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1. Write down a formula for a normal distribution
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-
OEC = W1X/Xbsl + W2Nbsl/N
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln


2. What does the CLT state - be specific!
P(between B and A)=F(B)-F(A)
It gives the probability that a value will be met or exceeded.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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


3. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
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 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
(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


4. TIES Step 6: Identify Technology
OEC = W1X/Xbsl + W2Nbsl/N
(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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


5. 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
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.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Has a natural zero - is a cardinal scale


6. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
(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
It can be continuous or discrete
A pareto frontier represents points of a non - dominated solution based on preferences
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee


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

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8. What can management do to mitigate the risk associated with infusing new technologies?
Technology space limits
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)


9. What are the three snapshots of UTE?
Technique for Order Preference by Similarity to Ideal Solution
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
(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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


10. interval scale
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Does not have a natural zero - is a cardinal scale
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'


11. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
X~N(0 -1)
Allows designer to assess feasibility of design
OEC = W1X/Xbsl + W2Nbsl/N
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. TIES Step 4: Investigate Design Space
No way to tell without more information. It depends on the relation between s12+s22 and s32
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept 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.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future


13. 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.
No way to tell without more information. It depends on the relation between s12+s22 and s32
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


14. Why do we use a sample?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


15. MADM
To analytically answer 'How much design margin is really necessary?'
RDTE - Investment/Acquisition - Operations and Support - Disposal
Mean and variance
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.


16. How is inflation measured?

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17. Weaknesses of TOPSis...
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
PE(i)=?Ft


18. Direct Operating Costs
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
(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


19. What does CLT stand for?
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
Central limit theorem
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Cumulative Distribution Function


20. What are the parameters for a standard normal distribution?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
The interest i such that 0=PE(i^)
Active UTE (additive) - Product UTE (multiplicative)
Mean =0 Variance =1


21. 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?
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.
Sample size is 4 - the sample is the sum of the five dice.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


22. What is the definition of CDF?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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
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


23. Why is the normal distribution useful or important?

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24. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
is bottom- up - you look at certain technologies and see what improvements they offer


25. What is the definition of ROI?
The interest i such that 0=PE(i^)
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
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)


26. Why use uniform dist for input variables (Gap Analysis)
Central limit theorem
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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
Allows designer to assess feasibility of design


27. 4 Measures of Dispersion
It can be continuous or discrete
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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
A pareto frontier represents points of a non - dominated solution based on preferences


28. What is the notation for a standard normal distribution?
To analytically answer 'How much design margin is really necessary?'
X~N(0 -1)
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


29. Strengths of TOPSis...
A pareto frontier represents points of a non - dominated solution based on preferences
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
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
#=2^n = 2^15


30. What is the definition of inflation?
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.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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
RDTE - Investment/Acquisition - Operations and Support - Disposal


31. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
It gives the probability that a value will be met or exceeded.
Has a natural zero - is a cardinal scale
It can be continuous or discrete


32. What is the normal distribution that results from adding x+y and x[sub]y?
Active UTE (additive) - Product UTE (multiplicative)
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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. 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
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.
A pareto frontier represents points of a non - dominated solution based on preferences


34. What is another name for a normal distribution?
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.
Gaussian Distribution
Mean and variance
Mean =0 Variance =1


35. What is the goal of robust design?

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36. What are properties of a CDF?
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
Range is always between zero and 1 monotonically increasing
is bottom- up - you look at certain technologies and see what improvements they offer
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee


37. 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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
OEC = W1X/Xbsl + W2Nbsl/N
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.


38. Define fixed cost and variable cost.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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.
Determine the design space - baseline Method: Morphological Matrix
Gaussian Distribution


39. What can be done about uncertainty in requirement?
Has a natural zero - is a cardinal scale
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 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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


40. What is TRL? Range? What does a high TRL mean?
It can be continuous or discrete
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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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


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


42. Does TIES use MADM or MODM? Why?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Range is always between zero and 1 monotonically increasing
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


43. What is the goal of probabilistic design?

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44. TIF

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45. What are the different types of UTEs?
Range is always between zero and 1 monotonically increasing
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 Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Active UTE (additive) - Product UTE (multiplicative)


46. Name the advantages of UTE.
X~N(0 -1)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
A pareto frontier represents points of a non - dominated solution based on preferences
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.


47. Other than infusing technologies - how can you create design space?
A pareto frontier represents points of a non - dominated solution based on preferences
is bottom- up - you look at certain technologies and see what improvements they offer
X+Y and X-Y are normally distributed. - (X
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space


48. In what regions of the graph is UTE applicable?
Regions 1 to 3.
RDTE - Investment/Acquisition - Operations and Support - Disposal
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


49. MODM
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.
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.


50. 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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Central limit theorem
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline