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. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
is bottom- up - you look at certain technologies and see what improvements they offer
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Mean and variance


2. What is the difference between price and cost?
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
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.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future


3. Assumptions Used in TOPSis...
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
OEC = W1X/Xbsl + W2Nbsl/N
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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.


4. What is the goal of probabilistic design?

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5. Ratio scale
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Allows designer to assess feasibility of design
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Has a natural zero - is a cardinal scale


6. Why is the normal distribution useful or important?

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7. 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
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)
Determine the design space - baseline Method: Morphological Matrix


8. Weaknesses of TOPSis...
It gives the probability that a value will be met or exceeded.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
A pareto frontier represents points of a non - dominated solution based on preferences
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.


9. Other than infusing technologies - how can you create design space?
(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 required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
OEC = W1X/Xbsl + W2Nbsl/N


10. If you have a two values on a CDF what is the probability of getting a value between them?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
P(between B and A)=F(B)-F(A)
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space


11. What can be done about uncertainty in requirement?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
RDTE - Investment/Acquisition - Operations and Support - Disposal
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
It gives the probability that a value will be met or exceeded.


12. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Mean =0 Variance =1
(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 Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


13. What is satisficing - what is optimizing?
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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
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.


14. Define fixed cost and variable cost.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
It can be continuous or discrete
Technology space limits
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


15. In what regions of the graph is UTE applicable?
Regions 1 to 3.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
To analytically answer 'How much design margin is really necessary?'
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)


16. 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.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
It can be continuous or discrete


17. 4 Measures of Dispersion
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
PE(i)=?Ft
Inflation is the decrease in the buying power/value of money. It is caused by the when amount of available money changes wrt amount of product/services available
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


18. What are K- factors applied to?
Technology space limits
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
#=2^n = 2^15
CDF= ?_(-8)^8


19. 8 Steps in TIES
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
To analytically answer 'How much design margin is really necessary?'


20. What are properties of a CDF?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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.
X+Y and X-Y are normally distributed. - (X
Range is always between zero and 1 monotonically increasing


21. What are the three snapshots of UTE?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Mean =0 Variance =1
It gives the probability that a value will be met or exceeded.
(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


22. What are the four difference life cycle costs?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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
RDTE - Investment/Acquisition - Operations and Support - Disposal


23. What are the different types of UTEs?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Active UTE (additive) - Product UTE (multiplicative)
To analytically answer 'How much design margin is really necessary?'
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


24. TIES Step 8: Selecting Technology

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25. 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
Determine the design space - baseline Method: Morphological Matrix
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
A pareto frontier represents points of a non - dominated solution based on preferences


26. Direct Operating Costs
Mean =0 Variance =1
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future


27. TIES Step 2: Design Space Conception
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
The interest i such that 0=PE(i^)
(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
Determine the design space - baseline Method: Morphological Matrix


28. TIES Step 1: Problem Definition
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) End result not intuitive (2) Heavily reliant on weights - which are subjective
Technique for Order Preference by Similarity to Ideal Solution
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD


29. What is the equation for present equivalent value? Define variables.
Mean and variance
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
Gaussian Distribution
PE(i)=?Ft


30. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
(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
It can be continuous or discrete
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


31. 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.
CDF= ?_(-8)^8
Gaussian Distribution
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


32. interval scale
Does not have a natural zero - is a cardinal scale
Gaussian Distribution
X+Y and X-Y are normally distributed. - (X
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


33. Why use uniform dist for input variables (Gap Analysis)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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.
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


34. TIES Step 7: Assess Technology
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers


35. TIF

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36. Strengths of TOPSis...
Mean and variance
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Active UTE (additive) - Product UTE (multiplicative)


37. Indirect Operating Cost
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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


38. What is the definition of ROI?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
The interest i such that 0=PE(i^)
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
OEC = W1X/Xbsl + W2Nbsl/N


39. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
Technique for Order Preference by Similarity to Ideal Solution
is bottom- up - you look at certain technologies and see what improvements they offer
Gaussian Distribution


40. What two variables are necessary to define a normal 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
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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


41. TIES Step 3: Model and Simulation
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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
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. What is the definition of CDF?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
It gives the probability that a value will be met or exceeded.
It can be continuous or discrete
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


43. Write down a formula for a normal distribution
A pareto frontier represents points of a non - dominated solution based on preferences
Cumulative Distribution Function
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Range is always between zero and 1 monotonically increasing


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

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45. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
The interest i such that 0=PE(i^)
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) 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


46. What is TCM? What is the size and what value can it take?
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.
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
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
It can be continuous or discrete


47. 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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD


48. What is the definition of inflation?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
The interest i such that 0=PE(i^)
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
OEC = W1X/Xbsl + W2Nbsl/N


49. What does CLT stand for?
CDF= ?_(-8)^8
Gaussian Distribution
Central limit theorem
Does not have a natural zero - is a cardinal scale


50. What is another name for a normal distribution?
Gaussian Distribution
It gives the probability that a value will be met or exceeded.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Does not have a natural zero - is a cardinal scale