Test your basic knowledge |

ADM

Instructions:

Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can study here.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.

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 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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Cumulative Distribution Function
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

2. In what regions of the graph is UTE applicable?
Does not have a natural zero - is a cardinal scale
Regions 1 to 3.
No way to tell without more information. It depends on the relation between s12+s22 and s32
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

3. What is the goal of robust design?

4. What does CDF stand for?
It gives the probability that a value will be met or exceeded.
Cumulative Distribution Function
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
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.

5. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Active UTE (additive) - Product UTE (multiplicative)
F(x)=1/(s(2p)^(.5) )exp?(-(x-
OEC = W1X/Xbsl + W2Nbsl/N
#=2^n = 2^15

6. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
No way to tell without more information. It depends on the relation between s12+s22 and s32
It can be continuous or discrete
PE(i)=?Ft
P(between B and A)=F(B)-F(A)

7. What is another name for a normal distribution?
Gaussian Distribution
The interest i such that 0=PE(i^)
Active UTE (additive) - Product UTE (multiplicative)
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

8. TIES Step 8: Selecting Technology

9. Does TIES use MADM or MODM? Why?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
CDF= ?_(-8)^8
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

10. What is the notation for a standard normal distribution?
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
X~N(0 -1)
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

11. 8 Steps in TIES
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(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

12. What does TOPSIS stand for?
To analytically answer 'How much design margin is really necessary?'
Technique for Order Preference by Similarity to Ideal Solution
It can be continuous or discrete
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

13. $/RPM Equation
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Range is always between zero and 1 monotonically increasing
RDTE - Investment/Acquisition - Operations and Support - Disposal
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

14. Ratio 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
Has a natural zero - is a cardinal scale
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
Technique for Order Preference by Similarity to Ideal Solution

15. TIES Step 1: Problem Definition
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
Regions 1 to 3.
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.

16. TIES Step 3: Model and Simulation
It can be continuous or discrete
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept 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
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

17. With 15 technologies - what is the number of possible combinations?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
#=2^n = 2^15
OEC = W1X/Xbsl + W2Nbsl/N
(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

18. Weaknesses of TOPSis...
(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~N(0 -1)
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

19. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
A technique used to determine the best alternative with all interactions between the constraints. Used for product 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)
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee

20. 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
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

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?
No way to tell without more information. It depends on the relation between s12+s22 and s32
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Sample size is 4 - the sample is the sum of the five dice.
P(between B and A)=F(B)-F(A)

22. TIES Step 6: Identify Technology
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.
(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
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.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

23. What is TRL? Range? What does a high TRL mean?
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
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
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline

24. What is the definition of ROI?
The interest i such that 0=PE(i^)
Determine the design space - baseline Method: Morphological Matrix
Allows designer to assess feasibility of design
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

25. What is TCM? What is the size and what value can it take?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Technology space limits
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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

26. What are the parameters for a standard normal distribution?
It gives the probability that a value will be met or exceeded.
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
Mean =0 Variance =1

27. Name the advantages of UTE.
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.
Does not have a natural zero - is a cardinal scale
F(x)=1/(s(2p)^(.5) )exp?(-(x-

28. interval scale
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
is bottom- up - you look at certain technologies and see what improvements they offer
OEC = W1X/Xbsl + W2Nbsl/N
Does not have a natural zero - is a cardinal scale

29. 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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
CDF= ?_(-8)^8
#=2^n = 2^15

30. Why is learning curve used (or what is it?)
#=2^n = 2^15
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
Does not have a natural zero - is a cardinal scale
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

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.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
X+Y and X-Y are normally distributed. - (X
Technology space limits

32. 3 Probabilistic Design Methods
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

33. Why do we use a sample?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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.

34. What is the definition of CDF?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Sample size is 4 - the sample is the sum of the five dice.
OEC = W1X/Xbsl + W2Nbsl/N
It gives the probability that a value will be met or exceeded.

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

36. What does CLT stand for?
Central limit theorem
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

37. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-

38. What can be done about uncertainty in requirement?
OEC = W1X/Xbsl + W2Nbsl/N
The interest i such that 0=PE(i^)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Central limit theorem

39. TIF

40. Write down a formula for a normal 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)
To analytically answer 'How much design margin is really necessary?'
Mean and variance
F(x)=1/(s(2p)^(.5) )exp?(-(x-

41. MADM
#=2^n = 2^15
A pareto frontier represents points of a non - dominated solution based on preferences
It gives the probability that a value will be met or exceeded.
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.

42. Show and explain a pareto frontier
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
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
The interest i such that 0=PE(i^)

43. TIES Step 2: Design Space Conception
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Determine the design space - baseline Method: Morphological Matrix
Mean and variance
Central limit theorem

44. Indirect Operating Cost
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Active UTE (additive) - Product UTE (multiplicative)

45. What can management do to mitigate the risk associated with infusing new technologies?
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
X~N(0 -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)
(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

46. What are the three snapshots of UTE?
(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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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
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. TIES Step 7: Assess Technology
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

48. Why is the normal distribution useful or important?

49. How is inflation measured?

50. What are the different types of UTEs?
Active UTE (additive) - Product UTE (multiplicative)
Sample size is 4 - the sample is the sum of the five dice.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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.