ADM

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This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.

1. TIES
is bottom- up - you look at certain technologies and see what improvements they offer
Mean and variance
RDTE - Investment/Acquisition - Operations and Support - Disposal
Sample size is 4 - the sample is the sum of the five dice.


2. Weaknesses of TOPSis...
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 technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
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.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


3. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
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
No way to tell without more information. It depends on the relation between s12+s22 and s32
PE(i)=?Ft


4. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
OEC = W1X/Xbsl + W2Nbsl/N
The interest i such that 0=PE(i^)
Technology space limits


5. Define fixed cost and variable cost.
X+Y and X-Y are normally distributed. - (X
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 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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


6. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Sample size is 4 - the sample is the sum of the five dice.


7. With 15 technologies - what is the number of possible combinations?
Determine the design space - baseline Method: Morphological Matrix
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
#=2^n = 2^15
PE(i)=?Ft


8. TIES Step 2: Design Space Conception
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.


9. 3 Probabilistic Design Methods
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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.


10. Does TIES use MADM or MODM? Why?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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
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.


11. If you have a two values on a CDF what is the probability of getting a value between them?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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
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


12. What does CDF stand for?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Cumulative Distribution Function
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
It can be continuous or discrete


13. What does TOPSIS stand for?
X~N(0 -1)
Range is always between zero and 1 monotonically increasing
Technique for Order Preference by Similarity to Ideal Solution
Gaussian Distribution


14. What is the definition of ROI?
The interest i such that 0=PE(i^)
Sample size is 4 - the sample is the sum of the five dice.
Determine the design space - baseline Method: Morphological Matrix
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo


15. What are the parameters for a standard normal distribution?
X+Y and X-Y are normally distributed. - (X
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 =0 Variance =1
Gaussian Distribution


16. TIES Step 8: Selecting Technology

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17. Write down a formula for a normal distribution
P(between B and A)=F(B)-F(A)
Mean and variance
F(x)=1/(s(2p)^(.5) )exp?(-(x-
To analytically answer 'How much design margin is really necessary?'


18. TIES Step 1: Problem Definition
X~N(0 -1)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee


19. What is the definition of inflation?
Allows designer to assess feasibility of design
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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
Gaussian Distribution


20. In what regions of the graph is UTE applicable?
Regions 1 to 3.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Technique for Order Preference by Similarity to Ideal Solution
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


21. What are K- factors applied to?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Technology space limits
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future


22. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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
Cumulative Distribution Function


23. How do you get the CDF from the PDF?
It can be continuous or discrete
CDF= ?_(-8)^8
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
X~N(0 -1)


24. 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.
To analytically answer 'How much design margin is really necessary?'
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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


25. What is the difference between price and cost?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
The interest i such that 0=PE(i^)
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.


26. What is the notation for a standard normal distribution?
X~N(0 -1)
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
Does not have a natural zero - is a cardinal scale
CDF= ?_(-8)^8


27. 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.
(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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.


28. What is the goal of robust design?

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29. What can management do to mitigate the risk associated with infusing new technologies?
No way to tell without more information. It depends on the relation between s12+s22 and s32
To analytically answer 'How much design margin is really necessary?'
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln


30. TIF

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31. What is the equation for the learning curve?
X~N(0 -1)
A pareto frontier represents points of a non - dominated solution based on preferences
Regions 1 to 3.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


32. What is TRL? Range? What does a high TRL mean?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
X~N(0 -1)
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
RDTE - Investment/Acquisition - Operations and Support - Disposal


33. 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?
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.
#=2^n = 2^15
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Sample size is 4 - the sample is the sum of the five dice.


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

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35. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
It can be continuous or discrete
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.


36. 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
is bottom- up - you look at certain technologies and see what improvements they offer
It gives the probability that a value will be met or exceeded.
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


37. What is satisficing - what is optimizing?
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
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.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
To analytically answer 'How much design margin is really necessary?'


38. TIES Step 6: Identify Technology
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Mean =0 Variance =1
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
(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. 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
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.
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


40. What is the goal of probabilistic design?

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41. Why use uniform dist for input variables (Gap Analysis)
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Allows designer to assess feasibility of design
is bottom- up - you look at certain technologies and see what improvements they offer
(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


42. What is the equation for present equivalent value? Define variables.
Mean =0 Variance =1
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
PE(i)=?Ft
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.


43. What is the definition of CDF?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
#=2^n = 2^15
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.


44. What are the different types of UTEs?
Active UTE (additive) - Product UTE (multiplicative)
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
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


45. What is probability density contour plot
Sample size is 4 - the sample is the sum of the five dice.
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
Determine the design space - baseline Method: Morphological Matrix


46. What is another name for a normal distribution?
Gaussian Distribution
(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
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


47. What two variables are necessary to define a normal distribution?
Mean and variance
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
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) End result not intuitive (2) Heavily reliant on weights - which are subjective


48. How is inflation measured?

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49. $/RPM Equation
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Does not have a natural zero - is a cardinal scale
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


50. Show and explain a pareto frontier
Range is always between zero and 1 monotonically increasing
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
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