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. What does CDF stand for?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Cumulative Distribution Function
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration


2. interval scale
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.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Mean =0 Variance =1


3. TIES Step 6: Identify Technology
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.
Mean =0 Variance =1
(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
(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. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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.
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
RDTE - Investment/Acquisition - Operations and Support - Disposal


5. What is the normal distribution that results from adding x+y and x[sub]y?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
X+Y and X-Y are normally distributed. - (X
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


6. What is the goal of robust design?

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7. What does the CLT state - be specific!
(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
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
P(between B and A)=F(B)-F(A)


8. In what regions of the graph is UTE applicable?
Regions 1 to 3.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


9. 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?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
(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
Sample size is 4 - the sample is the sum of the five dice.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo


10. MODM
Mean =0 Variance =1
CDF= ?_(-8)^8
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 used to determine the best alternative with all interactions between the constraints. Used for product design.


11. Direct Operating Costs
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)
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


12. Does TIES use MADM or MODM? Why?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
(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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Regions 1 to 3.


13. What is the goal of probabilistic design?

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14. What is the definition of ROI?
X+Y and X-Y are normally distributed. - (X
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
Has a natural zero - is a cardinal scale
The interest i such that 0=PE(i^)


15. Why is the normal distribution useful or important?

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16. What is TCM? What is the size and what value can it take?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Technique for Order Preference by Similarity to Ideal Solution
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


17. TIF

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18. Define fixed cost and variable cost.
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 technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
Central limit theorem
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


19. What two variables are necessary to define 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.
PE(i)=?Ft
Sample size is 4 - the sample is the sum of the five dice.
Mean and variance


20. MADM
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 technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
Active UTE (additive) - Product UTE (multiplicative)
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)


21. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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?'
(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


22. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
To analytically answer 'How much design margin is really necessary?'
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(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. What is the notation for a standard normal distribution?
X~N(0 -1)
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.
CDF= ?_(-8)^8
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


24. What are K- factors applied to?
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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Technology space limits


25. What is satisficing - what is optimizing?
Active UTE (additive) - Product UTE (multiplicative)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


26. What are the different types of UTEs?
Active UTE (additive) - Product UTE (multiplicative)
is bottom- up - you look at certain technologies and see what improvements they offer
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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


27. Assumptions Used in TOPSis...
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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)


28. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


29. What is the difference between price and cost?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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


30. Indirect Operating Cost
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
It can be continuous or discrete
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value


31. What are the four difference life cycle costs?
OEC = W1X/Xbsl + W2Nbsl/N
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal


32. What are the three snapshots of UTE?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
No way to tell without more information. It depends on the relation between s12+s22 and s32
(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


33. What is the equation for the learning curve?
#=2^n = 2^15
Technology space limits
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Sample size is 4 - the sample is the sum of the five dice.


34. 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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Technique for Order Preference by Similarity to Ideal Solution
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


35. TIES Step 4: Investigate Design 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
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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)


36. TIES Step 8: Selecting Technology

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37. Strengths of TOPSis...
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
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Determine the design space - baseline Method: Morphological Matrix
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order


38. 8 Steps in TIES
(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
X+Y and X-Y are normally distributed. - (X
Regions 1 to 3.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value


39. TIES Step 7: Assess 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.
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.
It gives the probability that a value will be met or exceeded.


40. Weaknesses of TOPSis...
Regions 1 to 3.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
P(between B and A)=F(B)-F(A)


41. What is the equation for present equivalent value? Define variables.
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
PE(i)=?Ft
Mean and variance
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem


42. How do you get the CDF from the PDF?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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
Mean =0 Variance =1


43. What is the definition of inflation?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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
#=2^n = 2^15
X+Y and X-Y are normally distributed. - (X


44. 3 Measures of Central Tendency (& Defs)
To analytically answer 'How much design margin is really necessary?'
Sample size is 4 - the sample is the sum of the five dice.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)


45. What is another name for a normal distribution?
Gaussian Distribution
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
To analytically answer 'How much design margin is really necessary?'
(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


46. Why use uniform dist for input variables (Gap Analysis)
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo


47. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
(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
OEC = W1X/Xbsl + W2Nbsl/N
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


48. What does TOPSIS stand for?
Determine the design space - baseline Method: Morphological Matrix
The interest i such that 0=PE(i^)
Technique for Order Preference by Similarity to Ideal Solution
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)


49. 4 Measures of Dispersion
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
Mean =0 Variance =1
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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


50. What are the parameters for a standard 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.
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
Cumulative Distribution Function
Mean =0 Variance =1