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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. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Central limit theorem
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

2. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Mean and variance
OEC = W1X/Xbsl + W2Nbsl/N
The interest i such that 0=PE(i^)

3. What is the definition of inflation?
Central limit theorem
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
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 related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

4. What does the CLT state - be specific!
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee

5. TIES Step 3: Model and Simulation
Technique for Order Preference by Similarity to Ideal Solution
(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
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
#=2^n = 2^15

6. Assumptions Used in TOPSis...
OEC = W1X/Xbsl + W2Nbsl/N
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

7. Why is the normal distribution useful or important?

8. 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
X+Y and X-Y are normally distributed. - (X
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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.

9. Why are scaling parameters important?
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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Technology space limits

10. What does CLT stand for?
(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
Central limit theorem
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
The interest i such that 0=PE(i^)

11. What is satisficing - what is optimizing?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Allows designer to assess feasibility of design
Mean =0 Variance =1
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.

12. 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
It can be continuous or discrete
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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

13. 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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Central limit theorem
No way to tell without more information. It depends on the relation between s12+s22 and s32

14. 3 Probabilistic Design Methods
Does not have a natural zero - is a cardinal scale
Determine the design space - baseline Method: Morphological Matrix
Active UTE (additive) - Product UTE (multiplicative)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

15. TIES Step 7: Assess Technology
No way to tell without more information. It depends on the relation between s12+s22 and s32
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

16. $/RPM Equation
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
F(x)=1/(s(2p)^(.5) )exp?(-(x-
X+Y and X-Y are normally distributed. - (X
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

17. What does CDF stand for?
Cumulative Distribution Function
A pareto frontier represents points of a non - dominated solution based on preferences
The interest i such that 0=PE(i^)
Regions 1 to 3.

18. 4 Measures of Dispersion
Determine the design space - baseline Method: Morphological Matrix
It gives the probability that a value will be met or exceeded.
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

19. What can be done about uncertainty in requirement?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
PE(i)=?Ft
CDF= ?_(-8)^8

20. Why use uniform dist for input variables (Gap Analysis)
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 sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Allows designer to assess feasibility of design
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

21. 3 Measures of Central Tendency (& Defs)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
Mean and variance
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

22. What is the definition of ROI?
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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
The interest i such that 0=PE(i^)

23. Does TIES use MADM or MODM? Why?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Mean and variance
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

24. MADM
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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.

25. TIES Step 2: Design Space Conception
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Gaussian Distribution
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Determine the design space - baseline Method: Morphological Matrix

26. Ratio scale
Technology space limits
Has 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.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

27. TIES Step 6: Identify Technology
To analytically answer 'How much design margin is really necessary?'
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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

28. Strengths of TOPSis...
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

29. What does TOPSIS stand for?
Technique for Order Preference by Similarity to Ideal Solution
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
RDTE - Investment/Acquisition - Operations and Support - Disposal

30. Show and explain a pareto frontier
A pareto frontier represents points of a non - dominated solution based on preferences
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

31. What is TRL? Range? What does a high TRL mean?
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
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
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
Sample size is 4 - the sample is the sum of the five dice.

32. interval scale
Does not have a natural zero - is a cardinal scale
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
PE(i)=?Ft
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

33. Weaknesses of TOPSis...
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Sample size is 4 - the sample is the sum of the five dice.

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.
It gives the probability that a value will be met or exceeded.
P(between B and A)=F(B)-F(A)
X~N(0 -1)

35. TIES Step 4: Investigate Design Space
To analytically answer 'How much design margin is really necessary?'
No way to tell without more information. It depends on the relation between s12+s22 and s32
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.

36. What is another name for a normal distribution?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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.
Gaussian Distribution
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

37. If you have a two values on a CDF what is the probability of getting a value between them?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
#=2^n = 2^15
P(between B and A)=F(B)-F(A)
Allows designer to assess feasibility of design

38. 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.
A pareto frontier represents points of a non - dominated solution based on preferences
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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.

39. Write down a formula for a normal distribution
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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

40. What are the three snapshots of UTE?
(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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
X~N(0 -1)

41. Direct Operating Costs
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
It gives the probability that a value will be met or exceeded.
#=2^n = 2^15
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

42. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
It can be continuous or discrete
X+Y and X-Y are normally distributed. - (X
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Allows designer to assess feasibility of design

43. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
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 Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Has a natural zero - is a cardinal scale

44. TIF

45. Other than infusing technologies - how can you create design space?
Regions 1 to 3.
Technology space limits
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
It can be continuous or discrete

46. In what regions of the graph is UTE applicable?
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)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

47. What is the equation for present equivalent value? Define variables.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
PE(i)=?Ft
Mean =0 Variance =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

48. How is inflation measured?

49. TIES Step 1: Problem Definition
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
(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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

50. TIES
X~N(0 -1)
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
is bottom- up - you look at certain technologies and see what improvements they offer