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Development of a quality management system for precast concrete factories

    Wonseok Seo Affiliation
    ; Byungjoo Choi   Affiliation
    ; Dongyoun Shin Affiliation
    ; Jinyoung Kim   Affiliation

Abstract

The precast concrete (PC) method involves manufacturing reinforced concrete building components in a factory that are then transported to and assembled on a construction site. Compared to conventional methods, PC is widely employed as an advantageous means of creating a sustainable environment and improving construction quality. However, due to time and cost increase, many modern PC factories inspect only randomly selected component samples, for which they write inspection reports using paper-based forms. The storage and management of these documents associated with inspections within factories are essential because any defects that occur during the manufacturing process adversely affect the subsequent delivery and assembly activities. In this study, a mobile application capable of automated documentation and the storage, and input of systematic data was developed to generate a system for comprehensive quality management and assurance within PC factories. The developed system was tested in a PC factory, achieving a 47% time-saving rate compared to the conventional inspection method. Inspection reports of the developed system contain considerably more information than those of the conventional method and fundamentally prevent the risk of document damage and loss as they are automatically archived on a server in digital format.

Keyword : quality inspection, inspection report, precast concrete, off-site construction, OSC, automation

How to Cite
Seo, W., Choi, B., Shin, D., & Kim, J. (2023). Development of a quality management system for precast concrete factories. Journal of Civil Engineering and Management, 29(5), 475–486. https://doi.org/10.3846/jcem.2023.19228
Published in Issue
Jul 18, 2023
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Arashpour, M., Wakefield, R., Blismas, N., & Maqsood, T. (2015). Autonomous production tracking for augmenting output in off-site construction. Automation in Construction, 53, 13–21. https://doi.org/10.1016/j.autcon.2015.03.013

Ballard, G., Harper, N., & Zabelle, T. (2003). Learning to see work flow: an application of lean concepts to precast concrete fabrication. Engineering, Construction and Architectural Management, 10(1), 6–14. https://doi.org/10.1108/09699980310466505

Chen, J., & Mo, H. (2009). Numerical study on crack problems in segments of shield tunnel using finite element method. Tunnelling and Underground Space Technology, 24(1), 91–102. https://doi.org/10.1016/j.tust.2008.05.007

Clayton, M., Kunz, J., & Fischer, M. (1998). The Charrette test method. Center for Integrated Facility Engineering. https://cife.stanford.edu/charrette-test-method

Gan, Y., Shen, L., Chen, J., Tam, V. W. Y., Tan, Y., & Illankoon, I. M. C. S. (2017). Critical factors affecting the quality of industrialized building system projects in China. Sustainability, 9(2), 216. https://doi.org/10.3390/su9020216

Hajdukiewicz, M., Goggins, J., de la Torre, O., Holleran, D., & Keane, M. M. (2019). An automated standard-based life cycle quality inspection methodology for smart precast concrete solutions in buildings. Journal of Structural Integrity and Maintenance, 4(3), 123–134. https://doi.org/10.1080/24705314.2019.1627454

Hong, J., Shen, G. Q., Li, Z., Zhang, B., & Zhang, W. (2018). Barriers to promoting prefabricated construction in China: A cost–benefit analysis. Journal of Cleaner Production, 172, 649–660. https://doi.org/10.1016/j.jclepro.2017.10.171

Jacobsen, S., Marchand, J., & Gerard, B. (1998). Concrete cracks I: durability and self healing – a review. Paper presented at the Second International Conference on Concrete under Severe Conditions (CONSEC).

Jaillon, L., & Poon, C. S. (2009). The evolution of prefabricated residential building systems in Hong Kong: A review of the public and the private sector. Automation in Construction, 18(3), 239–248. https://doi.org/10.1016/j.autcon.2008.09.002

Jaillon, L., Poon, C.-S., & Chiang, Y. H. (2009). Quantifying the waste reduction potential of using prefabrication in building construction in Hong Kong. Waste Management, 29(1), 309–320. https://doi.org/10.1016/j.wasman.2008.02.015

Jiang, R., Mao, C., Hou, L., Wu, C., & Tan, J. (2018). A SWOT analysis for promoting off-site construction under the backdrop of China’s new urbanisation. Journal of Cleaner Production, 173, 225–234. https://doi.org/10.1016/j.jclepro.2017.06.147

Kim, M.-K., Cheng, J. C., Sohn, H., & Chang, C.-C. (2015). A framework for dimensional and surface quality assessment of precast concrete elements using BIM and 3D laser scanning. Automation in Construction, 49, 225–238. https://doi.org/10.1016/j.autcon.2014.07.010

