Search result: Catalogue data in Spring Semester 2020

Civil Engineering Master Information
2. Semester
Major Courses
Major in Construction and Maintenance Management
NumberTitleTypeECTSHoursLecturers
101-0579-00LInfrastructure Management 2: Evaluation ToolsW+4 credits2GB. T. Adey, C. Kielhauser
AbstractThis course provides tools to predict the service being provided by infrastructure in situations where the infrastructure is expected to

1) to evolve slowly with relatively little uncertainty over time, e.g. due to the corrosion of a metal bridge, and

2) to change suddenly with relatively large uncertainty, e.g. due to being washed away from an extreme flood.
ObjectiveThe course learning objective is to equip students with tools to be used to the service being provided from infrastructure.
The course increases a student's ability to analyse complex problems and propose solutions and to use state-of-the-art methods of analysis to assess complex problems
ContentReliability
Availability and maintainability
Regression analysis
Event trees
Fault trees
Markov chains
Neural networks
Bayesian networks
Lecture notesAll necessary materials (e.g. transparencies and hand-outs) will be distributed before class.
LiteratureAppropriate reading material will be assigned when necessary.
Prerequisites / NoticeAlthough not an official prerequisite, it is perferred that students have taken the IM1:Process course first. Understanding of the infrastructure management process enables a better understanding of where and how the tools introduced in this course can be used in the management of infrastructure.
101-0588-01LRe-/Source the Built EnvironmentW+3 credits2SG. Habert
AbstractThe course focuses on material choice and energy strategies to limit the environmental impact of construction sector. During the course, specific topics will be presented (construction technologies, environmental policies, social consequences of material use, etc.). The course aims to present sustainable options to tackle the global challenge we are facing and show that "it is not too late".
ObjectiveAfter the lecture series, the students are aware of the main challenges for the production and use of building materials.

They know the different technologies/propositions available, and environmental consequence of a choice.

They understand in which conditions/context one resource/technology will be more appropriate than another
ContentA general presentation of the global context allows to identify the objectives that as engineer, material scientist or architect needs to achieve to create a sustainable built environment.

The course is then conducted as a serie of guest lectures focusing on one specific aspect to tackle this global challenge and show that "it is not too late".

The lecture series is divided as follows:
- General presentation
- Notion of resource depletion, resilience, criticality, decoupling, etc.
- Guest lectures covering different resources and proposing different option to build or maintain a sustainable built environment.
Lecture notesFor each lecture slides will be provided.
Prerequisites / NoticeThe lecture series will be conducted in English and is aimed at students of master's programs, particularly the departments ARCH, BAUG, ITET, MAVT, MTEC and USYS.

No lecture will be given during Seminar week.
101-0517-01LProject Management: Pre-Tender to Contract ExecutionW+4 credits2GJ. J. Hoffman
AbstractThis course (PM 2)will provide a comprehensive overview and understanding of the techniques, processes, tools and terminology to manage the Project Triangle (time, cost, quality) and to organize, analyze, control and report a complex project from Pre-Tender stage to Contract signature and Notice to Proceed. This course is part 2 of a 3 part course, see notice below.
ObjectiveUpon successful completion of this course students will have the understanding of the Project Management duties and responsibilities from the Pre-Tender stage of a project to Contract Execution.
Content- Project scope definition and project organization
- Technical specification proposals
- Work Breakdown Structure
- Estimating
- Schedule development
- Interface management
- Resource and cost integration
- Risk and opportunity identification and quantification
- Contract review and analysis
- Project life cycle
- Contract Execution - Project Manager Check List
Lecture notesThe slides will either be distributed at the beginning of the class, or made available online (via Moodle) prior to class. A copy of the appropriate chapter of the script, the assignment and any other assigned reading materials will be available via Moodle.
LiteratureAppropriate reading material (e.g., chapters out of certain textbooks or trade articles) will be assigned when necessary and made available via Moodle.
Prerequisites / NoticeThis is part 2 of a 3 part course. Part 1 will give the student an introduction to general tools in project management. Part 3 will take the student through Project Execution of the Project.

