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A Simulation Study on the Application of Cellular Manufacturing System in the Automated Welding Line Producing Excavator-parts

굴삭기 부품 용접 자동화라인의 셀생산방식 적용을 위한 시뮬레이션 연구

  • 김혜정 (창원대학교 산업시스템공학과) ;
  • 이승우 (창원대학교 산업시스템공학과) ;
  • 문덕희 (창원대학교 산업시스템공학과)
  • Received : 2013.03.04
  • Accepted : 2013.06.18
  • Published : 2013.06.30

Abstract

Mixed model production system means that various products are manufactured alternately in a line, and it has become a popular system in the era of multi-product small-quantity production. However, in the mixed model production system using flow line, the unbalance among stations is not inevitable because the workloads of stations cannot be the same. Thus, flow line system has been replaced to cellular manufacturing system for reducing the loss of waiting due to the unbalance of stations. In this paper, we introduce the simulation case study of an automated welding line which produces the parts of excavator. The factory has considered replacing the mixed model flow line to the cellular manufacturing system based on FMC concept. The increase of production quantity is estimated about 26.7%, and the lead time is reduced more than 55%. Furthermore sensitivity analyses are conducted considering the changes of product-mix.

다품종 소량생산이 보편화 되면서 하나의 생산라인에서 여러 종류의 제품을 교대로 생산하는 혼류생산방식이 보편화 되었다. 하지만 흐름라인 방식의 혼류생산에서는 필연적으로 작업장 간의 공정시간 불균형이 존재한다. 따라서 이러한 공정불균형에 의한 대기의 낭비를 최소화하기 위하여 기존의 흐름생산방식에서 셀생산방식으로 전환하는 시도가 빈번하게 발생한다. 본 논문에서는 굴삭기 부품을 생산하는 혼류흐름라인 방식의 자동화 로봇 용접라인을 FMC 개념의 직선형 셀방식으로 전환하는 과정에서 타당성 검토를 위해 시뮬레이션을 수행한 사례연구 결과를 소개한다. 분석결과 26.7%의 생산량 증가와 55% 이상의 리드타임 감소효과가 예상되었다. 또한 향후 제품 생산비율의 변화에 따른 민감도분석을 수행하였다.

Keywords

References

  1. (Korean)사카마키 히사시 (삼성전자 디지털미디어총괄 제조기술센터 역), 캐논방식의 셀생산시스템, 동양문고, 서울, 2006.
  2. (Korean)황학 외 6인, 설비계획론, 영지문화사, 서울, 2001.
  3. Akturk, M.S., Gultekin, H. and Karasan, O.E., "Robotic Cell Scheduling with Operational Flexibility", Discrete Applied Mathematics, Vol. 145, (2005), pp. 334-348. https://doi.org/10.1016/j.dam.2004.02.012
  4. Drobouchevitch, I.G., Geismar, H.N. and Sriskandarajah, C., "Throughput Optimization in Robot Cells with Input and Output Machine Buffers: A Comparative Study of Two Key Models", European Journal of Operational Research, Vol. 206, (2010), pp. 623-633. https://doi.org/10.1016/j.ejor.2010.03.002
  5. Gultekin, H., Akturk, M.S. and Karasan, O.E., "Scheduling in Three Machine Robotic Flexible Manufacturing Cell", Computers & Operations Research, Vol. 34, (2007), pp. 2463-2477. https://doi.org/10.1016/j.cor.2005.09.015
  6. Lu, M.S. and Wiens, G.J., "Predictive Pull Based Control of Unmanned Manufacturing Cells, Accounting for Robot Mobility", Robotics and Computer Integrated Manufacturing, Vol. 18, (2002), pp. 83-94. https://doi.org/10.1016/S0736-5845(01)00036-9
  7. Moon, D.H., Song, C. and Ha, J.H. "A Dynamic Algorithm for the Control of Automotive Painted Body Storage", Simulation, Vol. 81, (2005), pp.773-787. https://doi.org/10.1177/0037549705062173
  8. Savsar, M. and Aldaihani, M. "Modeling of Machine Failures in a Flexible Manufacturing Cell with Two machines Served by a Robot", Reliability Engineering and System Safety, Vol. 93, (2008), pp. 1551-1562. https://doi.org/10.1016/j.ress.2007.06.002
  9. Shin, K.W., Lee, G.H. and Moon, D.H., "A Simulation Study on the Overhaul Repair Shop of Weapon System", Journal of the Korea Society for Simulation, Vol. 20, No. 3 (2011), pp.119-127. https://doi.org/10.9709/JKSS.2011.20.3.119
  10. Yoon, J.I., Um, I.S. and Lee, H.C., "Proactive Operational Method for the Transfer Robot of FMC", Journal of the Korea Society for Simulation, Vol. 17, No. 4 (2008), pp. 249-257.