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ADM

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Answer 50 questions in 15 minutes.
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Match each statement with the correct term.
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1. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
It can be continuous or discrete
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

2. Does TIES use MADM or MODM? Why?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

3. What are the different types of UTEs?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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
Active UTE (additive) - Product UTE (multiplicative)

4. What are the four difference life cycle costs?
Determine the design space - baseline Method: Morphological Matrix
RDTE - Investment/Acquisition - Operations and Support - Disposal
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Mean and variance

5. What is the equation for the learning curve?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
RDTE - Investment/Acquisition - Operations and Support - Disposal
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

6. Define fixed cost and variable cost.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

7. Strengths of TOPSis...
Technique for Order Preference by Similarity to Ideal Solution
Cumulative Distribution Function
Technology space limits
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

8. What is the definition of ROI?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
The interest i such that 0=PE(i^)
CDF= ?_(-8)^8
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

9. What is another name for a normal distribution?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Gaussian Distribution
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

10. What is the equation for present equivalent value? Define variables.
Determine the design space - baseline Method: Morphological Matrix
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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

11. 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.
CDF= ?_(-8)^8
PE(i)=?Ft
X+Y and X-Y are normally distributed. - (X

12. Write down a formula for a normal distribution
Technology space limits
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
is bottom- up - you look at certain technologies and see what improvements they offer
F(x)=1/(s(2p)^(.5) )exp?(-(x-

13. TIES Step 4: Investigate Design Space
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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 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
F(x)=1/(s(2p)^(.5) )exp?(-(x-

14. Name the advantages of UTE.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Cumulative Distribution Function
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.

15. 3 Probabilistic Design Methods
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
It gives the probability that a value will be met or exceeded.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

16. 3 Measures of Central Tendency (& Defs)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

17. What is the definition of 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.
Gaussian Distribution
Regions 1 to 3.

18. TIES Step 3: Model and Simulation
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.
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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

19. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Cumulative Distribution Function
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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

20. 8 Steps in TIES
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(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
(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
RDTE - Investment/Acquisition - Operations and Support - Disposal

21. What is the normal distribution that results from adding x+y and x[sub]y?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Gaussian Distribution
X+Y and X-Y are normally distributed. - (X
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

22. What is the goal of probabilistic design?

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23. 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
Allows designer to assess feasibility of design
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
X~N(0 -1)

24. What is the notation for a standard normal distribution?
Mean =0 Variance =1
Sample size is 4 - the sample is the sum of the five dice.
X~N(0 -1)
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

25. What does CDF stand for?
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
Cumulative Distribution Function
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

26. What can management do to mitigate the risk associated with infusing new technologies?
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
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 is always between zero and 1 monotonically increasing

27. How is inflation measured?

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28. Why use uniform dist for input variables (Gap Analysis)
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
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
Allows designer to assess feasibility of design

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

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30. Ratio scale
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Has a natural zero - is a cardinal scale
Technology space limits
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

31. TIES
Cumulative Distribution Function
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
is bottom- up - you look at certain technologies and see what improvements they offer
Mean =0 Variance =1

32. MODM
OEC = W1X/Xbsl + W2Nbsl/N
CDF= ?_(-8)^8
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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

33. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
OEC = W1X/Xbsl + W2Nbsl/N
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

34. 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?
OEC = W1X/Xbsl + W2Nbsl/N
Sample size is 4 - the sample is the sum of the five dice.
Allows designer to assess feasibility of design
Range is always between zero and 1 monotonically increasing

35. interval 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.
Does not have a natural zero - is a cardinal scale
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

36. 4 Measures of Dispersion
A pareto frontier represents points of a non - dominated solution based on preferences
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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
Regions 1 to 3.

37. What are K- factors applied to?
is bottom- up - you look at certain technologies and see what improvements they offer
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 space limits
RDTE - Investment/Acquisition - Operations and Support - Disposal

38. If you have a two values on a CDF what is the probability of getting a value between them?
The interest i such that 0=PE(i^)
is bottom- up - you look at certain technologies and see what improvements they offer
P(between B and A)=F(B)-F(A)
#=2^n = 2^15

39. What is TCM? What is the size and what value can it take?
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.
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 technique used to determine the best alternative with all interactions between the constraints. Used for product design.

40. Weaknesses of TOPSis...
Central limit theorem
OEC = W1X/Xbsl + W2Nbsl/N
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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.

41. $/RPM Equation
A technique used to determine the best alternative with all interactions between the constraints. Used for product 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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

42. How do you get the CDF from the PDF?
(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: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
CDF= ?_(-8)^8
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

43. TIES Step 1: Problem Definition
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.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
X+Y and X-Y are normally distributed. - (X
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

44. TIF

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45. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
(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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(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. TIES Step 6: Identify Technology
(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) 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
It gives the probability that a value will be met or exceeded.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

47. Show and explain a pareto frontier
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
P(between B and A)=F(B)-F(A)
A pareto frontier represents points of a non - dominated solution based on preferences

48. What can be done about uncertainty in requirement?
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
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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

49. What is TRL? Range? What does a high TRL mean?
Central limit theorem
Cumulative Distribution Function
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
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.

50. What does the CLT state - be specific!
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
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo