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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. Define fixed cost and variable cost.
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
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
#=2^n = 2^15

2. 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.
Mean and variance
Gaussian Distribution
(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

3. Why do we use a sample?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

4. What is the notation for a standard normal distribution?
Has a natural zero - is a cardinal scale
(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
Regions 1 to 3.
X~N(0 -1)

5. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
It can be continuous or discrete
Active UTE (additive) - Product UTE (multiplicative)

6. What is another name for a normal distribution?
Gaussian Distribution
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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
PE(i)=?Ft

7. Ratio scale
Has a natural zero - is a cardinal scale
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

8. Does TIES use MADM or MODM? Why?
Has a natural zero - is a cardinal scale
Technique for Order Preference by Similarity to Ideal Solution
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
P(between B and A)=F(B)-F(A)

9. Weaknesses of TOPSis...
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
P(between B and A)=F(B)-F(A)
#=2^n = 2^15

10. 4 Measures of Dispersion
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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
Allows designer to assess feasibility of design
#=2^n = 2^15

11. What is probability density contour plot
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
(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
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
Gaussian Distribution

12. What are properties of a CDF?
The interest i such that 0=PE(i^)
Range is always between zero and 1 monotonically increasing
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
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

13. 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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
X~N(0 -1)
The interest i such that 0=PE(i^)

14. How do you get the CDF from the PDF?
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.
CDF= ?_(-8)^8
A pareto frontier represents points of a non - dominated solution based on preferences
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

15. How is inflation measured?

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16. You have a group of 5 dice. You roll the groups and sum the results of the 5 dice 4 times. What is the sample size? What are you sampling?
Sample size is 4 - the sample is the sum of the five dice.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
(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

17. TIES Step 7: Assess Technology
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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
P(between B and A)=F(B)-F(A)

18. TIES Step 4: Investigate Design Space
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.
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.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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.

19. Why is learning curve used (or what is it?)
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.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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.

20. Name the advantages of UTE.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
CDF= ?_(-8)^8
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.
Allows designer to assess feasibility of design

21. 3 Probabilistic Design Methods
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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) 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.

22. Why is the normal distribution useful or important?

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23. MODM
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.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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
OEC = W1X/Xbsl + W2Nbsl/N

24. What is the difference between price and cost?
Cumulative Distribution Function
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Technique for Order Preference by Similarity to Ideal Solution

25. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
#=2^n = 2^15
OEC = W1X/Xbsl + W2Nbsl/N
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.

26. 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
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 space limits
Cumulative Distribution Function

27. What is the equation for the learning curve?
The interest i such that 0=PE(i^)
Range is always between zero and 1 monotonically increasing
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

28. What is the definition of ROI?
The interest i such that 0=PE(i^)
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
Central limit theorem
X+Y and X-Y are normally distributed. - (X

29. What is the definition of CDF?
Mean and variance
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal

30. TIES Step 1: Problem Definition
Allows designer to assess feasibility of design
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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

31. 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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.

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

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33. Indirect Operating Cost
Has 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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

34. Assumptions Used in TOPSis...
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
It can be continuous or discrete
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Mean =0 Variance =1

35. TIES Step 5: Feasible?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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
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

36. Direct Operating Costs
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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
Sample size is 4 - the sample is the sum of the five dice.
Range is always between zero and 1 monotonically increasing

37. What is TCM? What is the size and what value can it take?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Mean and variance

38. TIES Step 6: Identify Technology
RDTE - Investment/Acquisition - Operations and Support - Disposal
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
(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

39. What are the different types of UTEs?
X~N(0 -1)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
No way to tell without more information. It depends on the relation between s12+s22 and s32
Active UTE (additive) - Product UTE (multiplicative)

40. What is the normal distribution that results from adding x+y and x[sub]y?
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Gaussian Distribution
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
X+Y and X-Y are normally distributed. - (X

41. TIF

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42. Show and explain a pareto frontier
Has a natural zero - is a cardinal scale
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
OEC = W1X/Xbsl + W2Nbsl/N
A pareto frontier represents points of a non - dominated solution based on preferences

43. What is TRL? Range? What does a high TRL mean?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Allows designer to assess feasibility of design
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-

44. interval scale
X+Y and X-Y are normally distributed. - (X
Gaussian Distribution
Mean =0 Variance =1
Does not have a natural zero - is a cardinal scale

45. What does CDF stand for?
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Cumulative Distribution Function
CDF= ?_(-8)^8

46. TIES Step 3: Model and Simulation
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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

47. What is the equation for present equivalent value? Define variables.
Mean and variance
#=2^n = 2^15
(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
PE(i)=?Ft

48. What are K- factors applied to?
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 space limits
Cumulative Distribution Function
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

49. 8 Steps in 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
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.
Central limit theorem
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

50. What are the three snapshots of UTE?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
(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