An Intelligent Decision-Making Model for the Design of Precast Slab Joints Based on Case-Based Reasoning
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 5
Abstract
Precast components are a critical part of the life cycle of prefabricated construction. Component joints and connections are essential to structural stability, posing rework problems. The design of precast component joints requires tacit and explicit knowledge. Existing joint design approaches and construction requirements underuse tacit knowledge. This paper proposes a case-based reasoning (CBR) model to support the design of component joints based on this tacit knowledge. A case library of 299 valid precast slabs was used to develop the model. The test cases in the model were used to verify the methodology. Records for 64 test cases with the same building information and 64 test cases from different buildings were used to validate the usability and effectiveness of the model. The results show that the accuracy rates are 100% and 94% when considering the comprehensive performance, and the model is more effective for different buildings than for the same building. The proposed model can improve the efficiency of joint design without expert participation and improve the standardization and coordination of design and construction.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The study was financially supported by the National Natural Science Foundation of China (Grant No. 72071120) and the Institute for Guo Qiang Tsinghua University. The authors would also like to thank all project managers and designers interviewed for their assistance in data collection.
References
Al-Saadi, S. N., and K. S. Al-Jabri. 2020. “Optimization of envelope design for housing in hot climates using a genetic algorithm (GA) computational approach.” J. Build. Eng. 32 (Nov): 101712. https://doi.org/10.1016/j.jobe.2020.101712.
Anthony, B. J. 2021. “A case-based reasoning recommender system for sustainable smart city development.” AI Soc. 36 (1): 159–183. https://doi.org/10.1007/s00146-020-00984-2.
Ataei, A., M. A. Bradford, and H. R. Valipour. 2016. “Finite element analysis of HSS semi-rigid composite joints with precast concrete slabs and demountable bolted shear connectors.” Finite Elem. Anal. Des. 122 (Dec): 16–38. https://doi.org/10.1016/j.finel.2016.08.003.
Ayhan, M., I. Dikmen, and M. T. Birgonul. 2021. “Predicting the occurrence of construction disputes using machine learning techniques.” J. Constr. Eng. Manage. 147 (4): 04021022. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002027.
Bhattacharya, A., R. T. Goswami, and K. Mukherjee. 2019. “A feature selection technique based on rough set and improvised PSO algorithm (PSORS-FS) for permission based detection of Android malwares.” Int. J. Mach. Learn. Cybern. 10 (Jul): 1893–1907. https://doi.org/10.1007/s13042-018-0838-1.
Brown, N. C., and C. T. Mueller. 2019. “Design variable analysis and generation for performance-based parametric modeling in architecture.” Int. J. Archit. Comput. 17 (1): 36–52. https://doi.org/10.1177/1478077118799491.
Bugata, P., and P. Drotar. 2020. “On some aspects of minimum redundancy maximum relevance feature selection.” Sci. China Inf. Sci. 63 (Jan): 112103. https://doi.org/10.1007/s11432-019-2633-y.
Cao, X., X. Li, Y. Zhu, and Z. Zhang. 2015a. “A comparative study of environmental performance between prefabricated and traditional residential buildings in China.” J. Cleaner Prod. 109 (Dec): 131–143. https://doi.org/10.1016/j.jclepro.2015.04.120.
Cao, X., Z. Li, and S. Liu. 2015b. “Study on factors that inhibit the promotion of SI housing system in China.” Energy Build. 88 (Feb): 384–394. https://doi.org/10.1016/j.enbuild.2014.11.064.
Carla, G., M. Mabsout, and A. M. Mohamed-Asem. 2020. “Knowledge management systems for structural engineering design in the era of emerging technological advancements.” In Construction research congress 2020, 398–407. Reston, VA: ASCE.
Chandrashekar, G., and F. Sahin. 2014. “A survey on feature selection methods.” Comput. Electr. Eng. 40 (1): 16–28. https://doi.org/10.1016/j.compeleceng.2013.11.024.
Chen, L., and S. Mohamed. 2010. “The strategic importance of tacit knowledge management activities in construction.” Constr. Innovation 10 (2): 138–163. https://doi.org/10.1108/14714171011037165.
Ding, M., W. Xu, J. Wang, Y. Chen, X. Du, and R. Fang. 2022. “Seismic performance of prefabricated concrete columns with grouted sleeve connections, and a deformation-capacity estimation method.” J. Build. Eng. 55 (Sep): 104722. https://doi.org/10.1016/j.jobe.2022.104722.
