DOI QR코드

DOI QR Code

Discrete Event Simulation based Equipment Combination Optimization Method - based on construction equipment performance estimation of the Construction Standard Production Rate -

이산형 이벤트 시뮬레이션 기반 최적의 건설장비 조합 도출 방법 제시 - 표준품셈 건설기계 시공능력 산식을 기반으로 -

  • Ko, Yongho (Department of Architectural Engineering, Inha University) ;
  • Ngov, Kheang (Department of Architectural Engineering, Inha University) ;
  • Noh, Jaeyun (Department of Architectural Engineering, Inha University) ;
  • Kim, Yujin (Department of Architectural Engineering, Inha University) ;
  • Han, Seungwoo (Department of Architectural Engineering, Inha University)
  • 고용호 (인하대학교 건축공학과) ;
  • 키앙 (인하대학교 건축공학과) ;
  • 노재윤 (인하대학교 건축공학과) ;
  • 김유진 (인하대학교 건축공학과) ;
  • 한승우 (인하대학교 건축공학과)
  • Received : 2022.09.15
  • Accepted : 2022.10.11
  • Published : 2022.11.30

Abstract

Productivity estimation of construction operations is crucial to successful project delivery. Especially in the preconstruction phase, the adequacy and effectiveness of plans directly affect the actual performance of operations. Currently, productivity estimation is conducted by referring to existing references such as the Construction Standard Production Rate. However, it is difficult to promptly apply changing conditions of operations when using such references. Moreover, it is difficult to deduce the optimal combination of construction machinery for the given condition. This paper presents a simple simulation model that can be used to generate productivity data that considers site conditions and construction equipment combination. The suggested method is expected to be used as a decision making assisting tool for practitioners who rely on estimations using the Construction Standard Production Rate when establishing construction plans using heavy machinery such as backhoes, loaders and dumptrucks.

건설 프로젝트의 성공적인 수행을 위해 공정 생산성 예측이 필수적으로 요구된다. 특히, 시공 단계 이전에 수행되는 계획의 정확도 및 실효성은 시공 단계의 성과에 큰 영향을 미친다. 기존의 생산성 예측은 표준품셈과 같은 기존 문헌 참고를 통해 수행된다. 그러나 이러한 방법은 변화하는 조건을 즉각적으로 반영하는 것과 공사 수행에 필요한 최적의 장비 조합을 도출하는 것이 어렵다. 본 연구에서는 이산 이벤트 시뮬레이션 기술을 이용하여 장비 조합에 따른 생산성 데이터베이스 구축 방법을 제시하였다. 제시된 방법을 통해 표준품셈 기반 공정 계획 수립을 하는 관리자에게 굴삭기, 로더, 덤프트럭 등으로 수행되는 작업에 대한 최적 시공 계획 수립을 할 수 있을 것이라 예상된다.

Keywords

Acknowledgement

본 논문은 한국연구재단의 지원(과제번호 2021R1A2C1007467)과 국토교통부/국토교통과학기술진흥원이 시행, 한국도로공사가 총괄하는 "스마트건설기술개발 국가R&D사업(과제번호 21SMIP-A158708-02)"의 지원으로 수행된 연구임을 밝히며 이에 감사를 드립니다.

