Industry 4.0 & Management

Master of Science (M.Sc.)

Degree: Master of Science (M.Sc.)

Master’s Study Programme Industry 4.0 & Management

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.


4 Semester inclusive Thesis

Accreditation (Master)

The FOM University of Applied Sciences is accredited by the German Council for Science and Humanities for its special service to education and research and was the first private university in Germany to receive system-accreditation by the FIBAA in 2012. This seal of approval proves that the quality management of the FOM University meets the high standards of the Accreditation Council, the most important body for the quality of studies and education at German universities. In 2018 the FOM University received system-accreditation for further eight years. Thus, all courses of study offered by the FOM are accredited. A Master’s degree from the FOM University enables entry to a subsequent a PhD programme.
Multi-ethnic group of students sitting at desk in lecture hall of modern college and smiling happily, focus on young Middle-Eastern man wearing glasses, copy space

Studying full-time in India and Germany

Master’s degree on campus

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 the Indira Global Study Centre in Pune, India.

The first two semesters of the study programme will be held at the IGSC in India, and the third and fourth semester will take place at the FOM Hochschule at the German University Center in Essen, Germany.

What you need for admission

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

English language B2

All information on registration and tuition fees can be found on Indira Global Study Centre website.

Partner website
Dr. Punam Bhoyar
Director Indira Global Study Center (IGSC)

Semester Overview

Study programme

Decision Focussed Management

Traditional decision theory
Management decisions from a psychological perspective
Decisions in a strategy context

Information Systems in Production

Product development systems
Production planning systems
Production management systens
Case Study

Big Data Analytics

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, Cloud Computing & Internet of Things

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)
Intelligent Things
Technology concepts of modern digitalisation


Technical basis
Threats and risks
threar prevention

Artificial Intelligence

Development of the AI and essential concepts
Knowledge-based systems
Machine learning and data mining

Smart Technologies within the Value Chain

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
Data security
Impacts and effects of Industry 4.0

Technology & Sustainability

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

Design Thinking & Business Model Innovation

Lean start-up
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

Organisational Transformation

requirements of digitisation for the enterprise organisation
success factors of organisational
transformation processes
concepts of organisational change: organisational transformation

Digital Factory & Cyber-Physical Systems

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

Research Methods

Qualitative and quantitative research methods
Quantitative data analysis (applications with R, statistical test procedures, multivariate procedures)

Enterprise Architecture Management

summary EAM
organisational anchoring of EAM
business and IT-strategy
IT systems and IT architecture
EAM tools

Applied Project I

Applied Project II

Master Thesis

Subject to change.