한국생산제조학회 학술지 영문 홈페이지
[ Papers ]
Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 32, No. 1, pp.8-16
ISSN: 2508-5107 (Online)
Print publication date 15 Feb 2023
Received 25 Jan 2023 Revised 08 Feb 2023 Accepted 09 Feb 2023
DOI: https://doi.org/10.7735/ksmte.2023.32.1.8

공정 로스 구조에 의한 가동률지표 모형 연구와 FOM솔루션 데이터 분석 방법

노규환a ; 김수영a, *
Study on an Operating Rate Metrics Model Based on Process Loss Structures and a FOM-solution-based Data Analysis Method
Kyu Hwan Roha ; Su Young Kima, *
aDepartment of AI Smart Factory Convergence Engineering, Hoseo University

Correspondence to: *Tel.: +82-70-8600-5336 E-mail address: df2030@hoseo.edu (Su Young Kim).

Abstract

The aim of this study is to present a new and improved metrics model for measuring the operating rate data based on the loss structure during the manufacturing process and a study on the data analysis methodology. First, the loss structure is classified, analyzed, and presented. Subsequently, the overall equipment effectiveness (OEE) metrics based on the total productive maintenance (TPM) losses are presented and the applicability problem is analyzed. The total production effectiveness (TPE) metrics, which includes both the equipment efficiency and 4M efficiency factors in the calculation of its operating rate new model, is then presented to minimize the problems of OEE. And the man-hour effectiveness (MHE) metrics is presented for measuring the man-hour during manual work with structured man-hour losses. Finally, factory operation management (FOM), which is a solution based on 4M multi-dimension analysis methodology, is applied for the analysis of the operating rate data.

Keywords:

Loss, Operating rate, OEE(overall equipment effectiveness), Man-hour, FOM(factory operation management)

Acknowledgments

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

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Kyu Hwan Roh

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: ghroh@naver.com

Su Young Kim

Professor in Department of AI Smart Factory Convergence Engineering, Hoseo University. His research interest is Applications of FOMs (smart-Factory Operation Managements).

E-mail: df2030@hoseo.edu