Courses in Technology and Innovation Management for exchange students
Objective:
Strategic Planning:
Students know and understand:
• the nature of strategy and different practices of performance evaluation
• analysis of the relevant competitive environment of companies
• Investigation of capabilities and resources within the company
• Nature and sources of sustainable competitive advantages of different layors of strategy development
Students acquire the following abilities:
• Capture and systemize the complexity of strategy development
• Analyzing and evaluate the relevant conditions of strategic management
• Critical questioning the instruments of strateg. management and apply it to examples from corporate practice Innovation management
The students know and understand:
• the need for and the nature of innovations
• the classification of innovation management in corporate management
• the concepts and strategies of innovation management
• the resources and methods of innovation management
• the organizational forms of innovation management
The students acquire the skills:
• Recognize and evaluate innovation opportunities
• To transfer innovation needs into innovation projects
• To acquire the necessary resources in the corporate environment
• Developing innovation strategies and applying context-specific concepts and instruments for their implementation
Content:
Strategic planning process:
• Nature of strategy, goals, values and performance, fundamentals of industry analysis, expansion of industry and competition analysis, analysis of resources and skills, nature and sources of competitive advantages, business strategies in different industries, diversification strategies, management of strategic change, current trends in the strategic management.
Innovation management:
• Generic innovation process, information search in practice, evaluation and selection of ideas, innovation strategies, financing of innovations, innovation cooperation (open innovation, lead-user approach),implementation of innovation projects, resistance to innovations, innovation culture, innovation projectmanagement
Objective:
Students are able to model practical problems into graph theory problems. They do understand algorithms for determining Eulerian cycles, shortest paths and minimal spanning trees. Also, they know why the Travelling Salesman Problem is very difficult and are able to apply various methods for finding a goodsolution.
Content:
Algorithm of Hierholzer for finding Eulerian trails and cycles, Breadth First Search and Algorithm of Dijkstra for determining shortest paths, Algorithm of Kruskal for determining minimal spanning trees, approximative and heuristic algorithms for solving the Travelling Salesman Problem, Branch and Boundmethod
Objective:
Students know the basics and methods of agile (software) development with the focus on requirements engineering as a part of the digital transformation process. In addition, they are able to use techniques and concepts of product line engineering and technical innovation management and integrate them into agile procedure.
Content:
• Classical Requirements Engineering
• Agiles Manifest and Principles
• (Software-)Kanban
• Feature Driven Development
• Scrum
• Agiles Requirements Engineering
• Requirements in Teams
• Agiles Portfolio Management and Planning
• Continious Development and Improvement
• Software Product Lines
Objective:
Students know the basic terms and models of information retrieval, data mining, and knowledge discovery. They are able to understand methods of data mining and machine learning using special tools and to apply them e. g. in industry 4.0 management
Content:
Information Retrieval
• basic terms and foundations
• knowledge discovery process
• process models
Methods
• regression and correlation
• decision trees
• cluster analysis
• association rules
• neural networks
Aim of the Module:
The students get insight into the design of xR technologies ranging from augmented to virtual reality.They will learn basics of geometric modeling and model optimization. They will learn about the tracking, projection and display technologies and basic computer graphic skills. In the field of industrial-xR students get to know the value of xR in the industry and about connectivity of virtual with real components.
Content:
Aim of the Module:
Students know the basics and methods of elements and network technologies with a focus on smarthome. Furthermore, they are able to apply techniques and concepts from the field of smart home engineering, components for smart homes, as well as technical innovation management and to integrate them into the construction of an overall system.
Content:
• Introduction
• Basic transmission techniques
• Basic network techniques
• Components of the smart home applications
• Functional safety (definition, examples, models, Standardization, limits, risk analysis, system behavior)
• Relationship to IT security
• Applications in the area of Ambient Assisted Living
• Design and implementation of overall smart home systems
Objective of the Module:
Digital Business Models
Students learn how to depict Digital Business Model Canvas based on Osterwalder et all. This model aims to show at a glance how a company earns its money today and in the digital future. By analysing 9 different aspects of possible digitalisization like Key Ressources or Customer Relationship the students estimate the overall as-is digitalization grade of a company first and second identify aspects to improve (like Value contribution or Key activities).
They learn how to depict all 9 aspects based on an integrated information model architecture like Enter-prise GPS and understand how these are implemented using business software such as SAP S/4 HANA. Accordingly, they are able to monitor and control the movement of money, goods and information within a company. Students learn how to differentiate between various Layers and Levels of the EnterpriseGPS model architecture and they are able to understand its horizontal and vertical navigation based ona BPM tool like ARIS correctly.
Idea Engineering
Students learn to use different Idea Engineering methods to generate new ideas. These methods will be used on a concreate case study to generate different ideas for new services of an organization. Six different groups present their own view on idea engineering methods or innovation processes and moderate a session with their class mates. The aim is to know when to use which process/method and how to use it in practise
Content:
Idea Engineering:
1) Introduction into Lecture with a Case Study
2) Theory of Innovation and Innovation Management
3) Different Idea Engineering Methods in Detail
4) Innovation Processes
5) Design Thinking Process
6) Business Model Innovation
Different language courses on different levels will be offered. A short entry test will be made at the beginning of the semester to identify suitable courses.
