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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. TIES
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
is bottom- up - you look at certain technologies and see what improvements they offer
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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. Why use uniform dist for input variables (Gap Analysis)
Sample size is 4 - the sample is the sum of the five dice.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Allows designer to assess feasibility of design

3. 8 Steps in TIES
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Central limit theorem
(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

4. MODM
(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
Technique for Order Preference by Similarity to Ideal Solution
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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

5. Strengths of TOPSis...
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
CDF= ?_(-8)^8
PE(i)=?Ft

6. Indirect Operating Cost
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
CDF= ?_(-8)^8
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

7. 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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Cumulative Distribution Function
X+Y and X-Y are normally distributed. - (X

8. 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.
The interest i such that 0=PE(i^)
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

9. 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
CDF= ?_(-8)^8
Regions 1 to 3.
Gaussian Distribution

10. Why is the normal distribution useful or important?

11. 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
Allows designer to assess feasibility of design
Technology space limits
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

12. What is the equation for present equivalent value? Define variables.
No way to tell without more information. It depends on the relation between s12+s22 and s32
To analytically answer 'How much design margin is really necessary?'
It can be continuous or discrete
PE(i)=?Ft

13. What is another name for a normal distribution?
(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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Gaussian Distribution
To analytically answer 'How much design margin is really necessary?'

14. Does TIES use MADM or MODM? Why?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Sample size is 4 - the sample is the sum of the five dice.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

15. What does CDF stand 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
Technique for Order Preference by Similarity to Ideal Solution
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Cumulative Distribution Function

16. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
P(between B and A)=F(B)-F(A)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
It can be continuous or discrete
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

17. 4 Measures of Dispersion
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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.
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
Range is always between zero and 1 monotonically increasing

18. In what regions of the graph is UTE applicable?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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.
Regions 1 to 3.
PE(i)=?Ft

19. interval scale
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.
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.
Does not have a natural zero - is a cardinal scale

20. Direct Operating Costs
Does not have a natural zero - is a cardinal scale
Central limit theorem
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Mean and variance

21. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
P(between B and A)=F(B)-F(A)
(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 =0 Variance =1
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

22. Why do we use a sample?
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
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
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

23. What is the goal of robust design?

24. What are the different types of UTEs?
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 Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Active UTE (additive) - Product UTE (multiplicative)
P(between B and A)=F(B)-F(A)

25. What is probability density contour plot
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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
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
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. 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?
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
Sample size is 4 - the sample is the sum of the five dice.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

27. What does the CLT state - be specific!
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) 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
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.

28. Show and explain a pareto frontier
Determine the design space - baseline Method: Morphological Matrix
A pareto frontier represents points of a non - dominated solution based on preferences
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

29. TIES Step 4: Investigate Design Space
Trying to determine the metric values for any combination of design variables/ what the metrics are as a function of design variables Method: RSE: Response Surface Eqn.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Determine the design space - baseline Method: Morphological Matrix
(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

30. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
is bottom- up - you look at certain technologies and see what improvements they offer
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

31. What is TRL? Range? What does a high TRL mean?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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

32. What is TCM? What is the size and what value can it take?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
No way to tell without more information. It depends on the relation between s12+s22 and s32

33. TIF

34. Weaknesses of TOPSis...
RDTE - Investment/Acquisition - Operations and Support - Disposal
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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 technique used to determine the best alternative with all interactions between the constraints. Used for product design.

35. Ratio scale
Gaussian Distribution
It can be continuous or discrete
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
Has a natural zero - is a cardinal scale

36. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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
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. Define fixed cost and variable cost.
Mean and variance
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
(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

38. What can be done about uncertainty in requirement?
(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
Regions 1 to 3.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

39. What are the four difference life cycle costs?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
A pareto frontier represents points of a non - dominated solution based on preferences

40. 3 Probabilistic Design Methods
P(between B and A)=F(B)-F(A)
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
(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

41. 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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

42. Name the advantages of UTE.
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
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
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 5: Feasible?
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
Mean and variance
Sample size is 4 - the sample is the sum of the five dice.

44. What are the three snapshots of UTE?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Gaussian Distribution
(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: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee

45. What is the notation for a standard normal distribution?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Allows designer to assess feasibility of design
X~N(0 -1)

46. What are the parameters for a standard normal distribution?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Mean =0 Variance =1
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

47. What are properties of a CDF?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
(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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

48. MADM
Central limit theorem
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
(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
A technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.

49. TIES Step 3: Model and Simulation
Has a natural zero - is a cardinal scale
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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Range is always between zero and 1 monotonically increasing

50. 3 Measures of Central Tendency (& Defs)
P(between B and A)=F(B)-F(A)
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.
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
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value