Automated scanning and individual identification system for parts without marking or tagging

Conference Paper (2018)
Author(s)

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)

Research Group
Biomechatronics & Human-Machine Control
DOI related publication
https://doi.org/10.1145/3206025.3206088
More Info
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Publication Year
2018
Language
English
Research Group
Biomechatronics & Human-Machine Control
Pages (from-to)
509-512
ISBN (print)
978-1-4503-5046-4

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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