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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.
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.
#=2^n = 2^15

2. 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)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
X+Y and X-Y are normally distributed. - (X
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

3. What is the goal of probabilistic design?

4. What is the normal distribution that results from adding x+y and x[sub]y?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
X+Y and X-Y are normally distributed. - (X
Allows designer to assess feasibility of design
(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

5. TIES Step 6: Identify Technology
is bottom- up - you look at certain technologies and see what improvements they offer
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
(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
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

6. What are the four difference life cycle costs?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

7. What are the different types of UTEs?
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
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
Technology space limits
Active UTE (additive) - Product UTE (multiplicative)

8. $/RPM Equation
OEC = W1X/Xbsl + W2Nbsl/N
P(between B and A)=F(B)-F(A)
(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

9. Assumptions Used in TOPSis...
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
is bottom- up - you look at certain technologies and see what improvements they offer
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

10. What is TRL? Range? What does a high TRL mean?
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

11. 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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Cumulative Distribution Function

12. What can management do to mitigate the risk associated with infusing new technologies?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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

13. 4 Measures of Dispersion
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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
X+Y and X-Y are normally distributed. - (X

14. Why are scaling parameters important?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Active UTE (additive) - Product UTE (multiplicative)
Central limit theorem
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

15. TIES Step 7: Assess Technology
CDF= ?_(-8)^8
Has a natural zero - is a cardinal scale
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

16. Other than infusing technologies - how can you create design space?
Does not have a natural zero - is a cardinal scale
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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

17. What two variables are necessary to define a 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
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.
Mean and variance

18. Show and explain a pareto frontier
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.
A pareto frontier represents points of a non - dominated solution based on preferences
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

19. Write down a formula for a normal distribution
#=2^n = 2^15
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

20. Why is learning curve used (or what is it?)
P(between B and A)=F(B)-F(A)
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
It gives the probability that a value will be met or exceeded.
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

21. 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.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Active UTE (additive) - Product UTE (multiplicative)
(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

22. 3 Measures of Central Tendency (& Defs)
Range is always between zero and 1 monotonically increasing
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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.

23. interval scale
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
Does not have a natural zero - is a cardinal scale

24. TIES Step 3: Model and Simulation
Technology space limits
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 related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
is bottom- up - you look at certain technologies and see what improvements they offer

25. What does CDF stand for?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Cumulative Distribution Function
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

26. Name the advantages of UTE.
The interest i such that 0=PE(i^)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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.

27. TIF

28. TIES Step 5: Feasible?
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

29. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
A pareto frontier represents points of a non - dominated solution based on preferences
Regions 1 to 3.
No way to tell without more information. It depends on the relation between s12+s22 and s32

30. What is the goal of robust design?

31. 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?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
CDF= ?_(-8)^8
Sample size is 4 - the sample is the sum of the five dice.
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

32. TIES Step 2: Design Space Conception
X~N(0 -1)
Determine the design space - baseline Method: Morphological Matrix
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.
Central limit theorem

33. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

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

35. What is the notation for a standard normal distribution?
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)
X~N(0 -1)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

36. What are K- factors applied to?
Technology space limits
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 that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.

37. MODM
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
A technique used to determine the best alternative with all interactions between the constraints. Used for product 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

38. What are properties of a CDF?
No way to tell without more information. It depends on the relation between s12+s22 and s32
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
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

39. 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
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
(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

40. How is inflation measured?

41. TIES
(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 bottom- up - you look at certain technologies and see what improvements they offer
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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

42. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
To analytically answer 'How much design margin is really necessary?'
OEC = W1X/Xbsl + W2Nbsl/N
Sample size is 4 - the sample is the sum of the five dice.
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

43. What is the equation for the learning curve?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

44. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

45. Why do we use a sample?
Range is always between zero and 1 monotonically increasing
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
A pareto frontier represents points of a non - dominated solution based on preferences
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

46. TIES Step 1: Problem Definition
Active UTE (additive) - Product UTE (multiplicative)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
#=2^n = 2^15
P(between B and A)=F(B)-F(A)

47. Ratio scale
Has a natural zero - is a cardinal scale
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Mean and variance
A pareto frontier represents points of a non - dominated solution based on preferences

48. Direct Operating Costs
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
RDTE - Investment/Acquisition - Operations and Support - Disposal
#=2^n = 2^15

49. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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.

50. In what regions of the graph is UTE applicable?
Sample size is 4 - the sample is the sum of the five dice.
Regions 1 to 3.
PE(i)=?Ft
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo