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Systems Engineering
Last Updated: 2026-06-03 00:07:25
Abstract
• Systems Engineering is a way of thinking that helps engineer sustainable systems, i.e., ones that meet the needs of stakeholders in the short, medium and long term.• This course provides an overview of the main principles of Systems Engineering, and includes an introduction to the use of operations research methods in the determination of optimal systems.
Objective
The world’s growing population, changing demographics, and changing climate pose formidable challenges to humanity’s ability to live sustainably. Ensuring that humanity can live sustainably requires accommodating Earth’s growing and changing population through the provision and operation of a sustainable and resilient built environment. This requires ensuring excellent decision-making as to how the built environment is constructed and modified. The objective of this course is to ensure students have the foundation of great decision making, i.e., the decision making that ensures our engineered systems meet the needs of stakeholders in the short, medium and long term. In this course, you will learn the main principles of Systems Engineering that can help you from the first idea that a system may not meet expectations, to the qualitative and quantitative evaluation of possible system modifications. More specifically upon completion of the course, you will have gained insight into: • how to be sure you have identified the right problem and how to set goals and define constraints in the engineering of complex systems as you search for solutions • how to generate possible solutions to complex problems in ways that limit exceedingly narrow thinking • how to compare multiple possible solutions over time with differences in the temporal distribution of costs and benefits and uncertainty as to what might happen in the future • how to assess whether it is worth obtaining more information in determining optimal solutions • the basics of operations research and how it can be used to determine optimal solutions to complex problems, including linear, integer, network and non-linear programming, dealing with multiple objectives and conducting sensitivity analyses
Content
The lectures are structured as follows: 1. Introduction – An introduction to Systems Engineering, a way of thinking that helps to engineer sustainable systems, i.e., ones that meet the needs of stakeholders in the short, medium and long terms. A high-level overview of the main principles of System Engineering. The expectations of your efforts throughout the semester. 2. Situation analysis and goals and constraints – How to structure the large amount of information that is often associated with attempting to modify complex systems. 3. Generation of possible solutions – How to set goals and constraints to identify the best solutions as clearly as possible. How to generate possible solutions to problems, considering multiple stakeholders. 4. The principles of net-benefit maximization and a series of methods that range from qualitative and approximate to quantitative and exact, including pairwise comparison, elimination, weighting, and expected value. 5. The concept of equivalence, including the time value of money, interest, lifetimes and terminal values. 6. The relationship between net-benefit and the benefit-cost ratio. How incremental cost benefit analysis can be used to determine the maximum net benefit. Internal rates of return. 7. How to consider multiple possible futures and use simple rules to help pick optimal solutions. 8. How to determine the value of more information. 9. An introduction to optimization. 10. Linear programming and the simplex method. 11. How sensitivity analysis is conducted using linear programming and how to use operations research to solve problems that consist of discrete values. 12. How to set up and solve problems when there are multiple objectives. 13. How to exploit the structure of networks to find optimal solutions to network problems, and how to solve non-linear problems. The course uses a combination of qualitative and quantitative approaches.
Resources
Lecture Notes
The lecture materials consist of a script, the slides, example calculations in Excel, Python, Moodle quizzes, exercises, and example exams.
Literature
Appropriate literature in addition to the lecture materials will be handed out when required via Moodle.
General Information
- Language
- German
- Levels
- BSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 120 minutes
- Aids
- nicht programmierbarer Taschenrechner ohne Textspeicher, Wörterbücher (keine elektronischen), Formelsammlung (wird zur Verfügung gestellt, eigene sind nicht erlaubt)
- Digital
- The exam takes place on devices provided by ETH Zurich.
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Systems Engineering | No time listed | 2 h weekly |