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1. What is the difference between price and cost?
Technique for Order Preference by Similarity to Ideal Solution
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
Cumulative Distribution Function

2. What is the definition of ROI?
A pareto frontier represents points of a non - dominated solution based on preferences
The interest i such that 0=PE(i^)
Allows designer to assess feasibility of design
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

3. 3 Measures of Central Tendency (& Defs)
Active UTE (additive) - Product UTE (multiplicative)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

4. What is another name for a normal distribution?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
PE(i)=?Ft
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Gaussian Distribution

5. TIES Step 8: Selecting Technology

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6. Ratio scale
Has a natural zero - is a cardinal scale
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
Mean =0 Variance =1
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

7. What are the four difference life cycle costs?
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.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
To analytically answer 'How much design margin is really necessary?'
RDTE - Investment/Acquisition - Operations and Support - Disposal

8. Direct Operating Costs
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) End result not intuitive (2) Heavily reliant on weights - which are subjective
Gaussian Distribution
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

9. TIES Step 5: Feasible?
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
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

10. Weaknesses of TOPSis...
PE(i)=?Ft
Does not have a natural zero - is a cardinal scale
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
No way to tell without more information. It depends on the relation between s12+s22 and s32

11. TIES Step 3: Model and Simulation
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Sample size is 4 - the sample is the sum of the five dice.
Range is always between zero and 1 monotonically increasing
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

12. Does TIES use MADM or MODM? Why?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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)
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.

13. TIES Step 2: Design Space Conception
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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.
OEC = W1X/Xbsl + W2Nbsl/N

14. What are the three snapshots of UTE?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(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

15. TIF

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16. 3 Probabilistic Design Methods
(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.
Range is always between zero and 1 monotonically increasing
Mean =0 Variance =1

17. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
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.
Active UTE (additive) - Product UTE (multiplicative)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
#=2^n = 2^15

18. Define fixed cost and variable cost.
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
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
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.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

19. 8 Steps in TIES
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)
(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
No way to tell without more information. It depends on the relation between s12+s22 and s32

20. What are properties of a CDF?
CDF= ?_(-8)^8
RDTE - Investment/Acquisition - Operations and Support - Disposal
Range is always between zero and 1 monotonically increasing
Determine the design space - baseline Method: Morphological Matrix

21. What is the equation for present equivalent value? Define variables.
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.
A pareto frontier represents points of a non - dominated solution based on preferences
PE(i)=?Ft
No way to tell without more information. It depends on the relation between s12+s22 and s32

22. What is the definition of inflation?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
No way to tell without more information. It depends on the relation between s12+s22 and s32
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

23. What does TOPSIS 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
Technique for Order Preference by Similarity to Ideal Solution
(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
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

24. 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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Mean and variance
Technology space limits

25. 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.
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
X+Y and X-Y are normally distributed. - (X
It can be continuous or discrete

26. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
No way to tell without more information. It depends on the relation between s12+s22 and s32
Technique for Order Preference by Similarity to Ideal Solution
The interest i such that 0=PE(i^)

27. interval scale
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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 required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Does not have a natural zero - is a cardinal scale

28. What are the different types of UTEs?
Cumulative Distribution Function
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Active UTE (additive) - Product UTE (multiplicative)
Does not have a natural zero - is a cardinal scale

29. If you have a two values on a CDF what is the probability of getting a value between them?
OEC = W1X/Xbsl + W2Nbsl/N
P(between B and A)=F(B)-F(A)
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

30. Indirect Operating Cost
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

31. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
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.
No way to tell without more information. It depends on the relation between s12+s22 and s32
It gives the probability that a value will be met or exceeded.

32. $/RPM Equation
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
P(between B and A)=F(B)-F(A)
Central limit theorem

33. TIES Step 1: Problem Definition
Has a natural zero - is a cardinal scale
No way to tell without more information. It depends on the relation between s12+s22 and s32
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

34. What does the CLT state - be specific!
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) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

35. Why are scaling parameters important?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
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
Mean and variance

36. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
P(between B and A)=F(B)-F(A)
Cumulative Distribution Function

37. Assumptions Used in TOPSis...
(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
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
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

38. Show and explain a pareto frontier
A pareto frontier represents points of a non - dominated solution based on preferences
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

39. What is the definition of CDF?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Cumulative Distribution Function
It gives the probability that a value will be met or exceeded.
Active UTE (additive) - Product UTE (multiplicative)

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

41. TIES Step 6: Identify Technology
Central limit theorem
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
CDF= ?_(-8)^8
(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

42. What is TCM? What is the size and what value can it take?
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 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
#=2^n = 2^15
Mean and variance

43. Why is learning curve used (or what is it?)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Gaussian Distribution
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

44. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Active UTE (additive) - Product UTE (multiplicative)
A pareto frontier represents points of a non - dominated solution based on preferences
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

45. 4 Measures of Dispersion
PE(i)=?Ft
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
#=2^n = 2^15
To analytically answer 'How much design margin is really necessary?'

46. TIES
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
Regions 1 to 3.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

47. What is the normal distribution that results from adding x+y and x[sub]y?
To analytically answer 'How much design margin is really necessary?'
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
X+Y and X-Y are normally distributed. - (X
X~N(0 -1)

48. Why do we use a sample?
Gaussian Distribution
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
X~N(0 -1)

49. With 15 technologies - what is the number of possible combinations?
Cumulative Distribution Function
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
#=2^n = 2^15
OEC = W1X/Xbsl + W2Nbsl/N

50. What does CLT stand for?
CDF= ?_(-8)^8
Mean =0 Variance =1
Central limit theorem
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

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