DECISION MAKING & RISK ANALYSIS

Course Description

Engineering systems are analyzed using probability theory and statistics to evaluate system performance under uncertainty. The course is focused on practical engineering problems and is designed to develop the students' appreciation for application of uncertainty analysis in engineering design. Specifically, students will learn how to analyze and draw conclusion of system performance from statistical data relating to components of engineering systems, analyze series and parallel systems, and make decisions under uncertainty. Theory and methods that are used to analyze multi-attribute decision problems under certainty, uncertainty and risk are discussed. Topics covered in the course include: the value of information, the concept of utility function, expected utility theory, decision trees, formulation of the multi-attribute problem, decision making with discrete and continuous alternatives.

DECISION MAKING & RISK ANALYSIS

Evaluation Tools (Active Term)

Course outcomes

1. 01 Students will have a clear understanding on decision making process and risk
2. 02 Students will be able to apply qualitative and quantitative risk analysis tools/methods
3. 03 Students will be able to identify opportunities to improve decision making under uncertainty
4. 04 Students will be able to apply tools, techniques and frameworks to solve a range of risk and decision situations under uncertainty

Course Syllabus

Reference Books & Course Materials

1. 01 Wayne L. W., Operations Research: Applications and Algorithms, 3rd edition, Duxbury Predd, 1993 (ISBN: 0-534-20971)
2. 02 Cox S., and Tait R., Safety, Reliability and Risk Management: an integrated approach, 2nd edition, Butterworth Heineman, 1998 (ISBN: 0 7506 4016 2)
3. 03 Gregory G., Decsion Analysis, Plenum Press, 1988 (ISBN: 0-306-42854-7)
4. 04 Chapman C., Ward S., Project Risk Management: Processes Techniques and Insights, 2nd edition, John Wiley & Sons, 2003 (ISBN: 0-470-85355-7)

Learning Outcomes

No learning outcomes have been defined.

Program Outcomes

1. P01 Knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline.
2. P02 Ability to apply knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline to the solution of complex engineering problems.
3. P03 Ability to define complex engineering problems by using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) related to the problem addressed.
4. P04 Ability to formulate complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
5. P05 Ability to analyse and solve complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
6. P06 Ability to design creative solutions to complex engineering problems.
7. P07 Ability to design complex systems, processes, devices, or products in a way that meets present and future needs while considering realistic constraints and conditions.
8. P08 Ability to select and use appropriate techniques and resources—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
9. P09 Ability to select and use modern engineering and computational tools—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
10. P10 Ability to conduct literature research and use appropriate research methods for the investigation of complex engineering problems.
11. P11 Ability to design experiments for the investigation of complex engineering problems.
12. P12 Ability to conduct experiments, collect data, analyse results, and interpret findings for the investigation of complex engineering problems.
13. P13 Knowledge of the impacts of engineering practices on society, health and safety, the economy, sustainability, and the environment within the framework of the United Nations Sustainable Development Goals (SDGs).
14. P14 Awareness of the legal implications of engineering solutions within the framework of the United Nations Sustainable Development Goals (SDGs).
15. P15 Knowledge of ethical responsibility and adherence to the principles of professional engineering conduct.
16. P16 Awareness of acting impartially without discrimination in any matter and of being inclusive of diversity.
17. P17 Ability to work effectively as an individual.
18. P18 Ability to work effectively as a team member or leader in intra-disciplinary teams (face-to-face, remote, or hybrid).
19. P19 Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote, or hybrid).
20. P20 Ability to communicate effectively in spoken form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
21. P21 Ability to communicate effectively in written form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
22. P22 Knowledge of professional practices such as project management and economic feasibility analysis.
23. P23 Awareness of entrepreneurship and innovation.
24. P24 Ability for independent and lifelong learning.
25. P25 Ability to adapt to new and emerging technologies.
26. P26 Lifelong learning ability that includes the capacity to think critically about technological changes.

Po-Lo Matrix

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