101-0031-01L  Systems Engineering

SemesterAutumn Semester 2023
LecturersB. T. Adey
Periodicityyearly recurring course
Language of instructionGerman


101-0031-01 GSystems Engineering
Vorlesung: Donnerstag
Fragestunde: Montag
4 hrs
Mon15:45-17:30HIL E 3 »
Thu09:45-11:30HIL E 3 »
B. 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 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.
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 lectures are 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 Optimisation – 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 Optimisation – 2/4 – How sensitivity analysis is conducted using linear programming.
13 Optimisation – 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.
Lecture notes• The lecture materials consist of a script, the slides and example calculations in Excel.
• The lecture materials will be distributed via Moodle at least two days before each lecture.
LiteratureAppropriate literature in addition to the lecture materials will be handed out when required via Moodle.
Prerequisites / NoticeThis course has no prerequisites.
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
In examination block forBachelor's Degree Programme in Civil Engineering 2014; Version 01.08.2016 (Examination Block 3)
Bachelor's Degree Programme in Environmental Engineering 2010; Version 07.03.2018 (Examination Block)
Bachelor's Degree Programme in Geospatial Engineering 2018; Version 06.10.2021 (Examination Block 3)
ECTS credits4 credits
ExaminersB. T. Adey
Typesession examination
Language of examinationGerman
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 120 minutes
Additional information on mode of examinationDie Lehrveranstaltung beinhaltet optionale Lernaktivitäten während der Vorlesungszeit. Die Teilnahme kann die Note der Sessionsprüfung um bis zu 0,25 Notenpunkte verbessern. Physische Anwesenheit ist für die optionale Lernaktivitäten notwendig.
Written aidsnicht programmierbarer Taschenrechner ohne Textspeicher
Wörterbücher (keine elektronischen)
Online examinationThe examination may take place on the computer.
Distance examinationIt is not possible to take a distance examination.
If the course unit is part of an examination block, the credits are allocated for the successful completion of the whole block.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.


No information on groups available.


There are no additional restrictions for the registration.

Offered in

Civil Engineering BachelorExamination Block 3OInformation
Geospatial Engineering BachelorExamination Block 3OInformation