Optimizing Lithium-Ion Battery Cell Production through Deep Learning

vor 4 Wochen


Aachen, Nordrhein-Westfalen, Deutschland Fraunhofer-Gesellschaft Vollzeit

At Fraunhofer-Gesellschaft, we are committed to developing key technologies that drive innovation and sustainability. In the department of Production Quality, our team applies digital technologies to optimize production processes, leveraging artificial intelligence to make production more efficient and sustainable. One of our key areas of focus is optimizing the production processes for lithium-ion battery cells and fuel cells.

Within this scope, we are seeking a master's thesis candidate to investigate deep learning-based defect detection approaches. To achieve this, we will utilize roll-to-roll processes for the efficient coating of electrodes. However, defects can occur during this process step, resulting in high reject rates. To address this challenge, we are developing a modern deep learning-based defect detection system. A crucial step in the application of this system is the reduction of the annotation effort by process experts. Transfer learning approaches for deep learning models are a promising way to reduce this effort. Therefore, within the scope of this master's thesis, different deep-learning approaches will be implemented and evaluated.

Key responsibilities will include:

  • Selection of suitable deep-learning approaches in the field of transfer learning
  • Training of deep learning models for defect detection and analysis of the results
  • Implementation of suitable deep learning models in the defect detection system

Requirements for the candidate include:

  • Studying mechanical engineering, computer science, or a comparable subject
  • First experience with PyTorch and deep learning is favorable
  • A high degree of initiative, independence, and problem-solving skills

We offer ideal conditions for practical experience alongside your studies, a GPU server for data science applications, and flexible working arrangements to combine study and job in the best possible way. We value and promote the diversity of our employees' skills and welcome all applications, regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation, and identity. Severely disabled persons are given preference in the event of equal suitability.

Fraunhofer-Gesellschaft plays a central role in the innovation process, developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.



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