Each module contains 3 ECTS. You choose a total of 10 modules/30 ECTS in the following module categories:
- 12-15 ECTS in technical scientific modules (TSM)
TSM modules teach profile-specific specialist skills and supplement the decentralised specialisation modules. - 9-12 ECTS in fundamental theoretical principles modules (FTP)
FTP modules deal with theoretical fundamentals such as higher mathematics, physics, information theory, chemistry, etc. They will teach more detailed, abstract scientific knowledge and help you to bridge the gap between abstraction and application that is so important for innovation. - 6-9 ECTS in context modules (CM)
CM modules will impart additional skills in areas such as technology management, business administration, communication, project management, patent law, contract law, etc.
In the module description (download pdf) you find the entire language information per module divided into the following categories:
- instruction
- documentation
- examination
Modules: 20
The goals of an organization can be efficiently pursued only through proper project management, as a means able to consistently tackle their needs. Thus the role of the Project Manager becomes essential, as responsible to achieve the objectives, respecting the constraints determined by the project context. Modern Project Managers must have in-depth technical and management knowledge.
The course provides the students…
Download full module description
Explore moreOne of the biggest challenges encountered in management is recognizing opportunities and making use of them while giving consideration to the associated risks. The constantly increasing dynamism and complexity of the environment in which companies and organizations operate is, however, making it difficult to take successful decisions. Multifactorial correlations, non-linearities, feedback effects and time lags make…
Download full module description
Explore moreThe module aims to explain the operational planning and management of innovations to students on the basis of an integrated innovation management model, as well as introducing them to the relevant concepts. This will enable students to establish links to various company-internal and company-external interfaces as part of innovation projects and to correctly interpret and influence these. In this module, students will…
Download full module description
Explore moreThe course introduces the concepts of Lean innovation and lean thinking. It also foster a complex serious-gaming session where the students can develop their own factory and implement a set of innovations. Indeed, the student will be able to devise and implement a production practice that considers to be waste the expenditure of resources for any goal other than the creation of value for the customer.
Download full module description
Explore moreCompanies are increasingly interested in conducting their activities so that a long-term future is assured for its business, society and environment. The purpose of this class is to deal with the well-recognized but sometimes vague concept of sustainability from an engineering perspective. The module is meant to introduce students to the implementation of sustainable management in industries and provide them with…
Download full module description
Explore moreThe CM_QRM addresses the most relevant basics in integrated quality and risk management. Theory is applied and specified by examples and case studies. The module concentrates on current standards and best practices on quality and risk management and introduces the most established approaches.
Download full module description
Explore moreStudents are introduced to statistical tools used in the industrial sector, and particularly in process and quality control. In this module, students learn to plan and conduct statistical evaluations independently.
Please note: An MSE cursus may not contain both similar statistics modules FTP_AppStat and FTP_PredMod. Students can only choose one of these modules.
Download full module description
Explore moreThe goal of this module is to teach the fundamentals of image processing, while putting emphasis on their mathematical and algorithmic principles. In addition, specific 2D and 3D industrial and biomedical applications will be treated.
Download full module description
Explore moreModelling, simulation and optimization are fundamental to solving problems in a number of fields of science, technology and life. Students will learn to design, implement, simulate, and optimize a model of dynamic system. First we will focus on the analysis of how different model structures can generate different behaviours, reproducing growth processes, but also goal seeking and oscillating behaviours. Then we focus…
Download full module description
Explore moreNatural, social, and engineered complex systems can be modelled as being composed of agents interacting with one another and their environment. This course introduces students to the theory, tools and techniques for understanding and solving problems related to such systems.
The course is composed of two parts. In the first one, both cooperative and selfish agents and interactions between them will be discussed. The…
Download full module description
Explore moreThe module gives students insight into the modeling and simulation of coupled effects (multiphysics). The module provides an overview on the different application fields of multiphysics modeling and simulation in industry. Students learn the methodical procedures that are necessary for successfully solving modeling and simulation problems in the different areas of engineering and physics. The consolidation and…
Download full module description
Explore moreThis course offers an introduction to optimization, emphasizing basic methodologies and underlying mathematical structures. Optimization refers to the application of mathematical models and algorithms to decision making. A large number of quantitative real-world problems can be formulated and solved in this general framework. Applications of optimization comprise, for instance, decision problems in production…
Download full module description
Explore moreIn this module, students learn which class of dynamical phenomena can be described with systems of ordinary differential equations. They learn to recognize the fundamental behavior patterns of these systems and also to develop simulation models for them.
Download full module description
Explore moreIn this module, basic and advanced robotics knowhow is developed necessary for leading-edge, innovative industrial and service applications with robot manipulators.
Download full module description
Explore moreMobile robots are complex mechatronic systems often interacting autonomously with their environment.
In the first part, the course provides theoretical fundamentals of mobile robot sensor fusion, planning, localization and mapping with examples in ROS. Tests of these complex systems can be conducted in simulated environments to speed up development and minimize risk of damage. Data from live tests can be recorded for…
Download full module description
Explore moreThis module treats methods of concept, dimensioning and development in the servo drive technology sector which are particularly compatible with the various industries.
Download full module description
Explore moreThe Machine and Production Operations Control is the core of the module, with focus on continuous time, motion and discrete event control of industrial systems. Practical laboratory activities are developed for both CNC (Computer Numerical Control) and PLC (Programmable Logic Control) programming.
Download full module description
Explore more
The course targets technical and application challenges related to the design of advanced robotic solutions for industrial and service applications. It addresses the design, engineering and optimization of serial and parallel kinematics robotic arms, as well as of mobile platforms.
The course will cover theoretical content and practical activities of mechanical design, programming and simulation, as well as…
Download full module description
Explore moreIn an automation system in manufacturing technology or process automation, sensors measure non-electric values and actuators, such as drives, influence the process. The individual components are controlled by control systems and automatic controllers, connected with industrial networks, and supervised by humans.
The emphasis of this module is on the selection and determination of the individual components, bearing in…
Download full module description
Explore moreModel Predictive Control (MPC) is an optimisation-based approach to control systems and processes. The general mathematical formulation of MPC allows it to be applied to a broad range of systems and considers system constraints intrinsically. The advances in optimisation methods and available computational power have made MPC a valuable alternative to classical control approaches also for fast dynamic systems. Today,…
Download full module description
Explore more