Many companies still rely on manual processes for CAM planning. These are time-consuming and error-prone. This is why we are developing a prototype for the automation of CAM planning in the Factory-X project together with leading companies such as Siemens and DMG Mori. At the beginning of the planning process, it is necessary to recognise the component features (e.g. free-form surfaces). This can be carried out based on rules or using artificial intelligence (AI). As part of your work, you will analyse both approaches and compare them with each other.

You will support us with:

• Automation of CAM processes
• Implementation of a machine learning model for recognising component features
• Development of an initial prototype

Ideally you have:

• Interest in machine learning and programming
• Experience in working with CAD programmes such as Siemens NX

Are you interested in digital data-based manufacturing technologies? Help develop data acquisition and analysis systems for CNC machines. You will support us, for example, in projects on intelligent manufacturing technologies, magnetic guidance systems and digital CNC systems. From simulation to application and research into new technologies on state-of-the-art test stands and machines, you will gain practical insights into current digitalisation concepts, digital twins and the latest innovations in manufacturing technology.

Your tasks:

• Development of a data acquisition system
• Signal processing and sensor data analysis (including experimental tests)
• Application of machine learning

Desirable skills and knowledge:

• Good command of German and English
• Interest in machine technologies, data analysis and control engineering
• Knowledge of machine tools and manufacturing technology
• Experience in using MATLAB and knowledge of TwinCAT or PLC

Do you love code, data and innovative technologies? Then work with us on a real high-tech topic with industry relevance. In the project, you will combine AI and machining. You will investigate the complex interactions between additive manufacturing (3D printing) and final machining (milling) of lightweight structures for aviation. These delicate, often highly flexible components are highly optimised for minimal use of materials – which makes processing them a real challenge. At our company, you will work at the interface between machining technology, simulation and artificial intelligence.

You will support us with:

• Modelling and programming: developing machine learning and classic models to predict milling forces
• Optimisation and testing: improving the accuracy of models through intelligent tuning
• Analysis and validation: data analysis and structured preparation for training processes, validation of models through real milling tests
• Tool development: integrating models into existing simulation environments

Ideally you have:

• Knowledge of Python or C#
• An interest in data analysis, modelling and machine learning techniques
• Previous experience of working with GitLab

In the EmSim project, you will work with us to analyse failure-prone milling processes. The aim is to identify and classify patterns on the basis of spindle current data. The aim of your work is to develop a decision logic to optimise monitoring limits. The analysis and modeling will be carried out using Python.

Your tasks:

• analysis of existing data sets from machining tests in Python
• development of a decision logic for the adjustment of monitoring limits
• verification of the developed logic

Desirable skills and knowledge:

• interest in machining technologies and data analysis
• initial experience with machine learning methods or interest in familiarising yourself with them
• good programming skills in C# or Python

AI-based prediction of component quality enables cost-effective 100 % quality control in manufacturing. In this study a real production dataset has to be analyzed and different AI models evaluated. The goal is to calculate quality parameters with high accuracy based on features in process signals. The focus of the work is on sequence-based AI approaches, which are particularly suitable for processing time series.

Your tasks:

• programming Python scripts for data analysis and preprocessing
• training and evaluating AI models

Desirable skills and knowledge:

• proficiency in German or English
• independent and structured working style
• strong knowledge in time series analysis with Python