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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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This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.

1. 3 Measures of Central Tendency (& Defs)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Central limit theorem
Cumulative Distribution Function
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

2. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Regions 1 to 3.
No way to tell without more information. It depends on the relation between s12+s22 and s32
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
OEC = W1X/Xbsl + W2Nbsl/N

3. What are properties of a CDF?
Range is always between zero and 1 monotonically increasing
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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

4. $/RPM Equation
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
OEC = W1X/Xbsl + W2Nbsl/N
It gives the probability that a value will be met or exceeded.
Range is always between zero and 1 monotonically increasing

5. Why is learning curve used (or what is it?)
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.
PE(i)=?Ft
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

6. What is the notation for a standard normal distribution?
X~N(0 -1)
Mean and variance
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Active UTE (additive) - Product UTE (multiplicative)

7. What are the parameters for a standard normal distribution?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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.
Technique for Order Preference by Similarity to Ideal Solution
Mean =0 Variance =1

8. What is the definition of ROI?
Allows designer to assess feasibility of design
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.

9. Indirect Operating Cost
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Central limit theorem
It can be continuous or discrete
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

10. Define fixed cost and variable cost.
Regions 1 to 3.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Sample size is 4 - the sample is the sum of the five dice.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

11. Write down a formula for a normal 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
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.
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.

12. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Technique for Order Preference by Similarity to Ideal Solution

13. Ratio scale
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Has a natural zero - is a cardinal scale
Allows designer to assess feasibility of design
(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

14. What is TCM? What is the size and what value can it take?
#=2^n = 2^15
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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 pareto frontier represents points of a non - dominated solution based on preferences

15. Why is the normal distribution useful or important?

16. What are the different types of UTEs?
Range is always between zero and 1 monotonically increasing
Active UTE (additive) - Product UTE (multiplicative)
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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

17. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Mean and variance
No way to tell without more information. It depends on the relation between s12+s22 and s32
Allows designer to assess feasibility of design
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

18. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
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
Does not have a natural zero - is a cardinal scale
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

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

20. What is the equation for the learning curve?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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
It can be continuous or discrete
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

21. Direct Operating Costs
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Mean =0 Variance =1
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

22. What does TOPSIS stand for?
Technique for Order Preference by Similarity to Ideal Solution
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Gaussian Distribution
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

23. interval scale
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
It can be continuous or discrete
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Does not have a natural zero - is a cardinal scale

24. What are the four difference life cycle costs?
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
RDTE - Investment/Acquisition - Operations and Support - Disposal
CDF= ?_(-8)^8

25. Assumptions Used in TOPSis...
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.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
#=2^n = 2^15

26. 3 Probabilistic Design Methods
It gives the probability that a value will be met or exceeded.
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 Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

27. How do you get the CDF from the PDF?
The interest i such that 0=PE(i^)
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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.

28. TIES Step 8: Selecting Technology

29. What does the CLT state - be specific!
#=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
It gives the probability that a value will be met or exceeded.
CDF= ?_(-8)^8

30. In what regions of the graph is UTE applicable?
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.
Sample size is 4 - the sample is the sum of the five dice.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

31. 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
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
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

32. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Determine the design space - baseline Method: Morphological Matrix

33. What does CLT stand for?
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 Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Central limit theorem
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

34. What is the goal of probabilistic design?

35. Other than infusing technologies - how can you create design space?
Does not have a natural zero - is a cardinal scale
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept 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.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

36. MODM
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: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

37. TIF

38. TIES Step 1: Problem Definition
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.
#=2^n = 2^15
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

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

40. What is satisficing - what is optimizing?
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.
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.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

41. 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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Range is always between zero and 1 monotonically increasing

42. Show and explain a pareto frontier
(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
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
A pareto frontier represents points of a non - dominated solution based on preferences

43. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
CDF= ?_(-8)^8
It can be continuous or discrete

44. 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
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-
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

45. 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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Gaussian Distribution
P(between B and A)=F(B)-F(A)

46. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Has a natural zero - is a cardinal scale
RDTE - Investment/Acquisition - Operations and Support - Disposal

47. Why do we use a sample?
Sample size is 4 - the sample is the sum of the five dice.
No way to tell without more information. It depends on the relation between s12+s22 and s32
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Regions 1 to 3.

48. What two variables are necessary to define a normal distribution?
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.
Gaussian Distribution
Mean and variance
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

49. Name the advantages of UTE.
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
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.
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.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

50. MADM
The interest i such that 0=PE(i^)
(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
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?'