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한국생산제조학회 학술지 영문 홈페이지
[ Special Issue : Smart Manufacturing Innovation based on FOMs ]
Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 31, No. 4, pp.279-287
ISSN: 2508-5107 (Online)
Print publication date 15 Aug 2022
Received 17 May 2022 Revised 01 Aug 2022 Accepted 02 Aug 2022
DOI: https://doi.org/10.7735/ksmte.2022.31.4.279

FOM 데이터 파일 세트의 공정별 단가 데이터와 장비 절삭 공구 수명 간의 상관관계 분석을 통한 제조원가 절감 알고리즘에 대한 연구

김용홍a ; 양해성a ; 김성수b ; 배병성a ; 김수영a, *
Manufacturing Cost-reduction Algorithm Through Correlation analysis Between Process-specific Unit Cost Data of FOM Data File Set and Machine-cutting Tool Life
Yong-hong Kima ; Hae-sung Yanga ; Seong-soo Kimb ; Byung Seong Baeaa ; Su Young Kima, *
aDepartment of AI Smart Factory Convergence Engineering, Hoseo University
bDepartment of Mechanical Convergency Engineering, Silla University

Correspondence to: *Tel.: +82-41-540-5114 E-mail address: df2030@hoseo.edu (Su Young Kim).

Abstract

It have been composed only introducing automatic equipment without analyzing manufacturing process in many smart factories; hence, productivity does not improve significantly. In this study, production data obtained from a computerized NC machining center were analyzed based on the operation and tool costs for each process to reduce the tool management cost of the cutting process for the die manufacturing, which is weak in cost analysis. Tool cost of the minimum cost required for each process was then modeled using linear programming. We derived a modeling logic that could manage the life of the medium cutting process using the programming method and achieved a cost reduction of up to 12% compared to the operation cost by linking tool cost to the manufacturing per process cost. The proposed algorithm can be applied to field equipment as a manual cost item one of the items of the FOM which manufacturing optimization system.

Keywords:

FOM(smart-factory operation management), Analysis, Milling cutting, Tool life, Cost optimization

Acknowledgments

이 연구는 중소벤처기업부 ‘중소기업연구인력지원사업’의 재원으로 한국산학연협회(AURI)의 지원을 받아 수행된 연구임(2022년 기업연계형연구개발인력양성사업, 과제번호: S3282285).

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Yong-hong Kim

Ph.D. candidate in Department of AI Smart Factory Convergence Engineering,, Hoseo University. His research interest is FOM (smart-Factory Operation Management) with AI.

E-mail: kyonghong777@daum.net

Hae-sung Yang

Graduate student in Department of AI Smart Factory Convergence Engineering,, Hoseo University. His research interest is FOM (smart-Factory Operation Management) with AI.

E-mail: hsyang@silla.ac.kr

Seong-soo Kim

Professor in Department of Mechanical Convergence Engineering, Silla University. His research interest is FOM with AI.

E-mail: sskim@silla.ac.kr

Byung Seong Bae

Professor in Department of Smart Factory for Materials-Parts-Equipment, Hoseo University. His research interest is FOM (smart-Factory Operation Management) in Display and Semiconductor Field.

E-mail: bsbae3@hoseo.edu

Su Young Kim

Professor in Department of Smart Factory for Materials-Parts-Equipment, Hoseo University. His research interest is applications of FOMs (smart-Factory Operation Managements).

E-mail: df2030@hoseo.edu