Master of Science (M.Sc.)
Degree: Master of Science (M.Sc.)
The economy is becoming increasingly digital and networked. The intelligent linking of IT and business management systems enables a more flexible, individual, and efficient production as well as an optimisation of the entire value chain. The goal of a more flexible production through networking goes hand in hand with ever shorter product cycles, improved business models and a digitalised value-added network. The core elements of an Industry 4.0 are automation, standardisation, digitisation, and networking as well as the merging of hardware and software.
In order to implement “Industry 4.0”, companies are dependent on specialized professionals who have both business management expertise and comprehensive skills in dealing with the key technologies of Industry 4.0.
With “Industry 4.0 & Management”, FOM has developed a future-oriented Master’s programme whose contents are specifically geared to these requirements. You will acquire both business expertise and management skills as well as sound specialist knowledge of the digital transformation of classic, industrial processes. In this way, you will prepare yourself for a wide range of possible applications in the context of Industry 4.0 and qualify for demanding positions and management tasks in nationally and internationally operating companies across all industries.
The Master’s degree in Industry 4.0 & Management will be completed with the academic degree Master of Science (M.Sc.). The degree will be awarded by FOM Hochschule für Oekonomie & Management.
Studying full-time in India and Germany
In cooperation with FOM Hochschule, students from India now also have the opportunity to participate in the Big Data & Business Analytics Master’s programme at Keystone Global Careers in Ahmedabad, India.
The first two semesters of the study programme will be held at Keystone Global Careers in India, and the third and fourth semester will take place at the FOM Hochschule at the German University Center in Essen, Germany.
Bachelor's degree with at least 60 credit points in (Economic-) Computer Science modules or (Economic-) Engineering
Bachelor's degree with least 60 credit points in subject related modules (for example, Mathematics, Statistics)
successfully completed oral entrance examination
Traditional decision theory
Management decisions from a psychological perspective
Decisions in a strategy context
Product development systems
Production planning systems
Production management systens
Data sources and data classification
Visual analytics/data discovery/explorative data analysis
AI methods such as machine learning
Computational intelligence: fuzzy logic, neuronal networks, evolutionary algorithms
Connectivity (e.g. networking, mobile radio, mobile devices)
Coud Computing (architecture, service concepts, intersection Big-Data and AI)
Sensor system (e.g. temperature sensors, position and acceleration sensors, pressure sensors)
Technology concepts of modern digitalisation
Threats and risks
Development of the AI and essential concepts
Machine learning and data mining
Industry 4.0 technologies within individual business processes of a manufacturing company (production IT, big data analytics, internet of things, artificial intelligence)
Industry 4.0 technologies within individual business process sections
Impacts and effects of Industry 4.0
The role of different actors in sustainable development
Sustainability assessment of products, services and processes
Technology transfer as an instrument of sustainable development
Sustainability relevant fields of technology
Methods of design thinking to formulate comprehensive and innovative problem and solution spaces
Basic principles of design thinking business systems and portals
Fundamentals in listening, reading, writing and speaking
Basic grammatical skills
Application in situations of everyday life
requirements of digitisation for the enterprise organisation
success factors of organisational
concepts of organisational change: organisational transformation
basics of cyber-physical production systems
fundamentals and application of robotics
fundamentals and classification of additive manufacuring
sustanability and ethical aspects in the context of smart production
Qualitative and quantitative research methods
Quantitative data analysis (applications with R, statistical test procedures, multivariate procedures)
organisational anchoring of EAM
business and IT-strategy
IT systems and IT architecture
Subject to change.