Objective:
Students know and understand the thinking behind technical safety, including functional safety and IT-security. Students are familiar with the relevant international standards. Students are able to perform risk analysis and document them. Students are able to use their gained knowledge during the design, implementation and launch of safe control algorithms. Students are not able to design systems or perform safety verifications.
Content:
• Introduction
• Safety term and basic approach to achieve safety
• Device safety
• Functional Safety (definition, examples, models, standardization, limits, risk analysis, system behaviour,communication media)
• Connections to IT-security
• Ways to achieve safety
• Draft and implementation of safe control algorithms for devices
Objective:
The students know the essential methods of technology assessment and technology monitoring and are able to select and apply suitable methods. They can evaluate technological developments in consideration of sustainability criteria and derive recommendations for further action. They know selected methods in the field of sustainabality, their areas of application and can interpret the results. Students are able to analyse specific resources and derive suitable information. Students can evaluate innovative technologies in a project from an innovative and sustainable perspective and present the results
Content:
• Introduction in TAS
• Analysis of megatrends as drivers of innovation
• Methods of technology assessment and monitoring
• Participatory technology development and assessment
• Introduction to Sustainability
• Methods for assessing sustainability
• Sustainable Marketing
Objective:
Candidates are well-versed in Data Analytics based on Big Data infrastructure and Big Data processing,especially in regards to Geoinformation. They know how to import, extract, manipulate, process and analyse spatial data as well as financial or industrial time series.
Content:
Big Data:
• Definitions: What is Big Data, Data Science, Machine Learning and Artificial Intelligence?
• Big Data
• Map-Reduce
• Spark, Hadoop, Kafka
• Data Warehousing
• Machine Learning
• Supervised Learning
• Unsupervised Learning
• Pattern Recognition and Clustering
• Dimensionality Reduction Techniques
• Artificial Neural Nets
• Data Analytics
• The exponential function
• Correlation vs. Causation
• Representation theory and scientific communication
• Big Data Ethics
• Data privacy, GDPR
• The discrimination problem of ML
• Ethics of autonomous decision making
Geoinformation:
• Ellipsoid models of the Earth
• Spatial reference systems, scale
• characteristics of spatial data: geometry, topology, attributes, time
• raster and vector model
• acquisition (digitalization from maps, GPS-supported field data collection, remote sensing)
• storage and administration of spatial data (spatial databases)
• introduction to GIS: QGIS and ArcGIS online
• analysis methods, e. g.
• distance- and area-based methods (sizes, centroids etc.)
• overlay
• buffering
• Delauney triangulation
• Thiessen polygons
• spatial interpolation (e. g. IDW, Kriging)
• visualisation
• cartographic principles
• 2D maps
• 3D models (including 3D analysis methods)
• interoperable GI services and Web Mapping
• Web Mapping Services
• Geography Markup Language
• standards of the Open Geospatial Consortium (OGC)
• exemplary open Web-Mapping tools
• open, spatial data
• guidelines and standards (from ISO, OGC, EU (e. g. INSPIRE))
• all themes are supported by exercises using QGIS, ArcGIS online and other tools
Objective:
The student works alone on a scientific project of his choice under supervision. In addition knowledge of the relevant subject area, knowledge of scientific work as well as key and methodological skills (presentation, presentation of the current state of knowledge on the basis of a literature research, proposal to close the gap; Planning, implementation and interpretation of experiments, discussion, evaluation of scientific results, etc.) are provided. The possible subject areas can be innovation fields from the research focus of the corresponding supervising professor.
Unit: Paper Reading Group
Students read selected papers individually in preparation for the meeeting (a.k.a. Paper Reading Group).
During the meeting, the student in charge will give a short presentation summarizing the paper and lead a discussion about the paper during the meeting.
Unit: Research Methods and Academic Writing
The participants of the lecture can
• correctly classify sources and cite them accordingly, observing different citation styles
• independently compose academic texts which stylistically and linguistically match the research standard on a Master level
• explain, evaluate and apply research strategy and research process
• explain, evaluate and apply selected research design concepts
• explain, evaluate and apply selected methods of qualitative and
• quantitative research
Content:
Unit: Research Methods and Academic Writing:
• Scientific project management
• Literature research, quality assessment of scientific literature
• Scientific publication system (conferences, journals, workshops, U)
• Scientific writing
• Scientific presentation
• Academic Writing: Style, Citations, Paraphrasing, Punctuation, Literature Management
• Research strategy and process
• Research design (Experimental, cross sectional, longitudinal, case study, comparative)
• Qualitative research (Action research, case study research, ethnographic research, grounded theory)
• Quantitative research and mixed methods
• Study design
• Guidelines to ensure good scientific practice
• Evaluation of scientific work (reviews)
Unit: Project Work
• Processing of a scientific project
• Literature research
• Presentation
• Carrying out experiments/implementation of the idea as a prototype
• Approaches to commercial exploitation
• Discussion/defense of own results
• Scientific writing
• Independent work
Different language courses on different levels will be offered. A short entry test will be made at the beginning of the semester to identify suitable courses.
