Master Thesis - Developing a Real-Time Digital Shadow for Smart Manufacturing

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What we offer:

At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are.

Group Summary:

Transforming mobility. Making automotive technology that is smarter, cleaner, safer and lighter. That’s what we’re passionate about at Magna Electronics, and we do it by creating world-class Electronic systems. We are a premier supplier for the global automotive industry with full capabilities in design, development, testing and manufacturing of complex Electronic systems. Our name stands for quality, environmental consciousness, and safety. Innovation is what drives us and we drive innovation. Dream big and create the future of mobility at Magna Electronics.

Job Responsibilities

This thesis offers a unique opportunity to work at the intersection of manufacturing, digitalisation, and software development in a real production environment. You will collaborate with experienced engineers and production specialists while developing a solution that can improve operational visibility, support continuous improvement initiatives, and contribute to smarter, data-driven manufacturing.

The project provides hands-on experience with Industry 4.0 concepts, industrial data integration, digital shadow technologies, and user-focused system design within the automotive industry.

The thesis is positioned within manufacturing digitalisation and combines production engineering, IIoT, software development, and operator-centered design.

The camera assembly line generates large amounts of machine and process data, but this information is not yet consolidated into a unified real-time view. As a result, production teams have limited visibility into current operations, making it more difficult to respond proactively, identify priorities, and focus improvement efforts where they create the greatest value.

In this thesis, you will design, implement, and validate a scalable digital shadow that enhances operational transparency and supports more consistent, data-driven decision-making. By connecting data sources, visualising critical production information, and creating actionable insights for operators and engineers, you will contribute directly to the digital transformation of a modern automotive electronics manufacturing environment.

• Engage operators and relevant production stakeholders to identify the information that should be monitored and visualised to create operational value.
• Map relevant data sources and signals for critical camera assembly processes.
• Design and implement functions that capture and monitor selected information, such as unit position, pass/fail or retest status, machine state, and material level.
• Create a digital representation of critical production processes and, if feasible, expand the implementation to the full line.
• Develop an operator-support dashboard that converts detected issues into prioritised events and work items.
• Define clear logic for issue acknowledgement, resolution, and closure.
• Validate the solution with users and document the architecture, data model, implementation, and results.

Expected outcome

• A validated data model and mapping of relevant data sources and signals.
• A working digital shadow prototype that visualises and monitors selected data in real time for critical processes, with possible expansion to line level depending on feasibility.
• An operator-support dashboard where detected issues generate prioritised events and work-list items with clear closure logic.
• A master's thesis report describing the method, technical solution, validation, and recommendations for future development.

Qualifications

You are a curious and motivated student with a strong analytical mindset and an interest in solving complex technical problems. You enjoy taking initiative, working both independently and as part of a team, and communicating your ideas clearly. Most importantly, you are passionate about technology and eager to contribute to innovative solutions for future automotive products.

To be successful in this thesis project, we believe that you:

• Are enrolled in a master's programme in Production Engineering, Industrial Engineering, Automation, Computer Science, Software Engineering, or a related field.
• Have an understanding of production systems. Experience from electronics manufacturing is considered an advantage.
• Have basic object-oriented programming knowledge and an interest in working with TypeScript and Visual Studio Code.
• Have a basic understanding of industrial data exchange technologies. Experience with MQTT is a plus.
• Can collaborate with production stakeholders and translate operational needs into technical requirements.
• Are analytical, structured, and curious, with the ability to combine practical shop-floor activities with software development.

Application and Contact Information

If you have any questions regarding this thesis project, please contact Supervisor Eleonora Boffa, eleonora.boffa@magna.com, or Per Lind, Talent Acquisition Partner, at per.lind@magna.com.

Last application date: 2026-10-15

Please note that applications are reviewed on an ongoing basis, and the position may be filled before the application deadline.

Start: Spring 2027

Scope: 30 ECTS (Master's Thesis)

Number of Students: 1-2

Learn More About Magna

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Awareness, Unity, Empowerment:

At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.

AI-Assisted Screening Disclosure

As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.

Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.

If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.

Group

Magna Electronics