BIM-Based Approach for Automatic Pipe Systems Installation Coordination and Schedule Optimization
Publication: Journal of Construction Engineering and Management
Volume 147, Issue 11
Abstract
Detailed planning, sequencing, and scheduling for the installation of multiple pipe systems are greatly needed to efficiently complete a piping project with both reduced cost and duration. Conventional manual scheduling tools cannot produce optimized and robust installation schedules due to insufficient planning of the installation sequence in generating an appropriate installation schedule. This paper proposes a new approach for automating pipe installation sequence and schedule optimization using 4D building information modeling (BIM). BIM technology is used to automatically capture valuable information from 3D models to assist time-based 4D modeling. Matching rules based on the category of pipe system components are developed to automate the pairing and integration between the 3D BIM models and installation activities. Constraint analysis by sequential rules is formulated and developed to generate favorable sequence and coordination between pipe systems, and conventional simulated annealing (SA) is adapted to optimize the generated practical schedules for installation based on a formulated objective function. An illustrative example is presented to validate the developed approach, and the result shows that the proposed approach can generate a constraint-free installation sequence and an optimal schedule. Compared with conventional methods, the developed approach results in 96%–97% saving in time and enhances accuracy of generating an installation schedule.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data generated or analyzed during the study are included in the published paper.
References
Abedi, M., R. Chiong, N. Noman, and R. Zhang. 2020. “A multi-population, multi-objective memetic algorithm for energy-efficient job-shop scheduling with deteriorating machines.” Expert Syst. Appl. 157 (Nov): 113348. https://doi.org/10.1016/j.eswa.2020.113348.
Amirabdollahian, M., and B. Datta. 2017. “Application of simulated annealing and adaptive simulated annealing in search for efficient optimal solutions of a groundwater contamination related problem.” Comput. Optim. Eng. Paradigms Appl. 2017 (Apr): 26. https://doi.org/10.5772/66998.
Autodesk. 2018. “Dynamo.” Accessed June 18, 2020. http://dynamobim.org/.
Badgujar, S., N. Shah, A. Forgeas, N. Navion-Maillot, E. Monneret, D. Grillot, L. Benkheira, and B. Sarkar. 2016. “Assembly installation studies for the ITER cryoline system, IOP conference series: Materials science and engineering.” In Proc., 26th Int. Cryogenic Engineering Conf. & Int. Cryogenic Materials Conf., 171. Bristol, UK: IOP Conference Series: Materials Science and Engineering.
Bosché, F., M. Ahmed, Y. Turkan, C. T. Haas, and R. Haas. 2015. “The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components.” Autom. Constr. 49 (Jan): 201–213. https://doi.org/10.1016/j.autcon.2014.05.014.
Bosché, F., Y. Turkan, C. T. Haas, T. Chiamone, G. Vassena, and A. Ciribini. 2013. “Tracking MEP installation works.” In Proc., 30th Int. Symp. on Automation and Robotics in Construction and Mining and 23rd World Mining Congress, 229–239. New York: Curran Associates.
Chai, S., Y. Li, C. Wu, and J. Wang. 2013. “A comparison of genetic algorithm, particle swarm optimization and simulated annealing.” Adv. Mater. Res. 679 (13): 77–81. https://doi.org/10.4028/www.scientific.net/AMR.679.77.
Chen, J., R. Hu, X. Guo, and F. Wu. 2020. “Building information modeling-based secondary development system for 3D modeling of underground pipelines.” Comput. Model. Eng. Sci. 123 (2): 647–660. https://doi.org/10.32604/cmes.2020.09180.
Christodoulou, S. 2005. “Ant colony optimization in construction scheduling.” Int. Conf. Comput. Civ. Eng. 2005 (1): 1–11. https://doi.org/10.1061/40794(179)167.
Chua, D. K. H., and K. W. Yeoh. 2011. “PDM++: Planning framework from a construction requirements perspective.” J. Constr. Eng. Manage. 137 (4): 266–274. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000292.
