[ Special Issue : Engineering Design of ADBL ]

Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 29, No. 3, pp.227-234

ISSN: 2508-5107 (Online)

Print publication date 15 Jun 2020

Received 09 Apr 2020 Revised 09 May 2020 Accepted 13 May 2020

DOI: https://doi.org/10.7735/ksmte.2020.29.3.227

운동화 중창의 작업 자동화를 위한 인라인 3D 스캐너 개발

김성환^a ; 이유나^a ; 송성재^b^{, *}

In-line 3D Scanning System for Automated Manufacturing of Injected Shoe Midsole

Sung Hwan Kim^a ; Yuna Lee^a ; Sung Jae Song^b^{, *}

aDepartment of Mechanical System Design Engineering, Seoul National University of Science and Technology
bDepartment of Mechanical Engineering, Gangneung-Wonju National University

Correspondence to: ^*Tel.: +82-33-760-8743 E-mail address: sjsong@gwnu.ac.kr (Sung Jae Song).

Abstract

A shoe midsole is manufactured by the phylon mold method in which each product is manufactured successively with differing dimensions due to deformation, and it hinders the automation of shoe manufacture with issues such as size inspection or cement spraying. To address this drawback, it is necessary to perform real-time 3D scanning of the inline conveyor. For the footwear industry, a 3D scanner should have the necessary precision, reasonable cost, and processing speed higher than a commercially available 3D scanner. The optical non-contact method with a line laser is adopted for 3D shape measurement. A laser stripe extraction method and a mathematical model for constructing 3D information are proposed. Unique jig shape and a mathematical method for estimating machine parameters are also expressed. The method of extracting meaningful features from the acquired point cloud and treating the abnormal data in toe and heel is discussed.

Keywords:

Shoe midsole, Inline 3D scanning, Laser stripe extraction, Point cloud reconstruction, Feature of point cloud

Acknowledgments

이 논문은 2020년도 정부(산업통상자원부)의 재원으로 한국산업기술진흥원의 지원을 받아 수행된 연구임(P0008473, 2020년 산업혁신인재성장지원사업).

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Sung Hwan Kim

Professor in the department of Mechanical System Design Engineering, Seoul National University of Science and Technology.His research interest is Manufacturing system and machine vision.

E-mail: sunghwan@seoultech.ac.kr

Yuna Lee

Graduate student in the department of Mechanical System Design Engineering, Seoul National University of Science and Technology.Her research interest is machine vision and deep learning

E-mail: lyn2344@seoultech.ac.kr

Sung Jae Song

Professor in the department of Mechanical Engineering, Gangneung- Wonju National University.His research interest is Mechanism design.

E-mail: sjsong@gwnu.ac.kr