of all DIT graduates
will find a job
within 2 months
#productionmanagement #logistics #sustainability #quality #lean #statistic #AI #machinelearning #deeplearning
#dataanalysis #bigdata #innovative #englishpostgraduateprogramme #industrialengineering
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 & 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.
Degree: Master of Engineering (M.Eng.)
Duration: 3 semesters (1.5 years)
Start: 1 October (winter semester)
Application period: 15 April - 15 July
Taught in: English
Content of the written entrance examination:
Section A: Mathematics (21 points)
Section B: Physics (17 points)
Section C: Production & Logistics (16 points)
Section D: Statistics (8 points)
Section E: Simulation (8 points)
Section F: Computer Science (20 points)
Concerning all applications for the winter semester 2023/2024:
If German is not your native language, proof of sufficient German skills is necessary.
If English is not your native language, proof of sufficient English skills is necessary.
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:
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:
Seize the fantastic opportunities that will open up to you in your prospective career path!
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 1st and 2nd semester. Read on to find out more details of each case study:
This case study in the 1st 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 optimisation methods.
This case study in the 2nd 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 2nd 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.
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":
|Machine Learning and Deep Learning in Production and Logistics||4||5|
|Advanced Statistical Methods & Optimisation||4||5|
|Production and Logistic Management||4||5|
|Digital Tools in Development and Production||4||5|
|Case Study "AI Project"||4||5|
|Technology and Innovation Management||4||5|
|Advanced Intelligent Systems||4||5|
|Case Study Intelligent Systems in Production||4||5|
|Digital Production Systems||4||5|
|Case Study "Production Systems"||4||5|
|Compulsory Technical Elective (FWP)||4||5|
|3rd Semester (Online)||SWS||ECTS|
|Quality & Sustainability||4||5|
|Master's Seminar (two parts: Master colloquium (2 ECTS) and seminar series "Career Start into German Technology Companies")||-||2|