Master thesis AI-Based Anomaly Detection for Production Verification

Help Shape the Future of Smart Manufacturing. Modern production systems generate vast amounts of verification data every day. Hidden within this data are patterns that can reveal quality deviations, process changes, and emerging issues long before they become visible through traditional limit-based evaluations. As manufacturing continues to embrace digitalization and artificial intelligence, there is a growing opportunity to use advanced analytics to improve quality assurance and decision-making. We are looking for a Master's student who wants to explore how AI and anomaly-detection techniques can be applied to production verification and contribute to the development of smarter, data-driven manufacturing processes. Thesis Scope The purpose of this thesis is to investigate how artificial intelligence and anomaly-detection methods can be used to identify unusual patterns in verification data and strengthen decision support in a production environment. The thesis is expected to: Analyze production verification data from a relevant industrial use case. Identify characteristic patterns of normal system behavior. Evaluate and compare different anomaly-detection approaches. Develop methods for visualizing and interpreting detected deviations. Assess detection performance, false rejections, traceability, and practical applicability in a production environment. Deliver a proof of concept or methodology, together with recommendations for future implementation and development. This project offers a unique opportunity to work at the intersection of artificial intelligence, data analytics, quality assurance, and manufacturing while addressing a real industrial challenge. Who We Believe You Are You are currently pursuing a Master's degree in: Data Science Computer Engineering Industrial Engineering Applied Mathematics Or another relevant engineering discipline You have a strong interest in: Data analytics and machine learning Artificial intelligence and anomaly detection Manufacturing systems and industrial applications Problem-solving and analytical thinking Experience within manufacturing or production environments is considered an advantage. What You'll Gain Hands-on experience applying AI and advanced analytics to real manufacturing challenges Exposure to production verification, quality assurance, and digital manufacturing Opportunities to collaborate with experts in manufacturing, data analytics, and engineering Experience developing solutions with direct industrial relevance and business impact Valuable insights into how AI can support the future of smart factories Practical Information Thesis Level: Master's Thesis Number of Students: 1 Location: Volvo GroupLanguage: English (mandatory), Swedish is a plus Semester: Spring 2026 Application Deadline: November 30, 2026 We value your data privacy and therefore do not accept applications via mail. Who we are and what we believe in We are committed to shaping the future landscape of efficient, safe, and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents across the group’s leading brands and entities. Applying to this job offers you the opportunity to join Volvo Group. Every day, you will be working with some of the sharpest and most creative brains in our field to be able to leave our society in better shape for the next generation. ​We are passionate about what we do, and we thrive on teamwork. ​We are almost 100,000 people united around the world by a culture of care, inclusiveness, and empowerment. Trucks Technology & Industrial Division hire team players who are ready to create real customer impact. Our decentralized teams work close to our customers, with speed and autonomy, to build what they truly need. Join us to collaborate on innovative, sustainable technologies that redefine how we design, build, and deliver value. Bring your curiosity, your expertise, and your collaborative energy, and together, we’ll turn bold ideas into tangible solutions for our customers and contribute to a more sustainable tomorrow.