ADM

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1. TIES Step 8: Selecting Technology

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2. TIES Step 2: Design Space Conception
Gaussian Distribution
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Determine the design space - baseline Method: Morphological Matrix


3. What is the equation for present equivalent value? Define variables.
Mean and variance
It can be continuous or discrete
PE(i)=?Ft
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


4. 3 Probabilistic Design Methods
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Determine the design space - baseline Method: Morphological Matrix


5. Other than infusing technologies - how can you create design space?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
The interest i such that 0=PE(i^)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


6. What can be done about uncertainty in requirement?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Gaussian Distribution
#=2^n = 2^15
It gives the probability that a value will be met or exceeded.


7. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space


8. What is the notation for a standard normal distribution?
X~N(0 -1)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
P(between B and A)=F(B)-F(A)


9. What is the equation for the learning curve?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
PE(i)=?Ft
It can be continuous or discrete


10. What can management do to mitigate the risk associated with infusing new technologies?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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


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

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12. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
P(between B and A)=F(B)-F(A)
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
Mean and variance


13. Why use uniform dist for input variables (Gap Analysis)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Technique for Order Preference by Similarity to Ideal Solution
Allows designer to assess feasibility of design
Mean =0 Variance =1


14. Define fixed cost and variable cost.
Sample size is 4 - the sample is the sum of the five dice.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Gaussian Distribution


15. What is another name for a normal distribution?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
X~N(0 -1)
PE(i)=?Ft
Gaussian Distribution


16. TIES Step 6: Identify Technology
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
Regions 1 to 3.
(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 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


17. TIES
is bottom- up - you look at certain technologies and see what improvements they offer
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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
Gaussian Distribution


18. 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
(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
X+Y and X-Y are normally distributed. - (X
Active UTE (additive) - Product UTE (multiplicative)


19. TIES Step 5: Feasible?
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
PE(i)=?Ft
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


20. Does TIES use MADM or MODM? Why?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
To analytically answer 'How much design margin is really necessary?'
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


21. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
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
is bottom- up - you look at certain technologies and see what improvements they offer
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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


22. 8 Steps in TIES
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.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(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


23. MADM
Sample size is 4 - the sample is the sum of the five dice.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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.


24. What is TCM? What is the size and what value can it take?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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
Technique for Order Preference by Similarity to Ideal Solution
X~N(0 -1)


25. Direct Operating Costs
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


26. With 15 technologies - what is the number of possible combinations?
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
PE(i)=?Ft
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
#=2^n = 2^15


27. TIES Step 7: Assess Technology
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Mean and variance
Active UTE (additive) - Product UTE (multiplicative)
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


28. What are the four difference life cycle costs?
(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
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
RDTE - Investment/Acquisition - Operations and Support - Disposal


29. What are the different types of UTEs?
Active UTE (additive) - Product UTE (multiplicative)
(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 and variance
Technique for Order Preference by Similarity to Ideal Solution


30. 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?
PE(i)=?Ft
Sample size is 4 - the sample is the sum of the five dice.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee


31. Write down a formula for a normal distribution
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
F(x)=1/(s(2p)^(.5) )exp?(-(x-


32. What two variables are necessary to define a normal distribution?
Has a natural zero - is a cardinal scale
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
Mean and variance


33. What is satisficing - what is optimizing?
Range is always between zero and 1 monotonically increasing
X+Y and X-Y are normally distributed. - (X
(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
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.


34. What is the goal of probabilistic design?

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35. $/RPM Equation
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
It gives the probability that a value will be met or exceeded.


36. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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


37. Ratio scale
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Central limit theorem
Cumulative Distribution Function
Has a natural zero - is a cardinal scale


38. What does the CLT state - be specific!
Mean and variance
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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) 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


39. 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
It gives the probability that a value will be met or exceeded.
Range is always between zero and 1 monotonically increasing
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)


40. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
CDF= ?_(-8)^8
Technology space limits
It can be continuous or discrete
RDTE - Investment/Acquisition - Operations and Support - Disposal


41. interval scale
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Mean =0 Variance =1
Does not have a natural zero - is a cardinal scale
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.


42. What is the definition of inflation?
A pareto frontier represents points of a non - dominated solution based on preferences
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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
Allows designer to assess feasibility of design


43. Strengths of TOPSis...
The interest i such that 0=PE(i^)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
(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.


44. Why is learning curve used (or what is it?)
Does not have a natural zero - is a cardinal scale
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Allows designer to assess feasibility of design
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


45. Why is the normal distribution useful or important?

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46. What does CDF stand for?
Cumulative Distribution Function
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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


47. What are the parameters for a standard normal distribution?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Mean =0 Variance =1
P(between B and A)=F(B)-F(A)


48. 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
X+Y and X-Y are normally distributed. - (X
It gives the probability that a value will be met or exceeded.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)


49. What is the goal of robust design?

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50. How is inflation measured?

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