The students will be randomly assigned to teams of 4 max. Students will be graded as a team based on the final Project report and the in-class oral presentation of the Project Proposal as well as a final exam (50% exam and 50% project report and presentation). Homework will not be graded but your final report and presentation will consist mostly of your homework assignments consolidated and put in a report and presentation format.
102-0348-00LProspective Environmental Assessments
Prerequisite for this lecture is basic knowledge of environmental assessment tools, such as material flow analysis, risk assessment and life cycle assessment.
Students without previous knowledge in these areas need to read according textbooks prior to or at the beginning of the lecture.
W3 credits2GS. Hellweg, N. Heeren, A. Spörri
AbstractThis lecture deals with prospective assessments of emerging technologies as well as with the assessment of long-term environmental impact caused by today's activities.
Objective- Understanding prospective environmental assessments, including scenario analysis techniques, prospective emission models, dynamic MFA and LCA.
- Ability to properly plan and conduct prospective environmental assessment studies, for example on emerging technologies or on technical processes that cause long-term environmental impacts.
- Being aware of the uncertainties involved in prospective studies.
- Getting to know measures to prevent long-term emissions or impact in case studies
- Knowing the arguments in favor and against a temporally differentiated weighting of environmental impacts (discounting)
Content- Scenario analysis
- Dynamic material flow analysis
- Temporal differentiation in LCA
- Systems dynamics tools
- Assessment of future and present environmental impact
- Case studies
Lecture notesLecture slides and further documents will be made available on Moodle.
102-0248-00LInfrastructure Systems in Urban Water Management Information
Prerequisites: 102-0214-02L Urban Water Management I and 102-0215-00L Urban Water Management II.
W3 credits2GJ. P. Leitão Correia , M. Maurer, A. Scheidegger
AbstractAn increasing demand for infrastructure management skills can be observed in the environmental engineering practice. This course gives an introductory overview of infrastructure management skills needed for urban water infrastructures, with a specific focus on pipe deterioration and engineering economics.
ObjectiveAfter successfully finishing the class, the participants will have the following skills and knowledge:
- They can perform basic engineering economic analysis
- Know the typical value and costs involved in running a wastewater infrastructure
- Know the key principles of infrastructure management
- Know how to quantify the future rehabilitation demand
ContentThe nationwide coverage of water distribution and wastewater treatment is one of the major public works achievements in Switzerland and other countries. Annually and per person, 135,000 kg of drinking water is produced and distributed and over 535,000 kg of stormwater and wastewater is drained. These impressive services are done with a pipe network with a length of almost 200,000 km and a total replacement value of 30,000 CHF per capita.

Water services in Switzerland are moving from a phase of new constructions into one of maintenance and optimization. The aim today must be to ensure that existing infrastructure is professionally maintained, to reduce costs, and to ensure the implementation of modern, improved technologies and approaches. These challenging tasks call for sound expertise and professional management.

This course gives an introduction into basic principles of water infrastructure management. The focus is primarily on Switzerland, but most methods and conclusions are valid for many other countries.
Lecture notesThe script 'Engineering Economics for Public Water Utilities' can be downloaded on the course website:
Link
LiteratureSee the reading resources on the course website:
Link
Prerequisites / NoticeCourse website:
Link
701-0104-00LStatistical Modelling of Spatial DataW3 credits2GA. J. Papritz
AbstractIn environmental sciences one often deals with spatial data. When analysing such data the focus is either on exploring their structure (dependence on explanatory variables, autocorrelation) and/or on spatial prediction. The course provides an introduction to geostatistical methods that are useful for such analyses.
ObjectiveThe course will provide an overview of the basic concepts and stochastic models that are used to model spatial data. In addition, participants will learn a number of geostatistical techniques and acquire familiarity with R software that is useful for analyzing spatial data.
ContentAfter an introductory discussion of the types of problems and the kind of data that arise in environmental research, an introduction into linear geostatistics (models: stationary and intrinsic random processes, modelling large-scale spatial patterns by linear regression, modelling autocorrelation by variogram; kriging: mean square prediction of spatial data) will be taught. The lectures will be complemented by data analyses that the participants have to do themselves.
Lecture notesSlides, descriptions of the problems for the data analyses and solutions to them will be provided.
LiteratureP.J. Diggle & P.J. Ribeiro Jr. 2007. Model-based Geostatistics. Springer.