Czerniawski, T., M. Nahangi, C. Haas, and S. Walbridge. 2016. “Pipe spool recognition in cluttered point clouds using a curvature-based shape descriptor.” Autom. Constr. 71 (Nov): 346–358. https://doi.org/10.1016/j.autcon.2016.08.011.
Dawood, N., and E. Sriprasert. 2006. “Construction scheduling using multi-constraint and genetic algorithms approach.” Constr. Manage. Econ. 24 (1): 19–30. https://doi.org/10.1080/01446190500310486.
Diao, P.-H., and N.-J. Shih. 2019. “BIM-based AR maintenance system (BARMS) as an intelligent instruction platform for complex plumbing facilities.” Appl. Sci. 9 (8): 1592. https://doi.org/10.3390/app9081592.
El-Rayes, K., and O. Moselhi. 2001. “Optimizing resource utilization for repetitive construction projects.” J. Constr. Eng. Manage. 127 (1): 18–27. https://doi.org/10.1061/(ASCE)0733-9364(2001)127:1(18).
Faghihi, V., K. F. Reinschmidt, and J. H. Kang. 2014. “Construction scheduling using genetic algorithm based on building information model.” Expert Syst. Appl. 41 (16): 7565–7578. https://doi.org/10.1016/j.eswa.2014.05.047.
Fang, X. 2012. “Research of construction schedule optimization using particle swarm optimization.” Adv. Mater. Res. 452 (8): 452–453. https://doi.org/10.4028/scientific5/AMR.452-453.441.
Glover, F., J. P. Kelly, and M. Laguna. 1996. “New advances and applications of combining simulation and optimization.” In Proc., 1996 Winter Simulation Conf. New York: IEEE.
Harmelink, D. J. 1995. “Linear scheduling model: The development of a linear scheduling model with micro computer applications for highway construction project control.” Theses and Dissertations, Dept. of Civil, Construction, and Environmental Engineering, Iowa State Univ.
Hu, Z., J. Zhang, and Z. Deng. 2008. “Construction process simulation and safety analysis based on building information model and 4D technology.” Tsinghua Sci. Technol. 13 (1): 266–272. https://doi.org/10.1016/S1007-0214(08)70160-3.
Johnson, D. W. 1981. “Linear scheduling method for highway construction.” J. Constr. Div. 107 (2): 247–261. https://doi.org/10.1061/JCCEAZ.0000960.
Kacprzyk, Z., and T. Kępa. 2014. “Building information modeling—4D modelling technology on the example of the reconstruction stairwell.” Procedia Eng. 91 (Jan): 226–231. https://doi.org/10.1016/j.proeng.2014.12.051.
Kalasapudi, V. S., and P. Tang. 2015. “Automated tolerance analysis of curvilinear components using 3D point clouds for adaptive construction quality control.” Congress Comput. Civ. Eng. 2015 (Jan): 57–65. https://doi.org/10.1061/9780784479247.008.
Karevan, A., M. Homayouni, A. Hesami, and S. Larki. 2016. “The comparison between simulated annealing algorithm and genetic algorithm in order to solve traveling salesman problem in Esfahan telecommunications companies.” In Proc., 3rd Int. Conf. on Industrial Engineering and Sustainable Management. Pisa, Italy: Sabanet Company.
Kim, C., H. Son, and C. Kim. 2013. “Automated construction progress measurement using a 4D building information model and 3D data.” Autom. Constr. 31 (May): 75–82. https://doi.org/10.1016/j.autcon.2012.11.041.
Kirkpatrick, S., C. D. Gelatt, and M. P. Vecchi. 1983. “Optimization by simulated annealing.” Science 220 (4598): 671–680. https://doi.org/10.1126/science.220.4598.671.
König, M., and U. Beißert. 2009. “Construction scheduling optimization by simulated annealing.” In Proc., 26th Int. Symp. on Automation and Robotics in Construction. London: International Association for Automation and Robotics in Construction.
