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Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 32 , No. 3

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[ Special Issue : SW-based smart-Factory Operation Managements(FOMs) Technology ]
Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 32, No. 3, pp. 169-176
Abbreviation: J. Korean Soc. Manuf. Technol. Eng.
ISSN: 2508-5107 (Online)
Print publication date 15 Jun 2023
Received 08 Apr 2023 Revised 15 May 2023 Accepted 18 May 2023
DOI: https://doi.org/10.7735/ksmte.2023.32.3.169
FOM-Tool Monitoring 활용 절삭공구 최적 교체 주기 설정으로 손실비용 저감
장재훈^a ; 장선준^b ; 김수영^a^{, *}


Reducing the Loss Cost by Setting the Optimal Replacement Cycle for Cutting Tools using FOM-Tool Monitoring
Jae Hoon Jang^a ; Seon Jun Jang^b ; Su Young Kim^a^{, *}
aDepartment of AI Smart Factory Convergence Engineering, Hoseo University
bDepartment of Mechanical and Automotive Engineering, Hoseo University
Correspondence to : ^*Tel.: +82-70-8600-5336 E-mail address: df2030@hoseo.edu (Su Young Kim).



Funding Information ▼ Ministry of SMEs and Startups Korea Association of University, Research Institute and Industry RS-2023-00259258

Abstract

In precision machining, the condition of cutting tools deteriorates the product quality, defect rate, and productivity. Most small- and medium-size enterprises set the cutting tool replacement cycle through experience; however, this significantly differs from the actual number of tool replacements. To solve this problem, in this study, based on tool replacement data, FOM-Tool Monitoring, a smart factory operation management system, was used to perform 4M multi-dimensional analysis to analyze Min-Max and deviation in the number of times of tool use. The tool load waveform trend was also analyzed to verify the suitability of replacement, optimal replacement cycle, and conduct verification.


Keywords: FOM(smart-factory operation management), Data file set, QPR(quick plan result), Tool monitoring, Daq(data acqusition)

Acknowledgments

이 연구는 중소벤처기업부 ‘중소기업연구인력지원사업’의 재원으로 한국산학연협회(AURI)의 지원을 받아 수행된 연구임. (2023년 기업연계형연구개발인력양성사업, 과제번호: RS-2023-00259258).

References


1.	Kim, Y. T., Kang, Y. S., Kim, H.-J., Seo, Y. H., Kim, B. H., 2019, Implementation of Wireless Condition Monitoring System in a Cutting Tool Using Accelerometer, J. Korean Soc. Manuf. Technol. Eng., 28:3 198-202.
2.	Song, K. H., Lee, D, Y., 2015, The State of the Art in Monitoring Technology of Machining Operations, J. Korean Soc. Precis. Eng., 35:3 293-304.
3.	Kim, S. Y., Kim, S. G., Yang, G. D., Park, K. H., Lee, S. W., Lee, D. Y., 2016, Characteristics of Machining Monitoring Signals in Accordance to Tool Wear Progression, Proc. Korean Soc. Mech. Eng. Fall Conf., 2634-2637.
4.	Jang, J. H., Park, Y. R., Kim, J. H., Bae, B. S., Kim, S. Y., 2021, Manufacturing Data Gathering Methods and 4M Data Analysis to Improve Process-productivity of Auto-parts using FOM Solution, Proc. Korean Soc. Manuf. Technol. Eng. Autumn Conf., 129.
5.	Kim, S. Y., 2018, A Case Study of the Introduction of Smart Factory Operation Management(FOM) in the fourth Industrial Revolution Era, Korean Association of Computers and Accounting, 16:1, 43-62.
6.	Jang, J. H., Jeoung, Y. Y., Kong, Y. G., Jo, M. S., Lim, H. Y., Bae, B. S., Kim, S. Y ., 2021, Correlation Analysis and Problem Solving between 4M and Productivity using FOM solution, Proc. Korean Soc. Manuf. Technol. Eng. Spring Conf., 61.
7.	Kim, J. H., Kim, S. Y., 2021, Productivity Analysis Method based on Manufacturing Big-data using the FOM System in the FOMs Package, J. Korean Soc. Manuf. Technol. Eng., 30:4 259-268.

Jae Hoon Jang

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: fomsre@naver.com

Seon Jun Jang

Associate Professor in Division of Mechanical and Automotive Engineering, Hoseo University. His research interest is Vibrational Energy Harvesters and Wave Energy Converters.

E-mail: mweagle@hoseo.edu

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