Bivand, R. S., Pebesma, E. J. & Gómez-Rubio, V. 2013. Applied Spatial Data Analysis with R. Springer.
Prerequisites / NoticeFamiliarity with linear regression analysis (e.g. equivalent to the first part of the course 401-0649-00L Applied Statistical Regression) and with the software R (e.g. 401-6215-00L Using R for Data Analysis and Graphics (Part I), 401-6217-00L Using R for Data Analysis and Graphics (Part II)) are required for attending the course.
351-0778-00LDiscovering Management
Entry level course in management for BSc, MSc and PHD students at all levels not belonging to D-MTEC.
This course can be complemented with Discovering Management (Excercises) 351-0778-01L.
W3 credits3GL. De Cuyper, S. Brusoni, B. Clarysse, S. Feuerriegel, V. Hoffmann, T. Netland, G. von Krogh
AbstractDiscovering Management offers an introduction to the field of business management and entrepreneurship for engineers and natural scientists. The module provides an overview of the principles of management, teaches knowledge about management that is highly complementary to the students' technical knowledge, and provides a basis for advancing the knowledge of the various subjects offered at D-MTEC.
ObjectiveThe objective of this course is to introduce the students to the relevant topics of the management literature and give them a good introduction in entrepreneurship topics too. The course is a series of lectures on the topics of strategy, innovation, marketing, corporate social responsibility, and productions and operations management. These different lectures provide the theoretical and conceptual foundations of management. In addition, students are required to work in teams on a project. The purpose of this project is to analyse the innovative needs of a large multinational company and develop a business case for the company to grow.
ContentDiscovering Management aims to broaden the students' understanding of the principles of business management, emphasizing the interdependence of various topics in the development and management of a firm. The lectures introduce students not only to topics relevant for managing large corporations, but also touch upon the different aspects of starting up your own venture. The lectures will be presented by the respective area specialists at D-MTEC.
The course broadens the view and understanding of technology by linking it with its commercial applications and with society. The lectures are designed to introduce students to topics related to strategy, corporate innovation, corporate social responsibility, and business model innovation. Practical examples from industry will stimulate the students to critically assess these issues.
Prerequisites / NoticeDiscovering Management is designed to suit the needs and expectations of Bachelor students at all levels as well as Master and PhD students not belonging to D-MTEC. By providing an overview of Business Management, this course is an ideal enrichment of the standard curriculum at ETH Zurich.
No prior knowledge of business or economics is required to successfully complete this course.
351-0778-01LDiscovering Management (Exercises)
Complementary exercises for the module Discovering Managment.

Prerequisite: Participation and successful completion of the module Discovering Management (351-0778-00L) is mandatory.
W1 credit1UB. Clarysse
AbstractThis course is offered complementary to the basis course 351-0778-00L, "Discovering Management". The course offers an additional exercise in the form of a project conducted in team.
ObjectiveThis course is offered to complement the course 351-0778-00L. The course offers an additional exercise to the more theoretical and conceptual content of Discovering Management.

While Discovering Management offers an introduction to various management topics, in this course, creative skills will be trained by the business game exercise. It is a participant-centered, team-based learning activity, which provides students with the opportunity to place themselves in the role of Chief Innovation Officer of a large multinational company.
ContentAs the students learn more about the specific case and identify the challenge they are faced with, they will have to develop an innovative business case for this multinational corporation. Doing so, this exercise will provide an insight into the context of managerial problem-solving and corporate innovation, and enhance the students' appreciation for the complex tasks companies and managers deal with. The exercise presents a realistic model of a company and provides a valuable learning platform to integrate the increasingly important development of the skills and competences required to identify entrepreneurial opportunities, analyse the future business environment and successfully respond to it by taking systematic decisions, e.g. critical assessment of technological possibilities.
363-1039-00LIntroduction to NegotiationW3 credits2GM. Ambühl
AbstractThe course combines different lecture formats to provide students with both the theoretical background and the practical appreciation of negotiation. A core element of the course is an introduction to the concept of negotiation engineering.
ObjectiveStudents learn to understand and to identify different negotiation situations, analyze specific cases, and discuss respective negotiation approaches based on important negotiation methods (i.a. Game Theory, Harvard Method).
ContentThe course combines different lecture formats to provide students with both the theoretical background and the practical appreciation of negotiation. A core element is an introduction to the concept of negotiation engineering. The course covers a brief overview of different negotiation approaches, different categories of negotiations, selected negotiation models, as well as in-depth discussions of real-world case studies on international negotiations involving Switzerland. Students learn to deconstruct specific negotiation situations, to differentiate key aspects and to develop and apply a suitable negotiation approach based on important negotiation methods.
LiteratureThe list of relevant references will be distributed in the beginning of the course.
101-0530-00LReal Options for Infrastructure Management Restricted registration - show details
Number of participants limited to 12.
W3 credits2GC. Martani
AbstractThe course will provide an introduction to the paradigm of flexibility/ real option for infrastructure management. It will also provide insights on the tools to model uncertainty and class applications on example cases.
ObjectiveUpon successful completion of this course students will be able:
- To recognize and model uncertainty affecting infrastructure;
- To identify possible interventions on infrastructure
- To develop dynamic model for simulating future scenarios, considering uncertainty
ContentPart 1: Introduction to the concept of flexibility in engineering, including the problem of the flaw of average on traditional engineering design processes.
Part 2: Explanation of the real option methodology and of the main methods for uncertainty modelling, including binomial trees and Monte Carlo simulations.
Part 3: Application in class of the real option methodology on two example cases.
LiteratureA list of relevant publications for the course will be given out before the first class.
101-0523-00LIndustrialized Construction Restricted registration - show details W4 credits3GD. Hall
AbstractThis course offers an introduction and overview to Industrialized Construction, a rapidly-emerging concept in the construction industry. The course will present the driving forces, concepts, technologies, and managerial aspects of Industrialized Construction, with an emphasis on current industry applications and future entrepreneurial opportunities in the field.
ObjectiveBy the end of the course, students should be able to:
1. Describe the characteristics of the nine integrated areas of industrialized construction: planning and control of processes; developed technical systems; prefabrication; long-term relations; logistics; use of ICT; re-use of experience and measurements; customer and market focus; continuous improvement.
2. Assess case studies on successful or failed industry implementations of industrialized construction in Europe, Japan and North America.
3. Propose a framework for a new industrialized construction company for a segment of the industrialized construction market (e.g. housing, commercial, schools) including the company’s business model, technical platform, and supply chain strategy.
4. Identify future trends in industrialized construction including the use of design automation, digital fabrication, and Industry 4.0.
ContentThe application of Industrialized Construction - also referred to as prefabrication, offsite building, or modular construction – is rapidly increasing in the industry. Although the promise of industrialized construction has long gone unrealized, several market indicators show that this method of construction is quickly growing around the world. Industrialized Construction offers potential for increased productivity, efficiency, innovation, and safety on the construction site. The course will present the driving forces, concepts, technologies, and managerial aspects of Industrialized Construction. The course unpacks project-orientated vs. product-oriented approaches while showcasing process and technology platforms used by companies in Europe, the UK, Japan, and North America. The course highlights future business models and entrepreneurial opportunities for new industrialized construction ventures.

