ADM

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1. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
(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
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.


2. If you have a two values on a CDF what is the probability of getting a value between them?
P(between B and A)=F(B)-F(A)
Has a natural zero - is a cardinal scale
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


3. TIES Step 6: Identify Technology
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Cumulative Distribution Function
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
(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


4. What can management do to mitigate the risk associated with infusing new technologies?
Technology space limits
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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 sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


5. Ratio scale
Has a natural zero - is a cardinal scale
Technique for Order Preference by Similarity to Ideal Solution
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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


6. What are properties of a CDF?
Range is always between zero and 1 monotonically increasing
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Gaussian Distribution
#=2^n = 2^15


7. What are K- factors applied to?
Technology space limits
To analytically answer 'How much design margin is really necessary?'
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


8. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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 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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


9. TIES Step 8: Selecting Technology

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10. With 15 technologies - what is the number of possible combinations?
PE(i)=?Ft
#=2^n = 2^15
Allows designer to assess feasibility of design
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


11. In what regions of the graph is UTE applicable?
Regions 1 to 3.
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Mean and variance


12. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
#=2^n = 2^15
Range is always between zero and 1 monotonically increasing
It can be continuous or discrete
PE(i)=?Ft


13. 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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
No way to tell without more information. It depends on the relation between s12+s22 and s32
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


14. 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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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


15. Write down a formula for a normal distribution
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.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Gaussian Distribution
(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


16. What two variables are necessary to define a normal distribution?
Sample size is 4 - the sample is the sum of the five dice.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Mean and variance


17. Show and explain a pareto frontier
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
A pareto frontier represents points of a non - dominated solution based on preferences
(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
Does not have a natural zero - is a cardinal scale


18. Does TIES use MADM or MODM? Why?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
CDF= ?_(-8)^8
(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.


19. Why is the normal distribution useful or important?

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20. Why do we use a sample?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)


21. 3 Probabilistic Design Methods
X+Y and X-Y are normally distributed. - (X
(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
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) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration


22. What is another name for a normal distribution?
Mean and variance
Gaussian Distribution
Regions 1 to 3.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration


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

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24. 4 Measures of Dispersion
(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 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
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
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


25. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
No way to tell without more information. It depends on the relation between s12+s22 and s32
Gaussian Distribution


26. What does TOPSIS stand 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)
(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 technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
Technique for Order Preference by Similarity to Ideal Solution


27. Why is learning curve used (or what is it?)
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
To analytically answer 'How much design margin is really necessary?'


28. 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?
The interest i such that 0=PE(i^)
A technique used to determine the best alternative with all interactions between the constraints. Used for product 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
Sample size is 4 - the sample is the sum of the five dice.


29. What is the difference between price and cost?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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
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


30. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Technology space limits


31. TIES Step 1: Problem Definition
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Central limit theorem
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


32. 3 Measures of Central Tendency (& Defs)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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
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


33. What is the equation for the learning curve?
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
It can be continuous or discrete
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


34. What is the goal of probabilistic design?

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35. What is the notation for a standard normal distribution?
X+Y and X-Y are normally distributed. - (X
is bottom- up - you look at certain technologies and see what improvements they offer
Central limit theorem
X~N(0 -1)


36. Name the advantages of UTE.
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.
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) 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
Active UTE (additive) - Product UTE (multiplicative)


37. TIES Step 3: Model and Simulation
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
CDF= ?_(-8)^8
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)


38. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
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
Has a natural zero - is a cardinal scale


39. What is the goal of robust design?

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40. 8 Steps in TIES
Technology space limits
(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
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


41. What can be done about uncertainty in requirement?
(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
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.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


42. TIES Step 2: Design Space Conception
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Determine the design space - baseline Method: Morphological Matrix
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


43. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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)
is bottom- up - you look at certain technologies and see what improvements they offer


44. 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
Active UTE (additive) - Product UTE (multiplicative)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
P(between B and A)=F(B)-F(A)


45. Direct Operating Costs
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
No way to tell without more information. It depends on the relation between s12+s22 and s32
Central limit theorem


46. TIF

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47. How is inflation measured?

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48. What is TCM? What is the size and what value can it take?
is bottom- up - you look at certain technologies and see what improvements they offer
Central limit theorem
(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 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


49. Indirect Operating Cost
Active UTE (additive) - Product UTE (multiplicative)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
Regions 1 to 3.


50. TIES Step 7: Assess Technology
Gaussian Distribution
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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