Master Thesis
2 days ago
Functional area:
Machine Learning
Education requirement:
Computer Science, Mechatronics, Electrical engineering (or similar engineering disciplines)
Level of thesis project:
Master thesis
Your role
The goal of the project is to design and evaluate Machine Learning models for specific sensor data processing in a pulsating tool for a specific function in an efficient way.
Background
Atlas Copco designs advanced high precision tools for the aerospace and automotive industry. The tools have many different sensors that help achieve optimal motor control and high precision in the performed operations.
By combining different sensor data together with a Machine Learning model, we may be able to reduce the number of sensors or achieve higher precisions than current solutions. Machine Learning models have shown great potential in the field.
Mission
- Build and use a test setup to collect sensor data from tool and external reference sensors for relevant use cases.
- Analyse the sensor data and explore what data is relevant and can be used as training data.
- Implement, train and verify different ML-models to evaluate that ML is a viable alternative for the specific function.
- Use modern methods to achieve an optimized and robust ML-model that works in an embedded environment.
Atlas Copco's Industrial Technique business area provides industrial power tools and systems, industrial assembly solutions, quality assurance products, software and service through a global network. The business area innovates for sustainable productivity for customers in the automotive and general industries, maintenance and vehicle service. Principal product development and manufacturing units are located in Sweden, Germany, the United States, United Kingdom, France, Japan and Hungary.
To succeed, you will need
Experience And/or Interest In The Following
- Machine Learning
- Signal processing
- Sensor fusion
- Embedded systems
Job location
This master thesis requires you to work on-site at our office in Stockholm, Sweden (SE).
Contact information
Supervisor: Wilhelm Nyberg,
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