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. Why do we use a sample?
Mean =0 Variance =1
Does not have a natural zero - is a cardinal scale
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Technology space limits

2. 4 Measures of Dispersion
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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.
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

3. What is the goal of probabilistic design?

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

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

5. TIES Step 4: Investigate Design Space
Technique for Order Preference by Similarity to Ideal Solution
PE(i)=?Ft
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.

6. What is the definition of ROI?
The interest i such that 0=PE(i^)
Regions 1 to 3.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

7. 3 Probabilistic Design Methods
Technique for Order Preference by Similarity to Ideal Solution
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

8. TIES Step 8: Selecting Technology

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

9. Weaknesses of TOPSis...
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
A pareto frontier represents points of a non - dominated solution based on preferences
It can be continuous or discrete
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

10. Indirect Operating Cost
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
No way to tell without more information. It depends on the relation between s12+s22 and s32
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

11. What is the normal distribution that results from adding x+y and x[sub]y?
X+Y and X-Y are normally distributed. - (X
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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.
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

12. interval scale
Does not have a natural zero - is a cardinal scale
CDF= ?_(-8)^8
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
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

13. 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.
OEC = W1X/Xbsl + W2Nbsl/N
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
Allows designer to assess feasibility of design

14. Strengths of TOPSis...
Gaussian Distribution
X~N(0 -1)
Central limit theorem
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

15. TIES Step 2: Design Space Conception
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.
Determine the design space - baseline Method: Morphological Matrix
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

16. What does CDF stand for?
Cumulative Distribution Function
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
is bottom- up - you look at certain technologies and see what improvements they offer
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

17. What can be done about uncertainty in requirement?
A pareto frontier represents points of a non - dominated solution based on preferences
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

18. Does TIES use MADM or MODM? Why?
Regions 1 to 3.
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

19. MADM
is bottom- up - you look at certain technologies and see what improvements they offer
OEC = W1X/Xbsl + W2Nbsl/N
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~N(0 -1)

20. What is TRL? Range? What does a high TRL mean?
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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
Active UTE (additive) - Product UTE (multiplicative)

21. Why are scaling parameters important?
No way to tell without more information. It depends on the relation between s12+s22 and s32
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
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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

22. What are the parameters for a standard normal distribution?
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
Mean =0 Variance =1
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective

23. What is the difference between price and cost?
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Sample size is 4 - the sample is the sum of the five dice.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

24. TIES Step 7: Assess Technology
X~N(0 -1)
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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

25. Assumptions Used in TOPSis...
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
is bottom- up - you look at certain technologies and see what improvements they offer
Mean =0 Variance =1
(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

26. TIF

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

27. Why is the normal distribution useful or important?

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

28. In what regions of the graph is UTE applicable?
Regions 1 to 3.
Range is always between zero and 1 monotonically increasing
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

29. If you have a two values on a CDF what is the probability of getting a value between them?
Does not have a natural zero - is a cardinal scale
#=2^n = 2^15
OEC = W1X/Xbsl + W2Nbsl/N
P(between B and A)=F(B)-F(A)

30. TIES Step 3: Model and Simulation
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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.
Cumulative Distribution Function

31. Direct Operating Costs
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

32. TIES Step 5: Feasible?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to 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
#=2^n = 2^15
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.

33. What is the notation for a standard normal distribution?
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
Range is always between zero and 1 monotonically increasing
X~N(0 -1)
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

34. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Does not have a natural zero - is a cardinal scale
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(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
F(x)=1/(s(2p)^(.5) )exp?(-(x-

35. 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
X~N(0 -1)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Central limit theorem

36. With 15 technologies - what is the number of possible combinations?
is bottom- up - you look at certain technologies and see what improvements they offer
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
#=2^n = 2^15

37. What is another name for a normal distribution?
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Gaussian 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

38. What two variables are necessary to define a normal distribution?
It can be continuous or discrete
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 and variance
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.

39. 8 Steps in TIES
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
(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
Does not have a natural zero - is a cardinal scale
Has a natural zero - is a cardinal scale

40. TIES
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
is bottom- up - you look at certain technologies and see what improvements they offer
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Technique for Order Preference by Similarity to Ideal Solution

41. 3 Measures of Central Tendency (& Defs)
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.
Cumulative Distribution Function
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: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

42. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Has a natural zero - is a cardinal scale
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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. What is the equation for present equivalent value? Define variables.
is bottom- up - you look at certain technologies and see what improvements they offer
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
PE(i)=?Ft

44. TIES Step 1: Problem Definition
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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
Does not have a natural zero - is a cardinal scale

45. $/RPM Equation
Determine the design space - baseline Method: Morphological Matrix
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

46. What are the different types of UTEs?
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)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
#=2^n = 2^15

47. What can management do to mitigate the risk associated with infusing new technologies?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
No way to tell without more information. It depends on the relation between s12+s22 and s32
Sample size is 4 - the sample is the sum of the five dice.
To analytically answer 'How much design margin is really necessary?'

48. What are K- factors applied to?
Technology space limits
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
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.
Cumulative Distribution Function

49. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
(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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Allows designer to assess feasibility of design

50. What is TCM? What is the size and what value can it take?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Cumulative Distribution Function
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)