The course is organized around a group project carried out in teams of 3-4. The project begins in week 6 of the course, and collaborative group work will occur during the Wednesday sessions. Teams will be required to propose a framework for a new industrialized construction venture including the company’s product offering, business model, technical platform, and supply chain strategy.

The planned course activities include a 1/2 day factory visit (UPDATE confirmed date is Friday, March 20), a tour of the NCCR dfab laboratory, and five reflection assignments. Students who are unable to attend the visits can make up participation through independent research and the writing of a short paper.
LiteratureA full list of required readings will be made available to the students via Moodle.
101-0518-10LOrganisation of Infrastructure ProjectsW3 credits2GH. Ehrbar
Abstract-Life cycle analysis for infrastructure projects
-Project phases and milestones in major projects
-Management of major projects
-Introduction to the methods of stakeholder management
-Procurement models / principles for tenders
-Project Risk Management
ObjectiveImparting important knowledge regarding
-Life cycle considerations for infrastructure projects
-Project requirements of major projects
-Project phases and milestones in major projects
-Tasks, responsibilities and competencies in a project organization
-Introduction to the methods of stakeholder management
-Procurement models / Basics of tenders
-Methods of project risk management
-Cost and schedule control
-Quality management for major projects

The students will be able to organize an infrastructure project from the perspective of the principal in the most important matters.
ContentGeneral basics
-SIA 103, SIA 112, SIA 118, SIA 118/198
-Relevant laws and regulations
-Basics for Life Cycle Assessments
-Possible project organisation forms
-Requirements / Tasks / Competences of project management
-SIA 103, SIA 112, SIA 118, SIA 118/198

Project phases and quality gates
-Strategic Planning / Analysis of the needs
-preliminary study phase / methods for variant selection
-Project planning / project optimisation mechanisms
-Tendering / Procurement Models
-Realization / assurance of contract conformity
-Commissioning / completion
-Preservation and maintenance

Selected chapters
-Dealing with stakeholders / stakeholder management
-Averting threats / benefits of opportunities; the importance of project risk management / methods and their limits of application
-National and international procurement models
-Cost control and scheduling methods
-Methods of quality assurance and quality management
-Contract Management / Change Management
-Duties of the principal
-Requirements for project portfolio management

The course is primary based on examples of tunnel construction.
Lecture notesslides
LiteratureIn the course of the lecture reference will be made to the usual specialist literature
Prerequisites / NoticeAttending the course 101-0517-10 Construction Management for Tunneling and 101-0517-01 Project Management: Pre-Tender to Contract Execution is highly recommended, to be interested in major infrastructure projects.
101-0521-10LMachine Learning for Predictive Maintenance Applications Restricted registration - show details
The number of participants in the course is limited to 25 students.