References

  1. AbouRizk, S. (2010). "Role of simulation in construction engineering and management." Journal of construction engineering and management, 136(10), pp. 1140-1153. https://doi.org/10.1061/(ASCE)CO.1943-7862.000022
  2. Halpin, D.W., and Riggs, L.S. (1992). "Planning and analysis of construction operations." John Wiley & Sons.
  3. Han, S.W., Lee, T.H., and Ko, Y.H. (2014). "Implementation of construction performance database prototype for curtain wall operation in high-rise building construction." Journal of Asian Architecture and Building Engineering, 13(1), pp. 149-156. https://doi.org/10.3130/jaabe.13.149
  4. Han, S.W., Lee, S.Y., Hong, T.H., and Chang, H. (2006). "Simulation analysis of productivity variation by global positioning system (GPS) implementation in earthmoving operations." Canadian Journal of Civil Engineering, 33(9), pp. 1105-1114. https://doi.org/10.1139/l05-124
  5. Kim, H.M. (2012). "Fuzzy technique-based productivity estimation by means of construction delay factor analysis on curtain wall operations in high-rise building constructions." MS thesis, Inha University, Incheon, South Korea.
  6. Kim, S.C., Kong, M.J., Choi, J.W., Han, S.W., Baek, H.Y., and Hong, T.H. (2021). "Feasibility analysis of COVID-19 response guidelines at construction sites in south korea using CYCLONE in terms of cost and time." Journal of Management in Engineering, 37(5), p. 04021048.
  7. Korea Price Information. (2022). https://www.kpi.or.kr (accessed on 14. Sep. 2022).
  8. Labban, R., AbouRizk, S., Haddad, Z., and Elsersy, A. (2013). "A discrete event simulation model of asphalt paving operations." 2013 Winter Simulations Conference (WSC), pp. 3215-3224.
  9. Lee, J.H. (2010). "Construction performance evaluation of an advanced-technology based on construction simulation technique: Focused on steel staircase." MS thesis, Inha University, Incheon, South Korea.
  10. Lee, D.E., Kim, Y.W., and Son, C.B. (2013). "Estimating Productivity of Al-Form operation using WebCYCLONE system." Korean Journal of Construction Engineering and Management, KICEM, 14(3), pp. 115-122. https://doi.org/10.6106/kJCEM.2013.14.3.115
  11. Lu, M. (2003). "Simplified discrete-event simulation approach for construction simulation." Journal of Construction Engineering and Management, 129(5), pp. 537-546. https://doi.org/10.1061/(ASCE)0733-9364(2003)129:5(537)
  12. Ministry of Land, Infrastructure and Transport. (2021). Construction Standard Production Rate.
  13. Mohamed, Y., and AbouRizk, S.M. (2005). "Framework for building intelligent simulation models of construction operations." Journal of computing in civil engineering, 19(3), pp. 277-291. https://doi.org/10.1061/(ASCE)0887-3801(2005)19:3(277)
  14. Martinez, J.C. (2010). "Methodology for conducting discrete-event simulation studies in construction engineering and management." Journal of Construction Engineering and Management, 136(1), pp. 3-16. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000087
  15. Oh, J.H., Song, T.S., and An, B.Y. (2020). "A Study on the Estimation of Proper Construction Cost for Road Pavement Maintenance Work." Korean Journal of Construction Engineering and Management, KICEM, 21(6), pp. 16-26. https://doi.org/10.6106/KJCEM.2020.21.6.016
  16. Shin, Y., Cho, H., and Kang, K.I. (2011). "Simulation model incorporating genetic algorithms for optimal temporary hoist planning in high-rise building construction." Automation in construction, 20(5), pp. 550-558. https://doi.org/10.1016/j.autcon.2010.11.021
  17. Smith, S.D. (1999). "Earthmoving productivity estimation using linear regression techniques." Journal of construction engineering and management, 125(3), pp. 133-141. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:3(133)
  18. Watkins, M., Mukherjee, A., Onder, N., and Mattila, K. (2009). "Using agent-based modeling to study construction labor productivity as an emergent property of individual and crew interactions." Journal of construction engineering and management, 135(7), pp. 657-667. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000022
  19. Widia, A. (2022). WebCYCLONE Users manual, available in: https://www.academia.edu/34614245/WebCYCLONE_Users_Manual
  20. Zankoul, E., Khoury, H., and Awwad, R., (2015). "Evaluation of agent-based and discrete-event simulation for modeling construction earthmoving operations." ISARC. Proceedings of the international symposium on automation and robotics in construction 2015, 32, pp. 1-9.
  21. Zayed, T.M., and Halpin, D.W. (2000). "Simulation as a tool for resource management." 2000 Winter Simulation Conference Proceedings, 2, pp. 1897-1906.