In the age of digitalisation, the ability to analyse and process big data in industry has become indispensable.

In all manufacturing industries, there is an increasing demand for qualified specialists to read and use Big Data in production processes to make efficient strategic decisions, develop innovations to improve everyday workflow and increase companies’ competitiveness while ensuring quality and sustainability in the digital production chain.

Lectures combining machine learning, data analysis, data management and intelligent systems will help you to deepen your understanding of innovative methods of data processing. In addition to this, modules in Advanced Statistical Methods & Optimisation will prepare you for the increasing demands of AI in production, logistics and technology management.

The theory you study will be put into practise through three case studies in AI, intelligent systems in production, and production systems, which are created and supervised by engineers from manufacturing companies.

Main features of the programme:

• The programme is a balanced combination of lectures, seminars, and case studies
• Small learn groups provide you with personal support and intensive tuition
• Three AI case studies will help you to analyse problems independently and apply proposed solutions
• State-of-the-art science labs are equipped with excellent equipment to supply you with the perfect infrastructure to study high-tech areas of AI
• Compulsory German lessons equipe you with language skills for you to kick-start your prospective future career in Germany
• Cham’s international and multicultural campus community will make you feel at home

Course objectives:

You will gain expertise in production, logistics and technology management which will enable you to manage or accompany technical projects in your future career. You will become an expert in:

• Machine learning methods
• Data processing methods (including cloud computing, big data)
• Modern statistical methods and optimisation procedures
• Production and logistics management
• Digital production systems
• Digital tools in development and production
• Quality and sustainability

Career prospects:

After graduating, you are open to a wide range of career opportunities in all companies that handle large amounts of data, e.g. companies from the car or semiconductor industry including their suppliers, and other companies that want to manage digitalisation in their production processes. There are a range of engineering positions focusing on digital production systems open in areas such as development, production, production planning and management, quality management, or research and teaching.

Here are some typical examples of professional challenges you might work on in production:

• Development and increased efficiency of predictive maintenance techniques, such as the collection and cleaning of data, and the creation of ML models with the aim of predicting required maintenance at a precise time point before a machine malfunctions.
• Collecting and evaluating large amounts of data in the search for outliers, e.g. recognising products that are good in the functional test but could fail at customer level (outlier detection).
• Automating product inspection (we develop this technique in our SensorLab at the Cham campus). Sensors are specifically stressed to analyse their lifespan behaviour which generates data that can be used for lifespan predictions or even classifications.
• Analysis of production and product data to improve products.
• Improving stock keeping efficiency by using targeted prediction, consumption and/or sales data.
• The general digitalisation of production, such as the introduction of barcodes, and the networking of systems with each other and with the internet, etc.

Enjoy the fantastic opportunities that will open up to you in your prospective career path!