Master's Thesis: AI-Based Vision for Automated Quality Inspection
Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Artificial Intelligence · Robotics & Automation
In short
This Master's Thesis focuses on automating quality inspection in a machining line using AI-based vision systems. The project involves mapping suitable cameras, sensors, lighting, and AI methods to detect visual deviations, assessing their effectiveness, and recommending future steps for implementation.
Responsibilities
- Investigate the use of AI-based vision for automated quality inspection.
- Detect quality deviations such as porosity, scratches, impact marks, and unmachined holes.
- Map suitable cameras, sensors, lighting solutions, vision systems, and AI methods.
- Assess the effectiveness of different solutions in detecting various deviations.
- Quantify the performance and detection rate of AI-based vision solutions.
Requirements
- Currently studying Engineering Physics, Electrical Engineering, Computer Science, Mechatronics, Mechanical Engineering, or a related field.
- Interest in computer vision, machine learning, and industrial automation.
- Analytical mindset with the ability to combine technical literature studies with practical testing.
- Ability to work independently and present technical results clearly.
Desired Qualifications
- Experience with image processing or machine learning is an advantage.
Benefits
- Opportunity to shape sustainable transport and infrastructure solutions.
- Work with next-generation technologies and collaborative teams.
- Contribute to a global scale impact.
- Gain experience in manufacturing at Volvo Group.
- Opportunity to join a leading industrial company with iconic brands.
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