ADM

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• Answer 50 questions in 15 minutes.
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This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.

1. Strengths of TOPSis...
Mean and variance
Determine the design space - baseline Method: Morphological Matrix
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


2. MODM
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
It gives the probability that a value will be met or exceeded.
Does not have a natural zero - is a cardinal scale
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.


3. What is the equation for the learning curve?
Gaussian Distribution
Regions 1 to 3.
It gives the probability that a value will be met or exceeded.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


4. What is probability density contour plot
Does not have a natural zero - is a cardinal scale
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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
(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


5. What is the definition of CDF?
Technique for Order Preference by Similarity to Ideal Solution
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
It gives the probability that a value will be met or exceeded.
Central limit theorem


6. 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
Central limit theorem
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
A pareto frontier represents points of a non - dominated solution based on preferences


7. What does CLT stand for?
Mean =0 Variance =1
Regions 1 to 3.
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
Central limit theorem


8. What can management do to mitigate the risk associated with infusing new technologies?
OEC = W1X/Xbsl + W2Nbsl/N
Determine the design space - baseline Method: Morphological Matrix
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)


9. 4 Measures of Dispersion
Technique for Order Preference by Similarity to Ideal Solution
Mean =0 Variance =1
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
(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


10. What are K- factors applied to?
Technology space limits
(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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
It gives the probability that a value will be met or exceeded.


11. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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.


12. What is the goal of probabilistic design?

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13. Ratio scale
Has a natural zero - is a cardinal scale
Sample size is 4 - the sample is the sum of the five dice.
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


14. Other than infusing technologies - how can you create design space?
Does not have a natural zero - is a cardinal scale
The interest i such that 0=PE(i^)
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.


15. What is the goal of robust design?

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16. 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.
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
Sample size is 4 - the sample is the sum of the five dice.


17. What are the different types of UTEs?
Sample size is 4 - the sample is the sum of the five dice.
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
Active UTE (additive) - Product UTE (multiplicative)
Cumulative Distribution Function


18. TIES Step 1: Problem Definition
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 first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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


19. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Technique for Order Preference by Similarity to Ideal Solution
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


20. If you have a two values on a CDF what is the probability of getting a value between them?
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: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
P(between B and A)=F(B)-F(A)


21. 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?
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
#=2^n = 2^15
Sample size is 4 - the sample is the sum of the five dice.
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.


22. Why is the normal distribution useful or important?

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23. Direct Operating Costs
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo


24. What is TRL? Range? What does a high TRL mean?
Technique for Order Preference by Similarity to Ideal Solution
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Sample size is 4 - the sample is the sum of the five dice.


25. What is the difference between price and cost?
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: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
The interest i such that 0=PE(i^)


26. interval scale
PE(i)=?Ft
Does not have a natural zero - is a cardinal scale
Active UTE (additive) - Product UTE (multiplicative)
To analytically answer 'How much design margin is really necessary?'


27. What does the CLT state - be specific!
As you add n number of identical & independent distributions (IIDs) together - as n --> inf - the resulting distribution will be normal - regardless of the shape of the IIDs
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
The interest i such that 0=PE(i^)
It gives the probability that a value will be met or exceeded.


28. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
It can be continuous or discrete
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Technology space limits


29. TIES Step 3: Model and Simulation
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 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
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
CDF= ?_(-8)^8


30. With 15 technologies - what is the number of possible combinations?
A pareto frontier represents points of a non - dominated solution based on preferences
#=2^n = 2^15
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(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


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

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32. TIF

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33. How is inflation measured?

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34. 3 Probabilistic Design Methods
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
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
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)


35. Indirect Operating Cost
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Does not have a natural zero - is a cardinal scale
To analytically answer 'How much design margin is really necessary?'


36. 3 Measures of Central Tendency (& Defs)
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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Technology space limits


37. What is the definition of inflation?
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
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.
#=2^n = 2^15


38. What is satisficing - what is optimizing?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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.
No way to tell without more information. It depends on the relation between s12+s22 and s32
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln


39. 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
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Allows designer to assess feasibility of design
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


40. Assumptions Used in TOPSis...
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(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
Active UTE (additive) - Product UTE (multiplicative)
#=2^n = 2^15


41. What is TCM? What is the size and what value can it take?
is bottom- up - you look at certain technologies and see what improvements they offer
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology
RDTE - Investment/Acquisition - Operations and Support - Disposal
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


42. $/RPM Equation
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Cumulative Distribution Function
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


43. TIES Step 6: Identify Technology
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Has a natural zero - is a cardinal scale
(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
RDTE - Investment/Acquisition - Operations and Support - Disposal


44. Write down a formula for a normal distribution
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-
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
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.


45. What can be done about uncertainty in requirement?
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
To analytically answer 'How much design margin is really necessary?'
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


46. What are the three snapshots 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
(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
#=2^n = 2^15
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


47. What two variables are necessary to define a normal distribution?
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 and variance
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
is bottom- up - you look at certain technologies and see what improvements they offer


48. What are the four difference life cycle costs?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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


49. MADM
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.
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.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


50. What are properties of a CDF?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Technique for Order Preference by Similarity to Ideal Solution
Range is always between zero and 1 monotonically increasing
(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