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

2. 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.
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

3. What two variables are necessary to define a normal distribution?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
Mean and variance

4. What are properties of a CDF?
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) 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
Range is always between zero and 1 monotonically increasing
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

5. What is the equation for present equivalent value? Define variables.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
X~N(0 -1)
Mean =0 Variance =1
PE(i)=?Ft

6. How is inflation measured?

7. TIES Step 6: Identify Technology
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
(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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

8. What is the normal distribution that results from adding x+y and x[sub]y?
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
X~N(0 -1)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

9. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
No way to tell without more information. It depends on the relation between s12+s22 and s32
X+Y and X-Y are normally distributed. - (X
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

10. Indirect Operating Cost
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Central limit theorem
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

11. 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
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
It can be continuous or discrete

12. What are the four difference life cycle costs?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
RDTE - Investment/Acquisition - Operations and Support - Disposal
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Allows designer to assess feasibility of design

13. What are K- factors applied to?
Technology space limits
(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
PE(i)=?Ft

14. If you have a two values on a CDF what is the probability of getting a value between them?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Gaussian Distribution
P(between B and A)=F(B)-F(A)
Mean and variance

15. Why do we use a sample?
Active UTE (additive) - Product UTE (multiplicative)
(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
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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

16. Define fixed cost and variable cost.
Mean =0 Variance =1
#=2^n = 2^15
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

17. 3 Probabilistic Design Methods
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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
Has a natural zero - is a cardinal scale

18. What is the goal of robust design?

19. TIES Step 8: Selecting Technology

20. 3 Measures of Central Tendency (& Defs)
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
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.

21. Ratio scale
Regions 1 to 3.
No way to tell without more information. It depends on the relation between s12+s22 and s32
Technique for Order Preference by Similarity to Ideal Solution
Has a natural zero - is a cardinal scale

22. TIES Step 2: Design Space Conception
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
#=2^n = 2^15
Mean =0 Variance =1
Determine the design space - baseline Method: Morphological Matrix

23. Write down a formula for a normal distribution
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-

24. How do you get the CDF from the PDF?
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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
CDF= ?_(-8)^8

25. Weaknesses of TOPSis...
#=2^n = 2^15
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Mean and variance

26. What are the different types of UTEs?
Active UTE (additive) - Product UTE (multiplicative)
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.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

27. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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 sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
It gives the probability that a value will be met or exceeded.

28. $/RPM Equation
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.
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

29. Does TIES use MADM or MODM? Why?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
The interest i such that 0=PE(i^)

30. 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?
Sample size is 4 - the sample is the sum of the five dice.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Regions 1 to 3.

31. What is the difference between price and cost?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(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
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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee

32. In what regions of the graph is UTE applicable?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Regions 1 to 3.
A pareto frontier represents points of a non - dominated solution based on preferences
(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

33. Why are scaling parameters important?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
X+Y and X-Y are normally distributed. - (X
X~N(0 -1)
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

34. What is the definition of CDF?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Mean and variance
It gives the probability that a value will be met or exceeded.

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

36. Why use uniform dist for input variables (Gap Analysis)
is bottom- up - you look at certain technologies and see what improvements they offer
Allows designer to assess feasibility of design
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

37. Direct Operating Costs
Cumulative Distribution Function
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Technique for Order Preference by Similarity to Ideal Solution
X+Y and X-Y are normally distributed. - (X

38. What is the notation for a standard normal distribution?
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
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

39. What are the parameters for a standard normal distribution?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Mean =0 Variance =1
The interest i such that 0=PE(i^)
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

40. What are the three snapshots of UTE?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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
(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
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

41. Other than infusing technologies - how can you create design space?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Determine the design space - baseline Method: Morphological Matrix
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.

42. 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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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.

43. TIES Step 4: Investigate Design Space
Has a natural zero - is a cardinal scale
Regions 1 to 3.
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.
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

44. What is the definition of inflation?
Range is always between zero and 1 monotonically increasing
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
PE(i)=?Ft
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

45. TIES Step 5: Feasible?
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.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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

46. interval scale
Range is always between zero and 1 monotonically increasing
Does not have a natural zero - is a cardinal scale
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

47. Name the advantages of UTE.
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
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.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

48. What can management do to mitigate the risk associated with infusing new technologies?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
PE(i)=?Ft
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

49. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
(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
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)
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

50. Show and explain a pareto frontier
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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
A pareto frontier represents points of a non - dominated solution based on preferences