Assignment Brief:
This assignment is in two parts. One part comprises a case study which poses real systems challenges in terms of planning, implementation, optimization and decision making. This will need to be analysed using the specific technique asked for and discussed and critically appraised with respect to its applicability to Systems Engineering (SE).
The second part provides a problem for you to solve using another SE tool. This is less involved than the first part but will allow you to demonstrate your ability when applying it to a SE problem.
Marks will be awarded on the basis of the knowledge of Systems Engineering (SE) techniques displayed by the candidate and on the quality of analysis in applying related perspectives to the case material
Demonstrating knowledge and understanding of the two techniques in a systems context
Ability to apply these tools in a systems context, with suitable analysis and interpretation.
Insight, deeper understanding and critical appraisal of how these techniques impact on the application of Systems engineering design and analysis.
Report quality including referencing and bibliography (if appropriate), writing style, use of grammar and correct spelling.
Instructions
Part 1 CASE STUDY - Decision Analysis
Objectives
Read the accompanying case study, construct the Decision Tree which represents the situation, identify all options and chance possibilities involved and calculate all appropriate values (superimposing them on the tree) which will assist your decision making process.
These values will include:
Cost penalties or advantages for all options.
Capacity after 20 years
Utilities for passenger demand, after 20 years, of 6 million,
8 million,12 million and 16 million for the various options.
Identify the action which the tree indicates you should take NOW and discuss your reasoning.
Critically appraise, in detail, the application of Decision Analysis to systems design and implementation.
CASE STUDY
A government is faced with the fact that, at four million passengers a year, its major international airport 'T' is near saturation point. Unfortunately, the expansion potential of T is limited, so the government has already taken steps to acquire a new site 'Z', on which a major new airport could be constructed. In the immediate future it has two options:-
1. Close down T, and build the first stage of a major airport at Z (capacity 8 million passengers).
2. Expand to the limits of the site (capacity 6 million passengers) and hold Z ready for future development.
These options are the most likely ways of coping with demand up to 10 years hence. The government is very uncertain about the way in which the market for air travel will develop; broadly, it divides possibilities for 10 years hence into "Low" and "High" forecasts. The probabilities of these levels are estimated as 0.4 and 0.6 respectively.
Thereafter things are more uncertain again. The market twenty years from now, the government estimates could be anything between 6 and 16 million passengers. The probabilities of four levels, given the level materialising after 10 years, are given in- Table 1.
The options open to it also become more complicated. Option 3 and 4 are possible if option 1 was taken and T is already closed.
3. Build the second stage of Z to bring its capacity up to 16 million.
4. Maintain the first stage of Z only (capacity 8 million)
Options 5-8 are possible if option 2 was taken:-
5. Close T and mount a crash programme to build both stages of Z (capacity 16 million)
6. Maintain T and build the first stage of Z (capacity 8 million).
7. Close T and build the first stage of Z (capacity 8 million).
8. Maintain T only; still do nothing at Z (capacity 6 million).
The government has decided to adopt a one-dimensional utility function, the measure of effectiveness being the difference between capacity and demand twenty years hence (ignoring the intermediate situation 10 years hence). Table 2 shows the pay-offs utiles
In addition there are certain cost penalties attached to the policies that involve expanding T and then closing it; this is equivalent in every case to the deduction of 0.15 utiles from the associated pay-off. On the other hand, if T is expanded and remains in use, there is a cost saving representable by an increase in utility of 0.05 utiles.
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Passenger Demand After
10 Years (million)
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Passenger Demand After 20 Years
(million)
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|
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6
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8
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12
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16
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Low
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0.3
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O.6
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0.1
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-
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High
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-
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0.1
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0.5
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0.4
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TABLE 1: Probabilities of Various Levels of Passengers Demand After 20 Years. Given the Level of Demand After 10 Years
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Capacity Demand
(million)
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Utility Associated with Under or
Over Capacity (utiles)
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Under Capacity
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-10
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0
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|
|
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-8
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0.1
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|
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-6
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0.2
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|
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-4
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0.4
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|
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-2
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0.75
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|
|
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0
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1
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|
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Over Capacity
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2
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0.95
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|
|
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4
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0.9
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|
|
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6
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0.8
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8
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0.5
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|
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10
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0.3
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TABLE 2
Part 2 Reliability Analysis
a) The failure rate of engineering components often exhibis three distinct phases. Identify these phases on a graph and discuss the nature of the failures they represent.
b) A manufacturing system is to be controlled using five devices in series. The failure rates together with the cost of each device is/are given in the table below. For a period of continuous operation of one week, determine the arrangement of the devices that will give a reliability of at least 75% for the minimum cost.
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Device
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Failure Rate, %/103hours
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Cost, £
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A
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60
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1000
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B
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12
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500
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C
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83
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250
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D
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50
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125
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E
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75
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1200
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