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Study program: Smart Engineering
Lecture: European Project Semester
Lecturer(s): Bernard Girsule
Team leader: Daan Bok
Team members:

Meike van den Heuvel (se250001)
Erik van der Kaag (se250002)
Sven van Rijkom (se250003)
Jan Milczarek (se250004)
Julia Syzd (se250005)
Daan Bok (se250006)

Short description: Anomaly Detection & Splice Quality Monitoring using Machine Learning

Project description:

In the packaging industry, continuous production relies on the processing of material webs, where automatic splicing operations are used to join and synchronize these webs without interrupting the process. However, splicing can occasionally fail, leading to production stops, quality issues, and measurable financial losses. In addition, thermal systems such as dryers or heating units rely on multiple fan motors whose condition often cannot be monitored directly. As a result, motor failures or maintenance needs are frequently detected only after a malfunction occurs, causing unplanned downtime and reduced process stability. To address these challenges, the project group will develop two complementary solutions: * Data-driven condition monitoring of electrical drives using data analysis and machine learning (ML) to detect faults, anomalies, and wear at an early stage. * Camera-based splice quality inspection using computer vision to automatically identify defective splices.