Trelleborg Sealing Solutions Helsingør - Project Bank

Trelleborg is a world leader in engineered polymer solutions for almost every industry on the planet. And we are where we are because our talents brought us here. By specializing in the polymer engineering that makes innovation and application possible, Trelleborg works closely with leading industry brands to accelerate their performance, drive their business forward—and along the way, shape the industry and progress that will benefit humankind in the exciting years ahead. Our people are Shaping Industry from the Inside. Why don´t you join us? 

Location

DNK - Helsingør

Workplace

On-site
Last application date 2026-05-01 Location: DNK - Helsingør


If you're a university student, you can explore the projects available at Trelleborg in this project bank. To apply for a project at Trelleborg, please submit an application that includes:

  • Whether you're applying for an internship, bachelor's project, or master's thesis
  • The project you're interested in
  • Your preferred start date
  • Some information about yourself and why this project has caught your interest

Data & Computer Science

Project Proposals

  • Industrial Data Analytics: Improve, design and implement data pipelines for our data service stack to collect, process, and visualize manufacturing data. Projects may involve predictive analytics, anomaly detection, and the integration of machine learning models for operational insights. Project proposals: Routing data architecture, Routings automation, Data Engineering for Data Service Stack.
  • Process Optimization with AI & Machine Learning: Develop and apply machine learning algorithms to optimize production processes, planning, forecasting and more. Collaborate on data-driven experiments using Python (or R) and SQL. Project proposals: Routing mapping, Capacity Modeling.
  • Computer Vision & Automated Inspection: Apply computer vision techniques for real-time defect detection, object recognition, and production monitoring. Explore open-source platforms and deep learning frameworks for visual analysis. Project proposals: Rod Vision, Vision Touch For Quality.
  • Do you have an idea for another project within this field? We’re always open to fresh perspectives and innovative suggestions. If you have a project proposal you’d like us to consider, feel free to submit it through the application function below.

Who should apply?
We welcome students with a strong interest and academic background in data science, engineering, computer science, mathematics, statistics, and related disciplines. If you are eager to work on interdisciplinary projects and drive technological advancement in manufacturing, we encourage you to apply.


IoT, Embedded and Automation

Project Proposals

  • ESP32-Based Industrial Sensors: Develop and test sensors using ESP32 for real-time monitoring of manufacturing processes. Projects may include wireless data collection, predictive maintenance, and integration with existing data platforms. Project proposals: Wagon RFID monitoring, Time registration Cells.
  • Raspberry Pi Automation Controllers: Design and implement automation solutions using Raspberry Pi for process control, machine interfacing, or visualization. Explore Python scripting, edge computing, and IoT connectivity. Project proposals: Weights Network, Network solutions.
  • Open-Source Machine Vision: Apply open-source vision platforms (such as OpenCV, TensorFlow, etc.) for defect detection, object tracking, and measurement in manufacturing environments. Develop algorithms that enhance production quality and efficiency. Project proposals: Rod Vision, Vision Parts Counting for Maufacturing Traceability, Vision inventory surveillance.
  • Do you have an idea for another project within this field? We’re always open to fresh perspectives and innovative suggestions. If you have a project proposal you’d like us to consider, feel free to submit it through the application function below.

Who should apply?
All students with significant interest and academic value in engineering, computer science, robotics, and related disciplines who are eager to work on interdisciplinary projects and drive technological advancement in manufacturing.


Industrial & Management Engineering

Project Proposals

  • Smart Production Planning & Scheduling: Design and implement innovative planning and scheduling systems to optimize resource utilization, minimize downtime, and enhance throughput. Projects may involve advanced algorithms, capacity modelling and digital tools, and simulation models.
  • Cost Savings & Economic Analysis: Analyze production workflows to identify opportunities for cost reduction, improve process efficiency, and maximize return on investment. Collaborate on developing economic models and savings strategies for manufacturing operations.
  • Lean Management & Process Improvement: Apply lean management principles to streamline production, eliminate waste, and drive continuous improvement. Projects may include value stream mapping, kaizen initiatives, and deployment of best practices.
  • Smart Calculation & Data-Driven Decision Making: Develop tools and methodologies for real-time calculation and analysis of production metrics, supporting informed decision-making and operational optimization.
  • Industrial Project Management: Lead and support projects focused on process upgrades, technology integration, and operational change management. Gain experience in planning, execution, and evaluation of industrial engineering initiatives.
  • Do you have an idea for another project within this field? We’re always open to fresh perspectives and innovative suggestions. If you have a project proposal you’d like us to consider, feel free to submit it through the application function below.

Who should apply?
We welcome students with a strong interest and academic background in production engineering, industrial engineering, management, economics, project management, operations research, and related disciplines. If you are eager to work on interdisciplinary projects and drive technological advancement in manufacturing, we encourage you to apply.


Natural Sciences and Computing

Project Proposals

  • Applied Machine Learning and AI: Develop machine learning models and AI-driven tools to optimize production planning, forecast demand, and analyze manufacturing data. Projects may include algorithm development, data visualization, and integration with existing platforms. Project proposals: Capacity modeling, Routing mapping.
  • Experimental Design: Conduct experiments to characterize materials and improve processing methods. Investigate material properties and their relationship to machine performance and settings and design experiments to explore these interactions. Project proposals: Speed vs. quality vs. tools.
  • Measurement: Computer Vision and 3D Scanning: Apply computer vision techniques for automated measurement, defect detection, and process control in manufacturing environments. Develop algorithms for object identification, tracking, and quality assurance. Vision-based inventory surveillance, Inline product measurement.
  • Do you have an idea for another project within this field? We welcome new perspectives and innovative suggestions. If you have a project proposal you would like us to consider, feel free to submit it through the application function below.

Who should apply?
Students with a strong interest and academic foundation in physics, mathematics, chemistry, computer science, or related disciplines, who are eager to work on interdisciplinary projects and drive scientific and technological advancement in manufacturing.


R&D Internship

Optimization of Process Parameters for Polymer Extrusion
The intern will work within the R&D Test team to gain hands‑on experience with polymer extrusion and process optimization. The main objective of the project is to develop a solid understanding of the laboratory extruder setup and systematically identify the best process parameters for stable, high‑quality material extrusion. The intern will work with material specialists and technicians to support ongoing development activities.

Project objectives:

  • Learn and Understand the Extruder Machine
  • Study the Materials Being Extruded
  •  Set Up and Conduct Extrusion Experiments
  • Evaluate and Analyze the Extrudate
  • Determine the Optimal Process Window
  • Reporting and Presentation
  • Expected Deliverables

Who should apply?
We welcome candidates studying Materials Science, Mechanical Engineering, Chemical Engineering, or a related field. An interest in polymer processing or manufacturing technologies is an advantage, as is the motivation to work hands‑on with equipment and experimental setups.


Why join Trelleborg?
By joining as an intern or project participant, you will immerse yourself in hands-on scientific projects that drive real innovation in manufacturing and research. Gain academic value, enjoy the freedom to explore your own ideas, and build projects with potential for further development. Please note that internships are not paid; our focus is on academic growth, providing a sandbox for students to develop their experience and personal academic and professional preferences.


If you have any questions regarding projects within Data & Computer Science, IoT, Embedded and Automation, Industrial & Management Engineering, and Natural Sciences and Computing please contact Tobias Ottsen, ME Manager, at +45 60 80 97 31.
For questions related to the R&D Internship, please reach out to Sara Krpovic, Team Lead R&D Test & Material Specialist, at +45 31 42 50 68.


We conduct interviews continuously, so please feel free to send your application today.
We look forward to hearing from you.

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