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ADM

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1. Does TIES use MADM or MODM? Why?
(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
The interest i such that 0=PE(i^)
(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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

2. What is the equation for the learning curve?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

3. What is probability density contour plot
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
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)

4. If you have a two values on a CDF what is the probability of getting a value between them?
#=2^n = 2^15
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.
P(between B and A)=F(B)-F(A)
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

5. Weaknesses of TOPSis...
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.

6. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
No way to tell without more information. It depends on the relation between s12+s22 and s32
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

7. What is the goal of probabilistic design?

8. What does the CLT state - be specific!
Technique for Order Preference by Similarity to Ideal Solution
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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
Sample size is 4 - the sample is the sum of the five dice.

9. What does CDF stand for?
#=2^n = 2^15
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
PE(i)=?Ft
Cumulative Distribution Function

10. 4 Measures of Dispersion
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
P(between B and A)=F(B)-F(A)
Range is always between zero and 1 monotonically increasing
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

11. What is the definition of ROI?
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.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
The interest i such that 0=PE(i^)
Regions 1 to 3.

12. What is the definition of CDF?
Active UTE (additive) - Product UTE (multiplicative)
X~N(0 -1)
It gives the probability that a value will be met or exceeded.
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. What is the goal of robust design?

14. 8 Steps in TIES
P(between B and A)=F(B)-F(A)
(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) 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)

15. Assumptions Used in TOPSis...
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.
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
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

16. Why are scaling parameters important?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Mean =0 Variance =1
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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

17. What is TRL? Range? What does a high TRL mean?
RDTE - Investment/Acquisition - Operations and Support - Disposal
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 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
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

18. interval scale
Does not have a natural zero - is a cardinal scale
is bottom- up - you look at certain technologies and see what improvements they offer
X~N(0 -1)
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

19. Why is the normal distribution useful or important?

20. What are the four difference life cycle costs?
RDTE - Investment/Acquisition - Operations and Support - Disposal
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) End result not intuitive (2) Heavily reliant on weights - which are subjective

21. What two variables are necessary to define a normal distribution?
Mean and variance
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.
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.

22. Why do we use a sample?
Has a natural zero - is a cardinal scale
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
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

23. What is satisficing - what is optimizing?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept 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
X~N(0 -1)
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.

24. What is the difference between price and cost?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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
CDF= ?_(-8)^8

25. 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
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(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 pareto frontier represents points of a non - dominated solution based on preferences

26. Why is learning curve used (or what is it?)
(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
It gives the probability that a value will be met or exceeded.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Active UTE (additive) - Product UTE (multiplicative)

27. TIES Step 4: Investigate Design Space
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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 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.

28. 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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Mean and variance
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

29. 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.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Allows designer to assess feasibility of design
Central limit theorem

30. In what regions of the graph is UTE applicable?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Regions 1 to 3.
Technology space limits

31. What is the equation for present equivalent value? Define variables.
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
PE(i)=?Ft
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.

32. What can be done about uncertainty in requirement?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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
is bottom- up - you look at certain technologies and see what improvements they offer

33. 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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
Sample size is 4 - the sample is the sum of the five dice.

34. Other than infusing technologies - how can you create design space?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

35. Indirect Operating Cost
Technology space limits
Allows designer to assess feasibility of design
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

36. Ratio scale
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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.
Has a natural zero - is a cardinal scale
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

37. TIES Step 8: Selecting Technology

38. How do you get the CDF from the PDF?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
CDF= ?_(-8)^8
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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

39. How is inflation measured?

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

41. TIES Step 1: Problem Definition
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Determine the design space - baseline Method: Morphological Matrix
(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
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

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

43. TIES Step 6: Identify Technology
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
Central limit theorem
The interest i such that 0=PE(i^)

44. $/RPM Equation
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
P(between B and A)=F(B)-F(A)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

45. 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?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
It can be continuous or discrete
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Sample size is 4 - the sample is the sum of the five dice.

46. Write down a formula for a normal distribution
Cumulative Distribution Function
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

47. 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
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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

48. TIES Step 7: Assess Technology
Central limit theorem
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

49. TIF

50. 3 Probabilistic Design Methods
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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.
#=2^n = 2^15