Thesis Work - AI-Assisted Machine Connectivity for Brownfield Production

Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future. If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match. Background Manufacturing companies often operate production equipment from different suppliers, generations, and automation platforms. Although machines may contain valuable production data, accessing and using this data can require significant engineering effort because PLC structures, tag names, signal logic, and available documentation differ between machines. For data-driven production, there is therefore a need to translate heterogeneous machine signals into standardized production information, such as machine status, cycle completion, part count, faults, and product information. Today, this mapping is often performed manually and depends heavily on automation expertise and knowledge of the individual machine. AI may offer new opportunities to support this process by analyzing PLC signals, available documentation, and production behavior to identify and propose mappings between raw machine signals and standardized production information. Combined with a software-based PLC, validated mappings could then provide a common interface for higher-level systems such as IIoT platforms, MES, and visualization solutions. Thesis Scope & Deliverables The Thesis Will Investigate How AI Can Support The Identification And Mapping Of Heterogeneous PLC Signals Into Standardized Production Information. Key Activities Include

• Identifying relevant production information and defining a common data model for selected machine use cases.
• Mapping the current process for identifying, interpreting, and integrating PLC signals and identifying major sources of engineering effort.
• Investigating suitable AI approaches for analysing PLC signals, tag information, documentation, and production events.
• Developing a prototype method for proposing mappings between machine-specific signals and standardized production variables.
• Evaluating the approach on selected machines with different PLC structures and levels of documentation.
• Assessing mapping accuracy, required engineering effort, expert involvement, and transferability between different machines.
• Investigating how validated mappings could be implemented through a soft PLC, edge solution, or similar standardized connectivity layer.
• Providing recommendations for how AI-assisted signal mapping could support scalable machine connectivity in future production systems.

Suitable Background

• Automation engineering
• Computer science / artificial intelligence
• Embedded systems or control systems
• Other relevant backgrounds combining automation, software, AI, and manufacturing

The thesis is particularly suitable for students interested in the intersection between industrial automation, artificial intelligence, machine connectivity, and smart production. Thesis Information

• Level: 15 or 30 credits (Bachelor’s or Master’s thesis)
• Language: Swedish or English
• Start date: 18 Januari, 2027
• Location: Volvo CE Eskilstuna or Arvika (on site preferred)
• Number of students: 1-2 students (2 are preferred)

Ready for the next move? Last application day is November 30. In case you have any questions regarding the position, contact

• Per Magnusson per.magnusson@volvo.com
• Joao Pedrassoli joao.jp.pedrassoli@volvo.com

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. Part of Volvo Group, Volvo Construction Equipment is a global company driven by our purpose to build the world we want to live in. Together we develop and deliver solutions for a cleaner, smarter, and more connected world. By unleashing everyone’s full potential, we build a more sustainable future for all our stakeholders. Come join our team and help us build a better tomorrow.