FOMs 패키지 내 FOM 시스템을 활용한 제조현장 빅데이터 기반의 생산성 분석 방법에 관한 연구
Abstract
The key to transforming the manufacturing industry is the appropriate application of information technology and the utilization of data. Therefore, a method for efficient factory operation management, as well as IT system introduction, is important. From this, it is possible to create data-driven value and strengthen the competitiveness of enterprises. In this paper, we propose a FOMs (smart-Factory Operation Managements) Package method based on 4M data of manufacturing sites to improve productivity and competitiveness. In addition, we performed a case study by applying part of the FOMs Package to the manufacturer. We performed a detailed and multi-dimensional analysis of the MES/POP data that the manufacturer managed, and were able to derive not only the products that needed improvement but also related facilities, workers, downtimes, and defects. As a result, we found that the proposed method was effective in analyzing 4M manufacturing data and making decisions for factory operation management.
Keywords:
FOMs package, FOM system, Productivity analysis, Manufacturing big data, Convergence technology, Smart manufacturingAcknowledgments
이 연구는 중소벤처기업부 ‘중소기업연구인력지원사업’의 재원으로 한국산학엽협회(AURI)의 지원을 받아 수행된 연구임(2021년 기업연계형연구개발인력양성사업, 과제번호 : S3039971).
References
- Tao, F., Qi, Q., Liu, A., Kusiak, A., 2018, Data-driven Smart Manufacturing, J. Manuf. Syst., 48 157-169. [https://doi.org/10.1016/j.jmsy.2018.01.006]
- Mourtzis, D., Vlachou, E., Milas, N., 2016, Industrial Big Data as a Result of IoT Adoption in Manufacturing, Procedia CIRP, 55 290-295. [https://doi.org/10.1016/j.procir.2016.07.038]
- Koren, Y., Gu, X., Guo, W., 2017, Reconfigurable Manufacturing Systems: Principles, Design, and Future Trends, Front. Mech. Eng., 13:2 121-136. [https://doi.org/10.1007/s11465-018-0483-0]
- Liang, S., Rajora, M., Liu, X., Yue, C., Zou, P., Wang, L., 2018, Intelligent Manufacturing Systems: A Review, Int. J. Mech. Eng. Robot. Res., 7:3 324-330. [https://doi.org/10.18178/ijmerr.7.3.324-330]
- Wang, B., Tao, F., Fang, X., Liu, C., Liu, Y., Freiheit, T., 2021, Smart Manufacturing and Intelligent Manufacturing: A Comparative Review, Engineering, 7:6 738-757. [https://doi.org/10.1016/j.eng.2020.07.017]
- Mittal, S., Khan, M. A., Romero, D., Wuest, T., 2018, A Critical Review of Smart Manufacturing & Industry 4.0 Maturity Models: Implications for Small and Medium-sized Enterprises (SMEs), J. Manuf. Syst., 49 194-214. [https://doi.org/10.1016/j.jmsy.2018.10.005]
- Lee, S. H., Roh, K. H., Kim, S. Y., Kim, J. H., 2020, Site Control of Smart Manufacturing, Mijeon Science Publishing Co., Republic of Korea.
- Kim, S. Y., Kim, W. H., Jung, I. H., 2014, A Case Study on the Automobile Company’s Productivity Improvements by Applying Digital Factory Technology, Productive Review, 28:3 35-52. [https://doi.org/10.15843/kpapr.28.3.201409.35]
- Kim, S. Y., 2015, Study of Digital Factory FOM Solution on Software-based : Applied Case to Heat-Treatment Company, Proc. Korean Management Sci. Assoc. 2015 Spring Joint Conf., 2855.
- Kim, S. Y., 2018, A Case Study of the Introduction of Smart Factory Operation Management (FOM) in the Fourth Industrial Revolution Era, J. Korean Assoc. Comput. Acct., 16:1 43-62. [https://doi.org/10.32956/kaoca.2018.16.1.43]
- Groger, C., Niedermann, F., Mitschang, B., 2012, Data Mining-Driven Manufacturing Process Optimization, Proc. World Cong. Eng. 2012 Vol Ⅲ, 4.
- Noh, K. -S., Park, S., 2014, An Exploratory Study on Application Plan of Big Data to Manufacturing Execution System, J. Digit. Converg., 12:1 305-311. [https://doi.org/10.14400/JDPM.2014.12.1.305]
Senior researcher in research institute affiliated with Digital Factory Co., Ltd.
His research interest is smart manufacturing and industrial AI.
E-mail: kiate93@naver.com
Professor in the Department of smart factory for materials-parts-equipment, Hoseo University.
His research interest is smart factory and applications of FOMs (smart-Factory Operation Managements) system.
E-mail: df2030@hoseo.edu