applied aI for digital production management, m.eng.
Faculty of Applied Natural Sciences & Industrial Engineering
Course Content
Create data management solutions for production processes
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 like "Advanced Statistical Methods & Optimization" 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 well-balanced combination of lectures, seminars, and case studies.
- Small study 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 equip 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.
All key information at a glance: Take a look at this brief introduction to the master's program in Applied AI for Digital Production Management.
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student case studies
Three AI case studies will help you to analyse problems independently and apply proposed solutions. These are an integrated element of the masters programme in the first and second semester. Read on to find out more details about each case study:
This case study in the first semester focuses on a topic from the areas of Machine Learning and Deep Learning in Production & Logistics, Advanced Statistical Methods & Optimisation, Data Management and Production Data Management (Acquisition and Control). Get to know and test existing techniques and learn to understand where limits are, including the range of possibilities using ML/DL in comparison to conventional optimization methods.
Summer semester 2024
Winter semester 2024/2025
This case study in the second semester covers a broad range related to production and production-related topics. For example, in the module "Intelligent Systems" of MSS, you could study text classification, chatbots, road damage detection, recognition of vehicles (traffic monitoring) and even the lifetime prediction of sensors.
This case study in the second semester focuses on concrete topics in "Digital Production Systems". This means design, improvement, and implementation of cyber-physical production systems (e.g. networking of systems with each other and with the internet), in addition to the simulation of production systems with specialised software packages, e.g. AnyLogic or Open Modellica.
After completing my Bachelor’s in Venezuela, I wanted to embrace a greater challenge and explore cutting-edge industry trends. Therefore, I decided to pursue my Master’s in Germany. At the DIT, I learned the AI fundamentals, understood its societal impact, and gained hands-on experience on its applications. Moreover, adapting to a new system, language, and culture, while thriving in an environment that encourages initiative and innovation, has made this experience highly rewarding.
I was interested in studying a master’s degree abroad because I wanted to acquire new experiences that would help me grow not only in my career but also as a person. As a student in the “Applied AI for Digital Production Management” master’s program at THD-Campus Cham, I learned diverse courses through case studies which boosted my career. I had many exciting experiences and new challenges: from meeting new friends and discovering German culture to working on AI projects and even trying to understand a few phrases in Bayrisch.
My passion for production management, particularly in the areas of supply chain management, logistics, data management, quality and sustainability management, and my curiosity about how AI influences these domains. This motivated me to purse a master’s degree with diverse specialization. When I came across the master program “Applied AI for Digitial Production Management” offered by THD-Campus Cham, I knew it was the perfect opportunity to realize my academic and professional goals. Studying at Campus Cham has been truly rewarding experiences – from beautiful and peaceful location to incredible expertise of highly knowledgeable professors. The diverse community of classmates from around the world has enriched my learning experiences, allowing me to exchange ideas and perspectives.
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
Subject Overview
Overview of lectures and courses, SWS (Semesterwochenstunden = weekly hours/semester) and ECTS (European Credit Transfer and Accumulation System) in the master's programme "Applied AI for Digital Production Management":
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 Sensor Lab 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.
Seize the fantastic opportunities that will open up to you in your prospective career path!