Students interested in attending the lecture are requested to upload their transcript and a short motivation responding the following two questions (max. 200 words):
-How does this course fit to the other courses you have attended so far?
-How does the course support you in achieving your goal?
The following link can be used to upload the documents.
Link
W8 credits4GO. Fink
AbstractThe course aims at developing machine learning algorithms that are able to use condition monitoring data efficiently and detect occurring faults in complex industrial assets, isolate their root cause and ultimately predict the remaining useful lifetime.
ObjectiveStudents will
- be able to understand the main challenges faced by predictive maintenance systems
- learn to extract relevant features from condition monitoring data
-learn to select appropriate machine learning algorithms for fault detection, diagnostics and prognostics
-learn to define the learning problem in way that allows its solution based on existing constrains such as lack of fault samples.
- learn to design end-to-end machine learning algorithms for fault detection and diagnostics
-be able to evaluate the performance of the applied algorithms.

At the end of the course, the students will be able to design data-driven predictive maintenance applications for complex engineered systems from raw condition monitoring data.
ContentEarly and reliable detection, isolation and prediction of faulty system conditions enables the operators to take recovery actions to prevent critical system failures and ensure a high level of availability and safety. This is particularly crucial for complex systems such as infrastructures, power plants and aircraft engines. Therefore, their system condition is increasingly tightly monitored by a large number of diverse condition monitoring sensors. With the increased availability of data on system condition on the one hand, and the increased complexity of explicit system physics-based models on the other hand, the application of data-driven approaches for predictive maintenance has been recently increasing.
This course provides insights and hands-on experience in selecting, designing, optimizing and evaluating machine learning algorithms to tackle the challenges faced by maintenance systems of complex engineered systems.

Specific topics include:

-Introduction to condition monitoring and predictive maintenance systems
-Feature extraction and selection methodology
-Machine learning algorithms for fault detection and fault isolation
-End-to-end learning architectures (including feature learning) for fault detection and fault isolation
-Unsupervised and semi-supervised learning algorithms for predictive maintenance
-Machine learning algorithms for prediction of the remaining useful life
-Performance evaluation
-Predictive maintenance systems at fleet level
-Domain adaptation for fault diagnostics
-Introduction to decision support systems for maintenance applications
Lecture notesSlides and other materials will be available online.
LiteratureRelevant scientific papers will be discussed in the course.
Prerequisites / NoticeStrong analytical skills.
Programming skills in python are strongly recommended.
103-0448-01LTransformation of Urban Landscapes
Only for masters students, otherwise a special permit of the lecturer is necessary.
W3 credits2GJ. Van Wezemael, A. Gonzalez Martinez
AbstractThe lecture course addresses the transformation of urban landscapes towards sustainable inward development. The course reconnects two largely separated complexity approaches in «spatial planning» and «urban sciences» as a basic framework to look at a number of spatial systems considering economic, political, and cultural factors. Focus lies on participation and interaction of students in groups.
Objective- Understand cities as complex adaptive systems
- Understand planning in a complex context and planning competitions as decision-making
- Seeing cities through big data and understand (Urban) Governance as self-organization
- Learn Design-Thinking methods for solving problems of inward development
- Practice presentation skills
- Practice argumentation and reflection skills by writing critiques
- Practice writing skills in a small project
- Practice teamwork
ContentStarting point and red thread of the lecture course is the transformation of urban landscapes as we can see for example across the Swiss Mittelland - but in fact also globally. The lecture course presents a theoretical foundation to see cities as complex systems. On this basis it addresses practical questions as well as the complex interplay of economic, political or spatial systems.

While cities and their planning were always complex the new era of globalization exposed and brought to the fore this complexity. It created a situation that the complexity of cities can no longer be ignored. The reason behind this is the networking of hitherto rather isolated places and systems across scales on the basis of Information and Communication Technologies. «Parts» of the world still look pretty much the same but we have networked them and made them strongly interdependent. This networking fuels processes of self-organization. In this view regions emerge from a multitude of relational networks of varying geographical reach and they display intrinsic timescales at which problems develop. In such a context, an increasing number of planning problems remain unaffected by either «command-and-control» approaches or instruments of spatial development that are one-sidedly infrastructure- or land-use orientated. In fact, they urge for novel, more open and more bottom-up assembling modes of governance and a «smart» focus on how space is actually used. Thus, in order to be effective, spatial planning and governance must be reconceptualised based on a complexity understanding of cities and regions, considering self-organizing and participatory approaches and the increasingly available wealth of data.
LiteratureA reader with original papers will be provided via the ILIAS system.
Prerequisites / NoticeOnly for masters students, otherwise a special permit of the lecturer is necessary.
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