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. TIES Step 1: Problem Definition
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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Active UTE (additive) - Product UTE (multiplicative)


2. Ratio scale
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Has a natural zero - is a cardinal scale
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
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'


3. Weaknesses of TOPSis...
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Determine the design space - baseline Method: Morphological Matrix
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'


4. 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.
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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee


5. Why is the normal distribution useful or important?

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6. What does CDF stand for?
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
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
Cumulative Distribution Function


7. What is the goal of probabilistic design?

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8. 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)
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
Gaussian Distribution
Has a natural zero - is a cardinal scale


9. In what regions of the graph is UTE applicable?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
The interest i such that 0=PE(i^)
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
Regions 1 to 3.


10. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
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
Range is always between zero and 1 monotonically increasing
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


11. What can management do to mitigate the risk associated with infusing new technologies?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
No way to tell without more information. It depends on the relation between s12+s22 and s32
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)


12. TIES Step 4: Investigate Design Space
Range is always between zero and 1 monotonically increasing
Technology space limits
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.


13. 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
(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
It gives the probability that a value will be met or exceeded.


14. TIES Step 8: Selecting Technology

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


16. Why are scaling parameters important?
X~N(0 -1)
Scaling parameters photographically scale the size of the vehicle to take full advantage of technology -(e.g. increase CL -> Can decrease S -> Decreases D -> Decreases Fuel Consumed -> etc...) This assumes that the physics of the problem remains the
Active UTE (additive) - Product UTE (multiplicative)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


17. Other than infusing technologies - how can you create design space?
Mean and variance
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
is bottom- up - you look at certain technologies and see what improvements they offer
Mean =0 Variance =1


18. 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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


19. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Does not have a natural zero - is a cardinal scale
Technique for Order Preference by Similarity to Ideal Solution
To analytically answer 'How much design margin is really necessary?'


20. What is the notation for a standard normal distribution?
X~N(0 -1)
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
OEC = W1X/Xbsl + W2Nbsl/N


21. What is satisficing - what is optimizing?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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.
To analytically answer 'How much design margin is really necessary?'
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.


22. What does TOPSIS stand for?
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.
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.
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.


23. What is the equation for the learning curve?
(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
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.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


24. TIES Step 6: Identify Technology
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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.
(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


25. What is the difference between price and cost?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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 pareto frontier represents points of a non - dominated solution based on preferences
is bottom- up - you look at certain technologies and see what improvements they offer


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

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27. MADM
It can be continuous or discrete
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 technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
Central limit theorem


28. What is probability density contour plot
A probability density contour plot is a visualization method for Joint probability density function (a 2D representation). Their shapes (contour shapes) tell if the metric analyzed in each axis are correlated or not (Circular -> no correlation) (elli
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.
X+Y and X-Y are normally distributed. - (X


29. Why use uniform dist for input variables (Gap Analysis)
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Allows designer to assess feasibility of design
X+Y and X-Y are normally distributed. - (X
It can be continuous or discrete


30. Does TIES use MADM or MODM? Why?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Mean =0 Variance =1
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


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
#=2^n = 2^15
A pareto frontier represents points of a non - dominated solution based on preferences


32. What are the parameters for a standard normal distribution?
is bottom- up - you look at certain technologies and see what improvements they offer
Mean and variance
X~N(0 -1)
Mean =0 Variance =1


33. What are properties of a CDF?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Range is always between zero and 1 monotonically increasing
Mean =0 Variance =1
Determine the design space - baseline Method: Morphological Matrix


34. 3 Probabilistic Design Methods
#=2^n = 2^15
It gives the probability that a value will be met or exceeded.
Determine the design space - baseline Method: Morphological Matrix
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration


35. $/RPM Equation
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Range is always between zero and 1 monotonically increasing
Central limit theorem
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)


36. Name the advantages of UTE.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
It gives the probability that a value will be met or exceeded.


37. How do you get the CDF from the PDF?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
It can be continuous or discrete
Does not have a natural zero - is a cardinal scale
CDF= ?_(-8)^8


38. 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
X+Y and X-Y are normally distributed. - (X
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


39. Why is learning curve used (or what is it?)
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Scaling parameters photographically scale the size of the vehicle to take full advantage of technology -(e.g. increase CL -> Can decrease S -> Decreases D -> Decreases Fuel Consumed -> etc...) This assumes that the physics of the problem remains the


40. How is inflation measured?

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41. Assumptions Used in TOPSis...
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)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


42. What does the CLT state - be specific!
CDF= ?_(-8)^8
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 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
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


43. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Regions 1 to 3.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
No way to tell without more information. It depends on the relation between s12+s22 and s32
X~N(0 -1)


44. What is the normal distribution that results from adding x+y and x[sub]y?
Active UTE (additive) - Product UTE (multiplicative)
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Technique for Order Preference by Similarity to Ideal Solution


45. What is the goal of robust design?

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46. 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
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
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.


47. TIF

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48. TIES Step 7: Assess Technology
X+Y and X-Y are normally distributed. - (X
Technique for Order Preference by Similarity to Ideal Solution
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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.


49. 4 Measures of Dispersion
Does not have a natural zero - is a cardinal scale
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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
Mean =0 Variance =1


50. What is TCM? What is the size and what value can it take?
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
To analytically answer 'How much design margin is really necessary?'
#=2^n = 2^15
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