101-0031-AAL  Systems Engineering

SemesterAutumn Semester 2021
LecturersB. T. Adey
Periodicityevery semester recurring course
Language of instructionEnglish
CommentEnrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.


101-0031-AA RSystems Engineering
Self-study course. No presence required.
120s hrsB. T. Adey

Catalogue data

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 terms.
• 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.
ObjectiveThe 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 the best possible decision making when engineering sustainable systems, i.e. ones that 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 quantitative and qualitative evaluation of possible system modifications. Additionally, the course includes an introduction to the use of operations research methods in the determination of optimal solutions in complex systems.

More specifically upon completion of the course, you will have gained insight into:
• how to structure the large amount of information that is often associated with attempting to modify complex systems
• how to set goals and define constraints in the engineering of complex systems
• 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 values of benefits to stakeholders that are not in monetary units
• how to assess whether it is worth obtaining more information in determining optimal solution
• how to take a step back from the numbers and qualitatively evaluate the possible solutions in light of the bigger picture
• the basics of operations research and how it can be used to determine optimal solutions to complex problems, including linear, integer and network programming, dealing with multiple objectives and conducting sensitivity analyses.
ContentThe weekly content is structured as follows:
1 Introduction – An introduction to System 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. An introduction to the example that we will be working with through most of the course. The expectations of your efforts throughout the semester.
2 Situation analysis – How to structure the large amount of information that is often associated with attempting to modify complex systems.
3 Goals and constraints – How to set goals and constraints to identify the best solutions as clearly as possible.
4 Generation of possible solutions – How to generate possible solutions to problems, considering multiple stakeholders.
5 Analysis – 1/5 – 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, display, weighting, and expected value.
6 Analysis – 2/5 – The idea behind the supply and demand curves and revealed preference methods.
7 Analysis – 3/5 – The concept of equivalence, including the time value of money, interest, life times and terminal values.
8 Analysis – 4/5 – The relationship between net-benefit and the benefit-cost ratio. How incremental cost benefit analysis can be used to determine the maximum net benefit. Marginal rates of return and internal rates of return.
9 Analysis – 5/5 – How to consider multiple possible futures and use simple rules to help pick optimal solutions and to determine the value of more information.
10 Evaluation of solutions – Regardless how sophisticated an analysis is, it requires that decision makers stand back and critically evaluate the results. This week we discuss the aspects of evaluating the results of an analysis.
11 Operations research – 1/4 – Once quantitative analysis is used it becomes possible to use operations research methods to analyse large numbers of possible solutions. This week we discuss linear programming and the simplex method.
12 Operations research – 2/4 – How sensitivity analysis is conducted using linear programming.
13 Operations research – 3/4 – How to use operations research to solve problems that consist of discrete values, as well as how to exploit the structure of networks to find optimal solutions to network problems.
14 Operations research – 4/4 – How to set up and solve problems when there are multiple objectives.

The course uses a combination of qualitative and quantitative approaches. The quantitative analyses requires the use of Excel. An introduction to Excel will be provided in one of the help sessions.
Lecture notesThe script for the original course is in German. The English material that can be used for the virtual course is:
1 ) Adey, B.T., Hackl, J., Lam, J.C., van Gelder, P., van Erp, N., Prak, P., Heitzler, M., Iosifescu, I., Hurni, L., (2016), Ensuring acceptable levels of infrastructure related risks due to natural hazards with emphasis on stress tests, International Symposium on Infrastructure Asset Management (SIAM), Kyoto, Japan, January 21-22.
2) Blanchard, B.S., and Fabrycky W.J., (2008), Systems Engineering and Analysis, 5th International Edition, Prentice Hall.
3) Revelle, C.S., Whitlach, E.E., and Wright, J.R., (2003), Civil and Environmental Systems Engineering, 2nd Edition, Prentice Hall.
LiteratureThe literature will be made available at the beginning of the course.
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Media and Digital Technologiesfostered
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingfostered
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersB. T. Adey
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition possible without re-enrolling for the course unit.

Learning materials

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Only public learning materials are listed.


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Offered in

Spatial Development and Infrastructure Systems MasterCourse Units for Additional Admission RequirementsE-Information