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 is the definition of inflation?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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. Ratio scale
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
#=2^n = 2^15
Has a natural zero - is a cardinal scale


3. What is the definition of ROI?
(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
The interest i such that 0=PE(i^)
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


4. Direct Operating Costs
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal
(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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)


5. What does CLT stand for?
is bottom- up - you look at certain technologies and see what improvements they offer
Central limit theorem
No way to tell without more information. It depends on the relation between s12+s22 and s32
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


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

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7. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
It can be continuous or discrete
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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


8. What is the equation for the learning curve?
(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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Cumulative Distribution Function
OEC = W1X/Xbsl + W2Nbsl/N


9. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Mean =0 Variance =1
Sample size is 4 - the sample is the sum of the five dice.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space


10. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Sample size is 4 - the sample is the sum of the five dice.
(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


11. Does TIES use MADM or MODM? Why?
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
P(between B and A)=F(B)-F(A)
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
is bottom- up - you look at certain technologies and see what improvements they offer


12. What is the goal of robust design?

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13. TIES Step 1: Problem Definition
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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
PE(i)=?Ft


14. What are the three snapshots of UTE?
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.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
(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


15. Define fixed cost and variable cost.
(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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Cumulative Distribution Function


16. TIES Step 8: Selecting Technology

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17. 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?
Does not have a natural zero - is a cardinal scale
Sample size is 4 - the sample is the sum of the five dice.
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) 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


18. What two variables are necessary to define a normal distribution?
Mean and variance
CDF= ?_(-8)^8
To analytically answer 'How much design margin is really necessary?'
Determine the design space - baseline Method: Morphological Matrix


19. What is the difference between price and cost?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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
(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


20. 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
#=2^n = 2^15
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


21. What is the notation for a standard normal distribution?
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
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
X~N(0 -1)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


22. Why is learning curve used (or what is it?)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Technology space limits
Determine the design space - baseline Method: Morphological Matrix
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.


23. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Central limit theorem
Regions 1 to 3.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
It can be continuous or discrete


24. What is probability density contour plot
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
CDF= ?_(-8)^8
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


25. Why are scaling parameters important?
Technique for Order Preference by Similarity to Ideal Solution
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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Cumulative Distribution Function


26. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
(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
No way to tell without more information. It depends on the relation between s12+s22 and s32


27. Other than infusing technologies - how can you create design space?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
The interest i such that 0=PE(i^)
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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space


28. 4 Measures of Dispersion
Has a natural zero - is a cardinal scale
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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 technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.


29. 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
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 and variance
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


30. What can be done about uncertainty in requirement?
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
Mean and variance
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


31. What are the different types of UTEs?
It gives the probability that a value will be met or exceeded.
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
Does not have a natural zero - is a cardinal scale


32. Why is the normal distribution useful or important?

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33. 3 Probabilistic Design Methods
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
OEC = W1X/Xbsl + W2Nbsl/N
A pareto frontier represents points of a non - dominated solution based on preferences
P(between B and A)=F(B)-F(A)


34. What is the definition of CDF?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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
To analytically answer 'How much design margin is really necessary?'


35. Show and explain a pareto frontier
A pareto frontier represents points of a non - dominated solution based on preferences
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.
No way to tell without more information. It depends on the relation between s12+s22 and s32
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.


36. 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
(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.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


37. What is the normal distribution that results from adding x+y and x[sub]y?
Does not have a natural zero - is a cardinal scale
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
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.


38. 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 =0 Variance =1
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Mean and variance


39. In what regions of the graph is UTE applicable?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
A pareto frontier represents points of a non - dominated solution based on preferences
Regions 1 to 3.
#=2^n = 2^15


40. TIES Step 4: Investigate Design 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.
Gaussian 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.
(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


41. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
is bottom- up - you look at certain technologies and see what improvements they offer
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
Regions 1 to 3.
OEC = W1X/Xbsl + W2Nbsl/N


42. Weaknesses of TOPSis...
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 pareto frontier represents points of a non - dominated solution based on preferences
OEC = W1X/Xbsl + W2Nbsl/N
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


43. Indirect Operating Cost
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Mean and variance
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


44. What can management do to mitigate the risk associated with infusing new technologies?
P(between B and A)=F(B)-F(A)
Regions 1 to 3.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value


45. What is TRL? Range? What does a high TRL mean?
Has a natural zero - is a cardinal scale
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
is bottom- up - you look at certain technologies and see what improvements they offer
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


46. 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
(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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
CDF= ?_(-8)^8


47. TIF

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48. What are K- factors applied to?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Gaussian Distribution
Technology space limits


49. What is another name for a normal distribution?
It can be continuous or discrete
Allows designer to assess feasibility of design
Gaussian Distribution
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space


50. 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.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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.
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.