Dong, L., D. Chen, N. Wang, and Z. Lu. 2020. “Key energy-consumption feature selection of thermal power systems based on robust attribute reduction with rough sets.” Inf. Sci. 532 (Sep): 61–71. https://doi.org/10.1016/j.ins.2020.03.085.
Elsanadedy, H. M. 2021. “New moment-resisting beam-column joints to increase progressive collapse resistance of precast concrete buildings.” J. Build. Eng. 44 (Dec): 102884. https://doi.org/10.1016/j.jobe.2021.102884.
Faia, R., T. Pinto, O. Abrishambaf, F. Fernandes, Z. Vale, and J. M. Corchado. 2017. “Case based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy management.” Energy Build. 155 (Nov): 269–281. https://doi.org/10.1016/j.enbuild.2017.09.020.
Frazzon, E. M., M. Freitag, and D. Ivanov. 2021. “Intelligent methods and systems for decision-making support: Toward digital supply chain twins.” Int. J. Inf. Manage. 57 (Apr): 102281. https://doi.org/10.1016/j.ijinfomgt.2020.102281.
Fuchs, B., J. Lieber, A. Mille, and A. Napoli. 2014. “Differential adaptation: An operational approach to adaptation for solving numerical problems with CBR.” Knowl.-Based Syst. 68 (Sep): 103–114. https://doi.org/10.1016/j.knosys.2014.03.009.
Han, Z. M., and R. Han. 2013. “Composite floor slab and slab joint formed by the same.” CNN. April 24, 2013.
Huang, Z., H. Fan, and L. Shen. 2019. “Case-based reasoning for selection of the best practices in low-carbon city development.” Front. Eng. Manage. 6 (3): 416–432. https://doi.org/10.1007/s42524-019-0036-1.
Ishak, M. F., and N. Hashim. 2020. “Precast connection behaviour using finite element.” IOP Conf. Ser.: Mater. Sci. Eng. 849 (May): 012084. https://doi.org/10.1088/1757-899X/849/1/012084.
Iwata, K. 2020. “Revisiting a nearest neighbor method for shape classification.” IEICE Trans. Inf. Syst. E103-D (12): 2649–2658. https://doi.org/10.1587/transinf.2020EDP7074.
Jia, L., Q. Li, Y. Zhang, W. Zhao, and M. Du. 2022. “Experimental study of the hysteretic behavior of prefabricated frame-shear wall structures with grouting sleeve connections.” J. Build. Eng. 57 (Oct): 104704. https://doi.org/10.1016/j.jobe.2022.104704.
Konczak, A., and J. Paslawski. 2015. “Decision support in production planning of precast concrete slabs based on simulation and learning from examples.” Procedia Eng. 122 (Jan): 81–87. https://doi.org/10.1016/j.proeng.2015.10.010.
Koo, B., R. Jung, and Y. Yu. 2021. “Automatic classification of wall and door BIM element subtypes using 3D geometric deep neural networks.” Adv. Eng. Inf. 47 (Jan): 101200. https://doi.org/10.1016/j.aei.2020.101200.
Kwon, N., Y. Ahn, B. Son, and H. Moon. 2021. “Developing a machine learning-based building repair time estimation model considering weight assigning methods.” J. Build. Eng. 43 (Nov): 102627. https://doi.org/10.1016/j.jobe.2021.102627.
Kwon, N., J. Cho, H. S. Lee, I. Yoon, and M. Park. 2019. “Compensation cost estimation model for construction noise claims using case-based reasoning.” J. Constr. Eng. Manage. 145 (8): 0401907. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001675.
Lee, H. J., and H. S. Kim. 2015. “eHealth recommendation service system using ontology and case-based reasoning.” In Proc., 2015 IEEE Int. Conf. on Smart City/SocialCom/SustainCom (SmartCity), 1108–1113. Los Alamitos: IEEE Computer Society.
Lin, W. Y., and Y. Huang. 2019. “Filtering of irrelevant clashes detected by BIM software using a hybrid method of rule-based reasoning and supervised machine learning.” Appl. Sci. 9 (24): 5324. https://doi.org/10.3390/app9245324.