Koo, C., T. Hong, C. Hyun, and K. Koo. 2010. “A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in multi-family housing projects.” Can. J. Civ. Eng. 37 (5): 739–752. https://doi.org/10.1139/L10-007.
Kumar, G. A., A. K. Patil, T. W. Kang, and Y. H. Chai. 2019. “Sensor fusion based pipeline inspection for the augmented reality system.” Symmetry 11 (10): 1325. https://doi.org/10.3390/sym11101325.
Kwiatek, C., M. Sharif, S. Li, C. Haas, and S. Walbridge. 2019. “Impact of augmented reality and spatial cognition on assembly in construction.” Autom. Constr. 108 (Dec): 102935. https://doi.org/10.1016/j.autcon.2019.102935.
Lee, C. H., M. H. Tsai, and S. C. Kang. 2014. “A visual tool for accessibility study of pipeline maintenance during design.” Visualization Eng. 2 (1): 6. https://doi.org/10.1186/s40327-014-0006-y.
Li, Y., and M. Jing. 2019. “Application research of BIM technology in water supply and drainage engineering.” J. Phys. 1168 (2): 022045. https://doi.org/10.1088/1742-6596/1168/2/022045.
Liao, Z., W. Wei, L. Zhao, and Y. Zhang. 2016. “Application of intelligent temperature control system of mass concrete based on BIM.” J. Civ. Archit. Environ. Eng. 38 (4): 132–138. https://doi.org/10.11835/j.issn.1674-4764.2016.04.019.
Liu, D., H. Li, H. Wang, C. Qi, and T. Rose. 2020. “Discrete symbiotic organisms search method for solving large-scale time-cost trade-off problem in construction scheduling.” Expert Syst. Appl. 148 (Jun): 113230. https://doi.org/10.1016/j.eswa.2020.113230.
Mikulakova, E., M. König, E. Tauscher, and K. Beucke. 2010. “Knowledge-based schedule generation and evaluation.” Adv. Eng. Inf. 24 (4): 389–403. https://doi.org/10.1016/j.aei.2010.06.010.
Miralinaghi, M., W. Woldemariam, D. M. Abraham, S. Chen, S. Labi, and Z. Chen. 2020. “Network-level scheduling of road construction projects considering user and business impacts.” Comput.-Aided Civ. Infrastruct. Eng. 35 (7): 650–667. https://doi.org/10.1111/mice.12518.
Moon, H., N. Dawood, and L. Kang. 2014. “Development of workspace conflict visualization system using 4D object of work schedule.” Adv. Eng. Inf. 28 (1): 50–65. https://doi.org/10.1016/j.aei.2013.12.001.
Mukhairez, H. H. A., and A. Y. A. Maghari. 2015. “Performance comparison of simulated annealing, GA and ACO applied to TSP.” Int. J. Intell. Comput. Res. 6 (4): 647–654.
Nahangi, M., and C. T. Haas. 2014. “Automated 3D compliance checking in pipe spool fabrication.” Adv. Eng. Inf. 28 (4): 360–369. https://doi.org/10.1016/j.aei.2014.04.001.
Nguyen, T. Q., and D. K. H. Chua. 2015. “Preemptive constraint analysis in construction schedules.” J. Constr. Eng. Manage. 29 (5): 04014062. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000363.
Park, J., and H. Cai. 2015. “Automatic construction schedule generation method through BIM model creation.” In Computing in civil engineering, 21–23. Reston, VA: ASCE.
Sigalov, K., and M. König. 2017. “Recognition of process patterns for BIM-based construction schedules.” Adv. Eng. Inf. 33 (Aug): 456–472. https://doi.org/10.1016/j.aei.2016.12.003.
Singh, J., and J. C. P. Cheng. 2021. “Automating the generation of 3D multiple pipe layout design using BIM and heuristic search methods.” Lec. Notes Civ. Eng. 98 (Aug): 54–72. https://doi.org/10.1007/978-3-030-51295-8_6.
Soltani, A. R., H. Tawfik, J. Y. Goulermas, and T. Fernando. 2002. “Path planning in construction sites: Performance evaluation of the Dijkstra, A∗, and GA search algorithms.” Adv. Eng. Inf. 16 (4): 291–303. https://doi.org/10.1016/S1474-0346(03)00018-1.
Wang, C., H. Abdul-Rahman, and W. S. Cheng. 2016. “Ant colony optimization (ACO) in scheduling overlapping architectural design activities.” J. Civ. Eng. Manage. 22 (6): 780–791. https://doi.org/10.3846/13923730.2014.91410.
Wang, Z., and E. R. Azar. 2018. “BIM-based draft schedule generation in reinforced concrete-framed buildings.” Constr. Innov. 19 (2): 280–294. https://doi.org/10.1108/CI-11-2018-0094.
Wu, I.-C., A. Borrmann, U. Beißert, M. König, and E. Rank. 2010. “Bridge construction schedule generation with pattern-based construction methods and constraint-based simulation.” Adv. Eng. Inf. 24 (4): 379–388. https://doi.org/10.1016/j.aei.2010.07.002.
Xu, S., E. S. L. Ho, and H. P. H. Shum. 2019. “A hybrid metaheuristic navigation algorithm for robot path rolling planning in an unknown environment.” Mech. Syst. Control 47 (4): 216–224. https://doi.org/10.2316/J.2019.201-3000.
Zhao, H., and Z. Ru. 2008. “Construction schedule optimization using particle swarm optimization.” In Proc., 4th Int. Conf. on Wireless Communications, Networking and Mobile Comp, 1–4. New York: IEEE.
Zhao, M., X. Wang, J. Yu, L. Bi, Y. Xiao, and J. Zhang. 2020. “Optimization of construction duration and schedule robustness based on hybrid grey: Wolf optimizer with sine cosine algorithm.” Energies 13 (1): 215. https://doi.org/10.3390/en13010215.
Zhou, L., L. Zhang, and Y. Fang. 2020. “Logistics service scheduling with manufacturing provider selection in cloud manufacturing.” Rob. Comput. Integr. Manuf. 65 (Oct): 101914. https://doi.org/10.1016/j.rcim.2019.101914.
Information & Authors
Information
Published In
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Aug 18, 2020
Accepted: Jan 15, 2021
Published online: Aug 23, 2021
Published in print: Nov 1, 2021
Discussion open until: Jan 23, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Chuanni He, Min Liu, Yuxiang Zhang, Zhigao Wang, Simon M. Hsiang, Gongfan Chen, Weiqiang Li, Gongfu Dai, Space–Time–Workforce Visualization and Conditional Capacity Synthesis in Uncertainty, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-4991, 39, 2, (2023).
- Ying Hong, Haiyan Xie, Eva Agapaki, Ioannis Brilakis, Graph-Based Automated Construction Scheduling without the Use of BIM, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-12687, 149, 2, (2023).
- Yoon-Soo Shin, Junhee Kim, Automated Dimension Estimation of Steel Pipes Stacked at Construction Sites Using Euclidean Distances Calculated by Overlapping Segmentation, Sensors, 10.3390/s22124517, 22, 12, (4517), (2022).
- Liang-Ting Tsai, Hung-Lin Chi, Tzong-Hann Wu, Shih-Chung Kang, AR-based automatic pipeline planning coordination for on-site mechanical, electrical and plumbing system conflict resolution, Automation in Construction, 10.1016/j.autcon.2022.104400, 141, (104400), (2022).
- Daniel M. Hall, Irfan Čustović, Ravina Sriram, Qian Chen, Teaching generative construction scheduling: Proposed curriculum design and analysis of student learning for the Tri-Constraint Method, Advanced Engineering Informatics, 10.1016/j.aei.2021.101455, 51, (101455), (2022).