Kim, M.-K., Wang, Q., Park, J.-W., Cheng, J. C., Sohn, H., & Chang, C.-C. (2016). Automated dimensional quality assurance of full-scale precast concrete elements using laser scanning and BIM. Automation in Construction, 72, 102–114. https://doi.org/10.1016/j.autcon.2016.08.035

Kong, L., Li, H., Luo, H., Ding, L., & Zhang, X. (2018). Sustainable performance of just-in-time (JIT) management in time-dependent batch delivery scheduling of precast construction. Journal of Cleaner Production, 193, 684–701. https://doi.org/10.1016/j.jclepro.2018.05.037

Korea Construction Standards Center. (2021). The Korean construction specifications. Precast concrete 14 20 52.

Lee, S., Kwon, S., Jeong, M., Hasan, S., & Kim, A. (2020). Automated on-site quality inspection and reporting technology for off-site construction (OSC)-based precast concrete members. In International Symposium on Automation and Robotics in Construction (ISARC) (pp. 1152–1159). International Association for Automation and Robotics in Construction. https://doi.org/10.22260/ISARC2020/0158

Ma, Z., Yang, Z., Liu, S., & Wu, S. (2018). Optimized rescheduling of multiple production lines for flowshop production of reinforced precast concrete components. Automation in Construction, 95, 86–97. https://doi.org/10.1016/j.autcon.2018.08.002

Nicał, A., & Anysz, H. (2020). The quality management in precast concrete production and delivery processes supported by association analysis. International Journal of Environmental Science and Technology, 17(1), 577–590. https://doi.org/10.1007/s13762-019-02597-9

Precast/Prestressed Concrete Institute. (1999). Manual for quality control for plants and production of structural precast concrete products (MNL-116-99).

Reichenbach, S., & Kromoser, B. (2021). State of practice of automation in precast concrete production. Journal of Building Engineering, 43, 102527. https://doi.org/10.1016/j.jobe.2021.102527

Sacks, R., Eastman, C. M., & Lee, G. (2004). Process model perspectives on management and engineering procedures in the precast/prestressed concrete industry. Journal of Construction Engineering and Management, 130(2), 206–215. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:2(206)

Shayanfar, M. A., Mahyar, P., Jafari, A., & Mohtadinia, M. (2017). Classification of precast concrete segments damages during production and transportation in mechanized shield tunnels of Iran. Civil Engineering Journal, 3(6), 412–426. https://doi.org/10.28991/cej-2017-00000101

U.S. National Precast Concrete Association. (2022). Quality control manual for precast concrete plants.

Wang, Q., Cheng, J. C., & Sohn, H. (2017). Automated estimation of reinforced precast concrete rebar positions using colored laser scan data. Computer‐Aided Civil and Infrastructure Engineering, 32(9), 787–802. https://doi.org/10.1111/mice.12293

Wang, Z., Hu, H., & Gong, J. (2018). Framework for modeling operational uncertainty to optimize offsite production scheduling of precast components. Automation in Construction, 86, 69–80. https://doi.org/10.1016/j.autcon.2017.10.026

Wang, Z., Hu, H., Gong, J., Ma, X., & Xiong, W. (2019). Precast supply chain management in off-site construction: A critical literature review. Journal of Cleaner Production, 232, 1204–1217. https://doi.org/10.1016/j.jclepro.2019.05.229

Wang, Z., Wang, T., Hu, H., Gong, J., Ren, X., & Xiao, Q. (2020). Blockchain-based framework for improving supply chain traceability and information sharing in precast construction. Automation in Construction, 111, 103063. https://doi.org/10.1016/j.autcon.2019.103063

Wang, Z., Zhang, Q., Yang, B., Wu, T., Lei, K., Zhang, B., & Fang, T. (2021). Vision-based framework for automatic progress monitoring of precast walls by using surveillance videos during the construction phase. Journal of Computing in Civil Engineering, 35(1), 04020056. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000933

Yin, S. Y., Tserng, H. P., Wang, J., & Tsai, S. (2009). Developing a precast production management system using RFID technology. Automation in Construction, 18(5), 677–691. https://doi.org/10.1016/j.autcon.2009.02.004

Yu, T., Man, Q., Wang, Y., Shen, G. Q., Hong, J., Zhang, J., & Zhong, J. (2019). Evaluating different stakeholder impacts on the occurrence of quality defects in offsite construction projects: A Bayesian-network-based model. Journal of Cleaner Production, 241, 118390. https://doi.org/10.1016/j.jclepro.2019.118390