ADM

Instructions:

• Answer 50 questions in 15 minutes.
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• Match each statement with the correct term.
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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. Why is the normal distribution useful or important?

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2. Strengths of TOPSis...
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) Easy to compute order of large # of alternatives (2) Gives specific ranking order
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
#=2^n = 2^15


3. TIES Step 2: Design Space Conception
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Determine the design space - baseline Method: Morphological Matrix
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


4. 8 Steps in TIES
Range is always between zero and 1 monotonically increasing
To analytically answer 'How much design margin is really necessary?'
Cumulative Distribution Function
(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


5. TIES Step 6: Identify Technology
Determine the design space - baseline Method: Morphological Matrix
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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo


6. Why are scaling parameters important?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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
Regions 1 to 3.
PE(i)=?Ft


7. What two variables are necessary to define a normal distribution?
Mean and variance
RDTE - Investment/Acquisition - Operations and Support - Disposal
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


8. What is the definition of CDF?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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.
It gives the probability that a value will be met or exceeded.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


9. MODM
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
P(between B and A)=F(B)-F(A)
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
To analytically answer 'How much design margin is really necessary?'


10. If you have a two values on a CDF what is the probability of getting a value between them?
P(between B and A)=F(B)-F(A)
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
Regions 1 to 3.
To analytically answer 'How much design margin is really necessary?'


11. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
F(x)=1/(s(2p)^(.5) )exp?(-(x-
The interest i such that 0=PE(i^)
Technology space limits


12. $/RPM Equation
Active UTE (additive) - Product UTE (multiplicative)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(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
Cumulative Distribution Function


13. 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
Regions 1 to 3.
Mean =0 Variance =1
Technique for Order Preference by Similarity to Ideal Solution


14. Ratio scale
Has a natural zero - is a cardinal scale
#=2^n = 2^15
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
A pareto frontier represents points of a non - dominated solution based on preferences


15. In what regions of the graph is UTE applicable?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Regions 1 to 3.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Has a natural zero - is a cardinal scale


16. interval scale
Does not have a natural zero - is a cardinal scale
Sample size is 4 - the sample is the sum of the five dice.
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.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


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?
Active UTE (additive) - Product UTE (multiplicative)
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) 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
Sample size is 4 - the sample is the sum of the five dice.


18. 3 Measures of Central Tendency (& Defs)
(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.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value


19. What is another name for a normal distribution?
Gaussian Distribution
(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)
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


20. What is TCM? What is the size and what value can it take?
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.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Cumulative Distribution Function
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


21. What is TRL? Range? What does a high TRL mean?
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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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


22. What can be done about uncertainty in requirement?
Does not have a natural zero - is a cardinal scale
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
OEC = W1X/Xbsl + W2Nbsl/N
Gaussian Distribution


23. What are K- factors applied to?
#=2^n = 2^15
Technology space limits
RDTE - Investment/Acquisition - Operations and Support - Disposal
Mean and variance


24. Show and explain a pareto frontier
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
OEC = W1X/Xbsl + W2Nbsl/N
A pareto frontier represents points of a non - dominated solution based on preferences
Technique for Order Preference by Similarity to Ideal Solution


25. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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
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.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


26. What is the definition of inflation?
The interest i such that 0=PE(i^)
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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future


27. What is the definition of ROI?
The interest i such that 0=PE(i^)
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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.
Has a natural zero - is a cardinal scale


28. 4 Measures of Dispersion
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.
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
Does not have a natural zero - is a cardinal scale
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.


29. Assumptions Used in TOPSis...
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Gaussian Distribution
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


30. 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.
Gaussian Distribution
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem


31. TIF

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32. What does CDF stand for?
Allows designer to assess feasibility of design
Cumulative Distribution Function
X~N(0 -1)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo


33. What is the goal of probabilistic design?

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34. 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
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
It can be continuous or discrete
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


35. Name the advantages of UTE.
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.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
Has a natural zero - is a cardinal scale


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

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37. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
The interest i such that 0=PE(i^)
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
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)


38. What is the equation for the learning curve?
No way to tell without more information. It depends on the relation between s12+s22 and s32
is bottom- up - you look at certain technologies and see what improvements they offer
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


39. TIES Step 1: Problem Definition
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
X~N(0 -1)
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD


40. What can management do to mitigate the risk associated with infusing new technologies?
PE(i)=?Ft
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
P(between B and A)=F(B)-F(A)
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)


41. How is inflation measured?

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42. TIES
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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.


43. 3 Probabilistic Design Methods
Determine the design space - baseline Method: Morphological Matrix
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration


44. Define fixed cost and variable cost.
Active UTE (additive) - Product UTE (multiplicative)
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.
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.


45. With 15 technologies - what is the number of possible combinations?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
#=2^n = 2^15
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


46. What is satisficing - what is optimizing?
Central limit theorem
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
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.


47. TIES Step 8: Selecting Technology

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48. 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
Technology space limits
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.


49. 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.
is bottom- up - you look at certain technologies and see what improvements they offer
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
#=2^n = 2^15


50. What are the different types of UTEs?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Active UTE (additive) - Product UTE (multiplicative)
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
F(x)=1/(s(2p)^(.5) )exp?(-(x-