

28. Why do we use a sample?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Mean and variance

29. MADM
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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.

30. Why use uniform dist for input variables (Gap Analysis)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Allows designer to assess feasibility of design
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

31. How do you get the CDF from the PDF?
is bottom- up - you look at certain technologies and see what improvements they offer
CDF= ?_(-8)^8
It gives the probability that a value will be met or exceeded.
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

32. 3 Measures of Central Tendency (& Defs)
It gives the probability that a value will be met or exceeded.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

33. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Does not have a natural zero - is a cardinal scale
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
OEC = W1X/Xbsl + W2Nbsl/N
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. How is inflation measured?

35. 8 Steps in TIES
X+Y and X-Y are normally distributed. - (X
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Mean =0 Variance =1
(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

36. Does TIES use MADM or MODM? Why?
(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.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
PE(i)=?Ft

37. What is TRL? Range? What does a high TRL mean?
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
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
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 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. What is the equation for present equivalent value? Define variables.
Technique for Order Preference by Similarity to Ideal Solution
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
PE(i)=?Ft
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

39. What is the goal of robust design?

40. TIES Step 5: Feasible?
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.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

41. 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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
P(between B and A)=F(B)-F(A)
Technology space limits

42. Indirect Operating Cost
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.
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
Mean =0 Variance =1
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

43. Assumptions Used in TOPSis...
Range is always between zero and 1 monotonically increasing
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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
P(between B and A)=F(B)-F(A)

44. Why is the normal distribution useful or important?

45. Why is learning curve used (or what is it?)
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
Has a natural zero - is a cardinal scale
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

46. 4 Measures of Dispersion
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.
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.
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

47. MODM
Regions 1 to 3.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Technology space limits
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

48. What does CLT stand for?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Central limit theorem
CDF= ?_(-8)^8

49. 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
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

50. $/RPM Equation
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) 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
No way to tell without more information. It depends on the relation between s12+s22 and s32