MSc Thesis: Design and Application of a Machine Learning Framework for Real World Systems in an Automation Environment

Placering
Västerås

MSc Thesis: Design and Application of a Machine Learning Framework for Real World Systems in an Automation Environment
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In ABB Robotics R&D Motion Control we have several Master thesis opportunities. The Motion Control department is responsible for a wide range of areas within the robot controller development spanning from modeling, identification, control design, optimization for path planning and numerous other motion control functionalities. Design and Application of a Machine Learning Framework for Real World Systems in an Automation Environment: Over recent years, machine learning and in particular deep learning based solutions have established themselves as highly effective for a wide range of tasks. However, to deploy them in an automation environment, they must not only run locally with limited compute but also enable continuous improvements and updates over the product’s life cycle. In this thesis, we will develop a framework addressing both requirements and then leverage it to design and deploy ML-based solutions for multiple tasks. We will begin by specifying a framework for the efficient development, deployment, and maintenance of ML models in embedded environments. To this end, we will focus on defining a clean interface to the ML-model enabling efficient inference, continuous learning, and updates to the model architecture over time. While establishing the framework described above, we will develop ML-based solutions for a real challenge like collision detection or predictive maintenance, using them first as a case-study to derive requirements and then to demonstrate the effectiveness of the resulting framework. Details: • Start: asap for a period of 6 months • 30 ECTS per student • Suitable for 1-2 students • On site ABB Robotics (Finnslätten) in Västerås (exceptions can be made)

Your responsibilities

• Investigate the requirements resulting from the objectives above under deployment on an edge platform
• Evaluate both open-source tools and commercial solutions against these requirements in a realistic environment
• Based on this evaluation, design a proof of concept. Then, implement it in a real-world control system, realizing one or multiple of the concrete tasks
• For any concrete task, a range of suitable ML models should be evaluated, motivated by solutions to similar problems discussed in literature. This part of the project will include an in-depth exploration of both the application domain and available data, including feature engineering and data preprocessing
• Finally, write a high-quality technical report, suitable for publication at an international conference

Your background

• Motivation to solve real world problems using state-of-the-art methods
• Background in computer science, statistics, engineering, or similar
• Good knowledge of Python
• Excellent problem solving skills
• Experience with code development and tools such as git, conda etc.
• Knowledge of AI & ML
• Good interpersonal skills

More about us
Recruiting Manager Niklas Durinder ([email protected]) and Jordis Herrmann ([email protected]) will answer your questions. Positions are filled continuously. Apply with your CV, academic transcripts and a cover letter in English via the ABB career page. We look forward to receiving your application (documents submitted in English are appreciated). If you want to discover more about ABB, take another look at our website www.abb.com. #LI-hybrid

Locations
Västerås, Sweden