Master Thesis: Computer Vision for Recognition of Manual Assembly Activities

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Background

Manufacturing environments increasingly rely on detailed production data to understand process status,

quality, and production progress. Existing production and automation systems can often capture

information directly from machines, PLCs, and other technical equipment. Manually performed assembly

activities, however, are generally more difficult to automatically observe and register.

Computer Vision and machine learning methods provide an opportunity to analyze image or video data

from an assembly station and identify objects, activities, and process states. Such a solution could

potentially complement existing production and automation systems by automatically identifying when

specific manual assembly activities have been completed.

Purpose

The purpose of the thesis is to investigate how a Computer Vision-based solution can be designed to

identify completed work activities at a manual assembly station.

The study should be limited to one selected workstation and a defined number of assembly activities

related to the assembly of engine components.

The Thesis Should Consist Of Two Main Parts

Design and evaluate a concept for using image or video data to identify one or more defined assembly activities.Evaluate and compare relevant Computer Vision and neural-network-based methods for understanding and performing this analysis.

The evaluation should not only consider theoretical model accuracy, but also the suitability of the

approaches for a real industrial environment.

Relevant Evaluation Criteria May Include

Detection or classificationRobustnessRequired amount of training dataInference time and computational requirementsCamera positioning and viewing angleLighting conditionsOcclusion of objects or componentsPotential integration with existing production and automation systems

A Possible Overarching Research Question Is

How can Computer Vision be used to automatically identify completed manual assembly activities, and

which technical approaches are most suitable for this task in an industrial production environment?

Data Collection

Data collection should be limited to a selected assembly station and a defined set of assembly activities.

The data collection will occur at Volvo Penta’s Vara Factory.

The Work May Include

Collection of image and/or video data from the selected workstationDefinition of the assembly activities that should be identifiedAnnotation of relevant objects, activities, or process statesCreation of training, validation, and test datasetsObservation of variations in how the activities are performed

Based on the characteristics of the selected activities, the student may evaluate methods such as:

Object detectionObject trackingPose estimationAction recognitionTemporal video analysisCombinations of several Computer Vision methods

The thesis should focus on selecting and motivating suitable technical approaches and empirically

evaluating their performance for the selected industrial use case, rather than being limited from the

beginning to a specific neural network architecture.

The final outcome should consist of both a technical evaluation and a recommendation for how a

Computer Vision component could complement existing production and automation systems.

Relevant Academic Fields

Suitable for students in Computer Science, Artificial Intelligence, Machine Learning, Data Science,

Automation, Robotics, Mechatronics, Electrical Engineering, or related fields.

Recommended Level

Suitable for Master’s thesis work.

Ready for the next move?

Contact: Leif Funke, Manager Digitalization & IT, leif.funke.2@volvo.com

Last application date: October 31

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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.

Volvo Penta, a world-leading supplier of engines and complete drive systems for marine and industrial applications, you will be part of a global and diverse team of highly skilled professionals who works with passion, trust each other and embraces change to stay ahead. We make our customers win.