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Test your basic knowledge |
ADM
Start Test
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. What does CDF stand for?
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(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
Cumulative Distribution Function
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
2. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Active UTE (additive) - Product UTE (multiplicative)
Technology space limits
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
It can be continuous or discrete
3. In what regions of the graph is UTE applicable?
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 'How much design margin is really necessary?'
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Regions 1 to 3.
4. MODM
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 Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
5. 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
Sample size is 4 - the sample is the sum of the five dice.
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.
6. What are K- factors applied to?
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Sample size is 4 - the sample is the sum of the five dice.
Technology space limits
7. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(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
8. What is the goal of robust design?
9. What is satisficing - what is optimizing?
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.
X+Y and X-Y are normally distributed. - (X
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
10. What is the definition of CDF?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
It gives the probability that a value will be met or exceeded.
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.
11. 3 Probabilistic Design Methods
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
Sample size is 4 - the sample is the sum of the five dice.
Range is always between zero and 1 monotonically increasing
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
12. 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?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Allows designer to assess feasibility of design
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Sample size is 4 - the sample is the sum of the five dice.
13. What are properties of a CDF?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Range is always between zero and 1 monotonically increasing
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
14. What does TOPSIS stand for?
Cumulative Distribution Function
Technique for Order Preference by Similarity to Ideal Solution
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
15. 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
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Sample size is 4 - the sample is the sum of the five dice.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
16. TIES Step 7: Assess Technology
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.
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
Technology space limits
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
17. Why is learning curve used (or what is it?)
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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.
18. 8 Steps in TIES
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
(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
To analytically answer 'How much design margin is really necessary?'
19. TIES Step 1: Problem Definition
Has a natural zero - is a cardinal scale
PE(i)=?Ft
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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
20. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
OEC = W1X/Xbsl + W2Nbsl/N
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
X~N(0 -1)
21. What is the definition of ROI?
Sample size is 4 - the sample is the sum of the five dice.
Central limit theorem
The interest i such that 0=PE(i^)
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
22. Weaknesses of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
CDF= ?_(-8)^8
Active UTE (additive) - Product UTE (multiplicative)
X~N(0 -1)
23. Why do we use a sample?
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.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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.
24. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
It can be continuous or discrete
Regions 1 to 3.
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.
No way to tell without more information. It depends on the relation between s12+s22 and s32
25. TIES
is bottom- up - you look at certain technologies and see what improvements they offer
PE(i)=?Ft
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
It can be continuous or discrete
26. What is the difference between price and cost?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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
is bottom- up - you look at certain technologies and see what improvements they offer
27. What is TCM? What is the size and what value can it take?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
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 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
No way to tell without more information. It depends on the relation between s12+s22 and s32
28. What does CLT stand for?
Central limit theorem
(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
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
The interest i such that 0=PE(i^)
29. What is the definition of inflation?
P(between B and A)=F(B)-F(A)
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
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
30. 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
Gaussian Distribution
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)
31. How do you get the CDF from the PDF?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
OEC = W1X/Xbsl + W2Nbsl/N
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
CDF= ?_(-8)^8
32. TIES Step 3: Model and Simulation
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)
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
33. TIES Step 4: Investigate Design Space
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Active UTE (additive) - Product UTE (multiplicative)
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.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
34. interval scale
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.
Does not have a natural zero - is a cardinal scale
It gives the probability that a value will be met or exceeded.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
35. What is TIM? What is the size and what value can it take?
36. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
X+Y and X-Y are normally distributed. - (X
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
RDTE - Investment/Acquisition - Operations and Support - Disposal
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
37. Show and explain a pareto frontier
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
A pareto frontier represents points of a non - dominated solution based on preferences
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. Define fixed cost and variable cost.
Regions 1 to 3.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
39. If you have a two values on a CDF what is the probability of getting a value between them?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
P(between B and A)=F(B)-F(A)
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.
40. 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.
Allows designer to assess feasibility of design
(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?'
41. Indirect Operating Cost
Technology space limits
Active UTE (additive) - Product UTE (multiplicative)
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)
42. Ratio scale
Range is always between zero and 1 monotonically increasing
PE(i)=?Ft
Allows designer to assess feasibility of design
Has a natural zero - is a cardinal scale
43. What is the equation for the learning curve?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
44. What are the four difference life cycle costs?
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
The interest i such that 0=PE(i^)
RDTE - Investment/Acquisition - Operations and Support - Disposal
To analytically answer 'How much design margin is really necessary?'
45. Why use uniform dist for input variables (Gap Analysis)
Allows designer to assess feasibility of design
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
46. What is probability density contour plot
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Allows designer to assess feasibility of design
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
47. TIF
48. Strengths of TOPSis...
Active UTE (additive) - Product UTE (multiplicative)
Allows designer to assess feasibility of design
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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
49. How is inflation measured?
50. Why is the normal distribution useful or important?