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