Mass-produced parts traceability system based on automated scanning of “Fingerprint of Things”

Abstract

This paper presents a prototype of parts traceability system which employs the “Fingerprint of Things”-based individual identification technique. Traceability of mass-produced tiny parts such as bolts and nuts are required to ensure quality and safety of big machines. However conventional systems using ID tags or serial marking are not applicable because of quantity and tiny size. To overcome this problem, we propose a tag-less traceability system which uses their appearance images as “fingerprints” to identify each of them. Our traceability system consists of three components; (i) automated fingerprints scanning machine for enrollment, (ii) mobile device for query and (iii) cloud server for identification from database. The key to success of our traceability system is enabling us to capture repeatable image features from the same parts in both of (i) enrollment and (ii) query. To this end, we designed the two lighting mechanisms; one for fast scanning of numerous bolts by automatic feeding, and another for a mobile device to capture one parts by hand. In our experiments, we achieve that 1,000 metal bolts produced with the same mold are perfectly identified by matching their surface images captured with our automatic scanning machine and a smart phone.