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ADM
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Study First
Subject
:
engineering
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. Ratio scale
Range is always between zero and 1 monotonically increasing
Has 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
Cumulative Distribution Function
2. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
No way to tell without more information. It depends on the relation between s12+s22 and s32
X~N(0 -1)
3. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Central limit theorem
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Determine the design space - baseline Method: Morphological Matrix
4. What is the goal of robust design?
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5. Why is the normal distribution useful or important?
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6. 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.
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal
Gaussian Distribution
7. What does CLT stand for?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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
Technology space limits
Central limit theorem
8. What is probability density contour plot
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
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.
9. 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 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.
Cumulative Distribution Function
10. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
(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
Does not have a natural zero - is a cardinal scale
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
11. Assumptions Used in TOPSis...
Mean and variance
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(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
12. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Sample size is 4 - the sample is the sum of the five dice.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
PE(i)=?Ft
It can be continuous or discrete
13. 4 Measures of Dispersion
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
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
14. TIF
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15. What are the three snapshots of UTE?
A pareto frontier represents points of a non - dominated solution based on preferences
Does not have a natural zero - is a cardinal scale
(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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
16. What are the different types of UTEs?
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.
Active UTE (additive) - Product UTE (multiplicative)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
It can be continuous or discrete
17. How do you get the CDF from the PDF?
It can be continuous or discrete
CDF= ?_(-8)^8
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
18. MADM
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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.
It can be continuous or discrete
19. Other than infusing technologies - how can you create design space?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
PE(i)=?Ft
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
20. TIES
Allows designer to assess feasibility of design
is bottom- up - you look at certain technologies and see what improvements they offer
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
X~N(0 -1)
21. TIES Step 3: Model and Simulation
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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
22. What two variables are necessary to define a normal distribution?
RDTE - Investment/Acquisition - Operations and Support - Disposal
A pareto frontier represents points of a non - dominated solution based on preferences
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
23. Why do we use a sample?
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
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
24. What is the notation for a standard normal distribution?
X~N(0 -1)
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) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
25. TIES Step 6: Identify Technology
(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
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
OEC = W1X/Xbsl + W2Nbsl/N
26. In what regions of the graph is UTE applicable?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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
Regions 1 to 3.
27. TIES Step 5: Feasible?
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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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
is bottom- up - you look at certain technologies and see what improvements they offer
28. What is the equation for present equivalent value? Define variables.
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
RDTE - Investment/Acquisition - Operations and Support - Disposal
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.
29. What are properties of a CDF?
A pareto frontier represents points of a non - dominated solution based on preferences
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Range is always between zero and 1 monotonically increasing
30. 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
Cumulative Distribution Function
Gaussian Distribution
To analytically answer 'How much design margin is really necessary?'
31. Show and explain a pareto frontier
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 interest i such that 0=PE(i^)
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.
A pareto frontier represents points of a non - dominated solution based on preferences
32. 3 Probabilistic Design Methods
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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)
X~N(0 -1)
33. Does TIES use MADM or MODM? Why?
Technology space limits
Has a natural zero - is a cardinal scale
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
34. 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
(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
To analytically answer 'How much design margin is really necessary?'
(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
35. Define fixed cost and variable cost.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
X~N(0 -1)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
#=2^n = 2^15
36. What is the normal distribution that results from adding x+y and x[sub]y?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Technology space limits
X+Y and X-Y are normally distributed. - (X
Range is always between zero and 1 monotonically increasing
37. Indirect Operating Cost
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(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
38. What is TRL? Range? What does a high TRL mean?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Range is always between zero and 1 monotonically increasing
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
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
39. What are the parameters for a standard normal distribution?
X~N(0 -1)
P(between B and A)=F(B)-F(A)
Mean =0 Variance =1
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
40. What is the definition of ROI?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Sample size is 4 - the sample is the sum of the five dice.
The interest i such that 0=PE(i^)
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
41. 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.
Mean =0 Variance =1
Gaussian 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
42. How is inflation measured?
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43. TIES Step 7: Assess Technology
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
RDTE - Investment/Acquisition - Operations and Support - Disposal
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
To analytically answer 'How much design margin is really necessary?'
44. What is the definition of CDF?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
It gives the probability that a value will be met or exceeded.
Range is always between zero and 1 monotonically increasing
is bottom- up - you look at certain technologies and see what improvements they offer
45. What can management do to mitigate the risk associated with infusing new technologies?
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
#=2^n = 2^15
Sample size is 4 - the sample is the sum of the five dice.
46. TIES Step 1: Problem Definition
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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
47. $/RPM Equation
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Active UTE (additive) - Product UTE (multiplicative)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
48. If you have a two values on a CDF what is the probability of getting a value between them?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
P(between B and A)=F(B)-F(A)
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
49. What is TIM? What is the size and what value can it take?
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50. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
PE(i)=?Ft
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