Lecturer: Filzmoser, Michael
Syllabus outline:
• Strategic managment
• The strategic management process (analysis, formulation, implementation, control)
• Internal and external strategic analysis
• Sources of competitive advantage (market-based, firm-based, and value creation view)
• Strategy and organization
• Strategy and innovation
Objectives and competences:
In this course, students develop a deep understanding of the topics described in the syllabus. In addition, students are enabled to use this newly gained knowledge in practice. More detailed information can be found in the sections "syllabus outline" and "intended learning outcomes".
Intended learning outcomes:
After successful completion of the course, students are able to …
• … describe central tasks and concepts of strategic management
• ... apply strategic management tools to solve problems and assignments
Lecturer: Ansari Chaharsoughi, Fazel; Khobreh, Marjan
Syllabus outline:
• Basics of Cyber Physical Production Systems (CPPS) related concepts and terminologies including Digitalization, Industry 4.0, Digital Transformation in Manufacturing Enterprises, IoT, Digital Twin, etc.
• Basic of Knowledge Management
• Knowledge Management 4.0 and Big Data
• Artificial Intelligence and Cognitive Science
• Human-Machine Interaction, Collaboration and Reciprocal Learning
• Collaborative Robotics
• Job Transformation in the Age of Industry 4.0
• CRISP-DM and Data Science Applications in Various Industrial Domains
• Knowledge-Based Maintenance (Maintenance wit/without sensing and computational technologies, Predictive and Prescriptive Maintenance, Text-Mining Applications in KBM, Industrial Use-cases)
• Knowledge Modeling and Representation with Ontology and Protégé Editor
• Human-Centered Cyber Physical Assembly Systems
• Excursion and Open Discussion at the TU Wien Pilot Factory Industry 4.0
Objectives and competences:
In this course, students develop a deep understanding of the topics described in the syllabus. In addition, students are enabled to use this newly gained knowledge in practice. More detailed information can be found in the sections "syllabus outline" and "intended learning outcomes".
Intended learning outcomes:
After successful completion of the course, students are able to …
• … define and recognize CPPS and its associated data-driven processes in operational and management dimensions of a smart factory.
• Characterize and map “knowledge holders”, “knowledge generators”, “knowledge users” and “knowledge assets” in the context of CPPS, including human and technological entities such as AI agents and collaborative robots.
• Select appropriate methods and/or tools (platforms) of “Artificial Intelligence” and “Data Science”, including machine learning and predictive data analytics, knowledge engineering and semantic technology for modeling and analyzing data, learning new patterns, and reasoning (including prediction).
• Design the knowledge map of a smart factory (e.g. TU Wien Pilot-Factory) and select required data analytics and knowledge engineering methods not only for processing and utilizing CPPS data but also for supporting decision making processes
Lecturer: Markus Pichlmair
Syllabus outline:
• Communication models
• Basics of perception
• Guides for creating a presentation
• Body language
• Practical exercises and feedback
Objectives and competences:
This course aims at improving the perception, communication skills, presentation techniques and basic rhetoric competencies.
Intended learning outcomes:
Knowledge and understanding:
After completing this course, the students:
• Have an improved perception of their environment as well as of themselves.
• Improved their skills in communication and building relationships
• Are aware of common presentation techniques and have acquired basic rhetoric competencies.
Lecturer: Sabine Theresia Köszegi
Syllabus outline:
• Introduction and theoretical foundations
• Organization of Human Resource (HR) Management
• HR planning, recruitment and selection
• Performance and reward management, training and development
• Leadership and management
• Specific topics of HR management
Objectives and competences:
The course provides the knowledge, tools and instruments necessary to manage human performance during the entire employee lifecycle. Further it adresses the analytical and synthetical skills in the evaluation of complex socio-economical problems, critical discussion and evalutation of alternative or conflicting theories and concepts. Interactive parts of the courses deepen teamwork and conflict management competences.
Intended learning outcomes:
Knowledge and understanding:
After completing this course, the students possess the theoretical foundations and basic instruments of Human Resource (HR) management and leadership.
Lecturer: Selim Erol, Fazel Ansari Chaharsoughi
Syllabus outline:
• Background and History of Management Information Systems (MIS)
• Typology and Examples of Management Information Systems (Types of MIS, Application areas of MIS, MIS and the industrial organization)
• Design and Engineering Process of MIS in the context of Cyber-physical Production Systems (Systems/Software Engineering Processes and Methods)
• Architecture of Information Systems (Components (Hard-, Software) of an Information System, Layers)
• Modelling of Management Information Systems – Requirements specification (Informal Requirements Elicitation and Analysis (Interviews, Personas, …), Semi-formal requirements specification techniques (UML use-case modelling, BPMN process modelling, Scenarios))
• Modelling of Management Information Systems – System specification (Database specification techniques (ER, UML class modelling), Application logic specification techniques (Process, Activity modelling))
• User-interface specification techniques (Wireframing, Storyboards, …)
• Management Information System Selection and Evaluation
• Case-studies of MIS
Objectives and competences:
This course aims at introducing the basics of information systems (IS) and software design with a focus on cyber-physical production systems. This covers the theoretical foundations and practical methods for the design and specification of cyber-physical production systems from an information systems perspective. The course aims to close the knowledge gap between classical industrial engineering competencies and information systems design competencies.
Intended learning outcomes:
Knowledge and understanding:
After completing this course, the students are capable of:
• Naming and distinguishing different methodological approaches for information systems design and evaluation.
• Elicitation and specification of requirements for the design of cyber-physical production systems.
• Modelling of cyber-physical production systems from an information systems and engineering perspective.
• Selecting and applying appropriate systems modelling methods and tools according to domain/company/process-specific problems.