Unveiling Hidden Anomalies

A Hybrid Approach for Surface Mounted Electronics

Conference paper (2024)

Authors

Amir Ghezeljehmeidan Electronic Components, Technology and Materials - EEMCS
Williem Driel Electronic Components, Technology and Materials - EEMCS
Justin Dauwels Signal Processing Systems - EEMCS
Research Group
Electronic Components, Technology and Materials (EEMCS) (TU Delft)
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Published Date

2024

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Electronic Components, Technology and Materials

Abstract

Industrial assembly lines are the heartbeat of modern manufacturing, where precision and efficiency are paramount. This paper introduces a novel hybrid Explainable artificial intelligence (XAI) approach to enhance monitoring and analysis in industrial assembly. By fusing the power of vision anomaly detection models with the clarity of the gradient tree boosting algorithm, this framework not only boosts defect detection accuracy but also provides transparent, actionable insights. This synergy transforms how operators and engineers interact with AI, fostering trust and enhancing operational excellence.

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File under embargo until 16-06-2025