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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. What is satisficing - what is optimizing?
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.
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.
Regions 1 to 3.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

2. How do you get the CDF from the PDF?
Sample size is 4 - the sample is the sum of the five dice.
CDF= ?_(-8)^8
Does not have a natural zero - is a cardinal scale
Allows designer to assess feasibility of design

3. What is the definition of CDF?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
It gives the probability that a value will be met or exceeded.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

4. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

5. Show and explain a pareto frontier
Mean and variance
A pareto frontier represents points of a non - dominated solution based on preferences
Central limit theorem
X~N(0 -1)

6. What is the definition of ROI?
The interest i such that 0=PE(i^)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
P(between B and A)=F(B)-F(A)

7. MADM
To analytically answer 'How much design margin is really necessary?'
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
Active UTE (additive) - Product UTE (multiplicative)

8. TIES Step 4: Investigate Design Space
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
is bottom- up - you look at certain technologies and see what improvements they offer
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.

9. What is another name for a normal distribution?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Gaussian Distribution
Does not have a natural zero - is a cardinal scale
The interest i such that 0=PE(i^)

10. In what regions of the graph is UTE applicable?
Regions 1 to 3.
X+Y and X-Y are normally distributed. - (X
To analytically answer 'How much design margin is really necessary?'
Has a natural zero - is a cardinal scale

11. What is the equation for the learning curve?
No way to tell without more information. It depends on the relation between s12+s22 and s32
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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

12. Indirect Operating Cost
X~N(0 -1)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Regions 1 to 3.
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

13. What is the definition of inflation?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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 Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

14. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
The interest i such that 0=PE(i^)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

15. TIES Step 7: Assess 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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Gaussian Distribution
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

16. 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
It can be continuous or discrete
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

17. interval scale
Does not have a natural zero - is a cardinal scale
It gives the probability that a value will be met or exceeded.
Determine the design space - baseline Method: Morphological Matrix
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.

18. TIES Step 1: Problem Definition
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

19. What is TRL? Range? What does a high TRL mean?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
It gives the probability that a value will be met or exceeded.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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

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

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21. TIES Step 8: Selecting Technology

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22. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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

23. If you have a two values on a CDF what is the probability of getting a value between them?
Mean =0 Variance =1
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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)

24. Why use uniform dist for input variables (Gap Analysis)
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Allows designer to assess feasibility of design
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
RDTE - Investment/Acquisition - Operations and Support - Disposal

25. What is TCM? What is the size and what value can it take?
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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
F(x)=1/(s(2p)^(.5) )exp?(-(x-

26. What are the four difference life cycle costs?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal
X+Y and X-Y are normally distributed. - (X

27. What is the equation for present equivalent value? Define variables.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Gaussian Distribution
PE(i)=?Ft

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

29. TIES
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) Easy to compute order of large # of alternatives (2) Gives specific ranking order
is bottom- up - you look at certain technologies and see what improvements they offer
X~N(0 -1)

30. $/RPM Equation
It can be continuous or discrete
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

31. What are K- factors applied to?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
X~N(0 -1)
(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
Technology space limits

32. Strengths of TOPSis...
Gaussian Distribution
Determine the design space - baseline Method: Morphological Matrix
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Active UTE (additive) - Product UTE (multiplicative)

33. 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
It can be continuous or discrete
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

34. TIES Step 2: Design Space Conception
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.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Determine the design space - baseline Method: Morphological Matrix
(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

35. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Central limit theorem
P(between B and A)=F(B)-F(A)

36. 4 Measures of Dispersion
Determine the design space - baseline Method: Morphological Matrix
(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
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

37. What is the difference between price and cost?
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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Has a natural zero - is a cardinal scale
#=2^n = 2^15

38. Ratio 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
CDF= ?_(-8)^8
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Has a natural zero - is a cardinal scale

39. How is inflation measured?

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40. What two variables are necessary to define a normal distribution?
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
Cumulative Distribution Function
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Mean and variance

41. Define fixed cost and variable 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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(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

42. What can be done about uncertainty in requirement?
is bottom- up - you look at certain technologies and see what improvements they offer
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.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

43. What does CDF stand for?
#=2^n = 2^15
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
X+Y and X-Y are normally distributed. - (X
Cumulative Distribution Function

44. What are the three snapshots 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
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
is bottom- up - you look at certain technologies and see what improvements they offer
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

45. What are the different types of UTEs?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Technique for Order Preference by Similarity to Ideal Solution
is bottom- up - you look at certain technologies and see what improvements they offer
Active UTE (additive) - Product UTE (multiplicative)

46. With 15 technologies - what is the number of possible combinations?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
#=2^n = 2^15
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

47. 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?
Does not have a natural zero - is a cardinal scale
Sample size is 4 - the sample is the sum of the five dice.
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

48. 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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
X+Y and X-Y are normally distributed. - (X

49. TIES Step 5: Feasible?
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
Central limit theorem
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

50. 3 Probabilistic Design Methods
OEC = W1X/Xbsl + W2Nbsl/N
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Mean and variance
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration