Abstract
In this paper we present a comparative study of two approaches for the detection of foreign objects in an industrial assembly line setting and proposes a complete solution from the findings. The methodology is vision based and can be used for processing 3D objects conveyed at a constant velocity. Out of the two methods, the CNN based approach is recommended to the company sponsoring this research. The design of the system is accomplished using a fixed camera, a display unit, a conveyor belt and further a raspberry pi or equivalent hardware to run the solution. The novelty of this solution is the possible full automation of the assembly line with low latency and high performance and with a small training dataset.
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Acknowledgements
We would like to express our special thanks to our guide Prof. Pushkar Joglekar and to our company mentor Mr. Hrishikesh Hirde who helped us in every possible way and resolved the problems we faced. Additionally, we would like to thank VIT, Pune for providing us with the opportunity to tackle such industry problems.
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Vasave, S., Shah, A., More, P., Joglekar, P., Hirde, H. (2023). Foreign Object Detection on an Assembly Line. In: Goswami, S., Barara, I.S., Goje, A., Mohan, C., Bruckstein, A.M. (eds) Data Management, Analytics and Innovation. ICDMAI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 137. Springer, Singapore. https://doi.org/10.1007/978-981-19-2600-6_29
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DOI: https://doi.org/10.1007/978-981-19-2600-6_29
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