Automated scanning and individual identification system for parts without marking or tagging
Kengo Makino (NEC Corporation)
Wen Jie Duan (Student TU Delft)
Rui Ishiyama (NEC Corporation)
Toru Takahashi (NEC Corporation)
Yuta Kudo (NEC Corporation)
Pieter Jonker (TU Delft - Biomechatronics & Human-Machine Control)
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Abstract
This paper presents a fully automated system for detecting, classifying, microscopic imaging, and individually identifying multiple parts without ID-marking or tagging. The system is beneficial for product assemblers, who handle multiple types of parts simultaneously. They can ensure traceability quite easily by only placing the parts freely on the system platform. The system captures microscopic images of parts as their "fingerprints," which are matched with pre-registered images in a database to identify an individual part's information such as its serial number. We demonstrate a working prototype and interaction scenario.
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