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