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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?
To analytically answer 'How much design margin is really necessary?'
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Gaussian Distribution
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

2. What is the goal of robust design?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
No way to tell without more information. It depends on the relation between s12+s22 and s32
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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

3. Ratio scale
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.
Has a natural zero - is a cardinal scale
P(between B and A)=F(B)-F(A)
Allows designer to assess feasibility of design

4. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
A pareto frontier represents points of a non - dominated solution based on preferences
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

5. Write down a formula for a normal distribution
It gives the probability that a value will be met or exceeded.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Does not have a natural zero - is a cardinal scale

6. What can management do to mitigate the risk associated with infusing new technologies?
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
Does not have 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)
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.

7. What is the difference between price and cost?
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.
It gives the probability that a value will be met or exceeded.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

8. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
(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)
It can be continuous or discrete

9. If you have a two values on a CDF what is the probability of getting a value between them?
#=2^n = 2^15
To analytically answer 'How much design margin is really necessary?'
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
P(between B and A)=F(B)-F(A)

10. What are the different types of UTEs?
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
Active UTE (additive) - Product UTE (multiplicative)
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 can be continuous or discrete

11. What is TCM? What is the size and what value can it take?
Range is always between zero and 1 monotonically increasing
(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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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

12. What are properties of a CDF?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Range is always between zero and 1 monotonically increasing
(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

13. What is the definition of inflation?
X~N(0 -1)
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 =0 Variance =1
Technology space limits

14. What is satisficing - what is optimizing?
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.
Determine the design space - baseline Method: Morphological Matrix
Mean =0 Variance =1
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future

15. Why use uniform dist for input variables (Gap Analysis)
X+Y and X-Y are normally distributed. - (X
Allows designer to assess feasibility of design
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
is bottom- up - you look at certain technologies and see what improvements they offer

16. What is TIM? What is the size and what value can it take?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
Allows designer to assess feasibility of design

17. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Sample size is 4 - the sample is the sum of the five dice.
RDTE - Investment/Acquisition - Operations and Support - Disposal
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

18. 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.
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.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

19. 3 Probabilistic Design Methods
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Technique for Order Preference by Similarity to Ideal Solution

20. TIES Step 7: Assess Technology
It can be continuous or discrete
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. 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
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

21. What does TOPSIS stand for?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
The interest i such that 0=PE(i^)
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

22. What does CDF stand for?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

23. TIF
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Gaussian Distribution
P(between B and A)=F(B)-F(A)
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

24. With 15 technologies - what is the number of possible combinations?
Mean =0 Variance =1
Determine the design space - baseline Method: Morphological Matrix
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
#=2^n = 2^15

25. 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
Regions 1 to 3.
OEC = W1X/Xbsl + W2Nbsl/N
Technology space limits

26. 4 Measures of Dispersion
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
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
(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) End result not intuitive (2) Heavily reliant on weights - which are subjective

27. What can be done about uncertainty in requirement?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Mean and variance
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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

28. Assumptions Used in TOPSis...
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 technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

29. 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
Has a natural zero - is a cardinal scale
It gives the probability that a value will be met or exceeded.
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.

30. Show and explain a pareto frontier
It gives the probability that a value will be met or exceeded.
is bottom- up - you look at certain technologies and see what improvements they offer
No way to tell without more information. It depends on the relation between s12+s22 and s32
A pareto frontier represents points of a non - dominated solution based on preferences

31. What are K- factors applied to?
Technology space limits
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Has a natural zero - is a cardinal scale
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

32. How do you get the CDF from the PDF?
Has a natural zero - is a cardinal scale
(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
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
CDF= ?_(-8)^8

33. 3 Measures of Central Tendency (& Defs)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Central limit theorem
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

34. TIES Step 8: Selecting Technology
RDTE - Investment/Acquisition - Operations and Support - Disposal
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.
Does not have a natural zero - is a cardinal scale

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

36. What is the notation for a standard normal distribution?
X~N(0 -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.
Active UTE (additive) - Product UTE (multiplicative)
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

37. TIES Step 1: Problem Definition
No way to tell without more information. It depends on the relation between s12+s22 and s32
Central limit theorem
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

38. Define fixed cost and variable cost.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Determine the design space - baseline Method: Morphological Matrix
#=2^n = 2^15
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. Other than infusing technologies - how can you create design space?
(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.
Cumulative Distribution Function
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

40. Name the advantages of UTE.
Technique for Order Preference by Similarity to Ideal Solution
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.
Central limit theorem
X~N(0 -1)

41. What are the parameters for a standard normal distribution?
RDTE - Investment/Acquisition - Operations and Support - Disposal
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 =0 Variance =1
Has a natural zero - is a cardinal scale

42. 8 Steps in TIES
OEC = W1X/Xbsl + W2Nbsl/N
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
(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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

43. How is inflation measured?
X+Y and X-Y are normally distributed. - (X
P(between B and A)=F(B)-F(A)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
is bottom- up - you look at certain technologies and see what improvements they offer

44. Why do we use a sample?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(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
Determine the design space - baseline Method: Morphological Matrix
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

45. What is the definition of ROI?
Cumulative Distribution Function
The interest i such that 0=PE(i^)
A pareto frontier represents points of a non - dominated solution based on preferences
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. Does TIES use MADM or MODM? Why?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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) 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
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.

47. TIES Step 6: Identify 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
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.
X~N(0 -1)

48. Why are scaling parameters important?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
No way to tell without more information. It depends on the relation between s12+s22 and s32
P(between B and A)=F(B)-F(A)
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

49. What is the normal distribution that results from adding x+y and x[sub]y?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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
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

50. In what regions of the graph is UTE applicable?
Regions 1 to 3.
(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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Gaussian Distribution

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