Liu, H., G. Singh, M. Lu, A. Bouferguene, and M. Al-Hussein. 2018. “BIM-based automated design and planning for boarding of light-frame residential buildings.” Autom. Constr. 89 (May): 235–249. https://doi.org/10.1016/j.autcon.2018.02.001.
Liu, J., H. Li, M. Skitmore, and Y. Zhang. 2019. “Experience mining based on case-based reasoning for dispute settlement of international construction projects.” Autom. Constr. 97 (Jan): 181–191. https://doi.org/10.1016/j.autcon.2018.11.006.
Ma, D., X. Li, B. Lin, and Y. Zhu. 2022. “An intelligent retrofit decision-making model for building program planning considering tacit knowledge and multiple objectives.” Energy 263 (Jan): 125704. https://doi.org/10.1016/j.energy.2022.125704.
Madkour, H., M. Maher, and O. Ali. 2022. “Finite element analysis for interior slab-column connections reinforced with GFRP bars using damage plasticity model.” J. Build. Eng. 48 (May): 104013. https://doi.org/10.1016/j.jobe.2022.104013.
Mishra, N., S. Petrovic, and S. Sundar. 2011. “A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy.” Med. Phys. 38 (12): 6528–6538. https://doi.org/10.1118/1.3660517.
Mohandes, S. R., S. Durdyev, H. Sadeghi, A. Mahdiyar, M. R. Hosseini, S. Banihashemi, and I. Martek. 2022. “Towards enhancement in reliability and safety of construction projects: Developing a hybrid multi-dimensional fuzzy-based approach.” Eng. Constr. Archit. Manage. https://doi.org/10.1108/ECAM-09-2021-0817.
MOHURD. 2015. Code for design of concrete structures (GB 50010-2010) (2015 Edition). Beijing: China Architecture & Building Press.
MOHURD. 2019. Assessment standard for green building (GB/T 50378). Beijing: China Architecture & Building Press.
Mota, V. C., F. A. Damasceno, and D. F. Leite. 2018. “Fuzzy clustering and fuzzy validity measures for knowledge discovery and decision making in agricultural engineering.” Comput. Electron. Agric. 150 (Jul): 118–124. https://doi.org/10.1016/j.compag.2018.04.011.
Mulayim, M. O., and J. L. Arcos. 2020. “Fast anytime retrieval with confidence in large-scale temporal case bases.” Knowl.-Based Syst. 206 (Oct): 106374. https://doi.org/10.1016/j.knosys.2020.106374.
Nightingale, P. 2009. “Tacit knowledge and engineering design.” In Handbook of the philosophy of science, philosophy of technology and engineering sciences, 351–374. Amsterdam, Netherland: Elsevier. https://doi.org/10.1016/B978-0-444-51667-1.50017-3.
Oliveira, H., F. Louf, E. Herve-Secourgeon, and F. Gatuingt. 2020. “Wall-slab joint parameter identification of a reinforced concrete structure using possibly corrupted modal data.” Int. J. Numer. Anal. Methods Geomech. 44 (1): 19–39. https://doi.org/10.1002/nag.2994.
Pan, Y., and L. Zhang. 2021. “Roles of artificial intelligence in construction engineering and management: A critical review and future trends.” Autom. Constr. 122 (Feb): 103517. https://doi.org/10.1016/j.autcon.2020.103517.
Polanyi, M. 1969. Knowing and being. Chicago: Univ. of Chicago Press.
Pugna, A. P., and S. A. Potra. 2021. “A strategic decision making tool for new product and service design.” Manage. Decis. 59 (2): 406–425. https://doi.org/10.1108/MD-01-2019-0110.
Ramasamy, M., and A. M. Kowshalya. 2022. “Information gain based feature selection for improved textual sentiment analysis.” Wireless Pers. Commun. 125 (2): 1203–1219. https://doi.org/10.1007/s11277-022-09597-y.
Ransikarbum, K., and S. J. Mason. 2016. “Goal programming-based post-disaster decision making for integrated relief distribution and early-stage network restoration.” Int. J. Prod. Econ. 182 (Dec): 324–341. https://doi.org/10.1016/j.ijpe.2016.08.030.
Ray, P., S. S. Reddy, and T. Banerjee. 2021. “Various dimension reduction techniques for high dimensional data analysis: A review.” Artif. Intell. Rev. 54 (Jun): 3473–3515. https://doi.org/10.1007/s10462-020-09928-0.
Saleh, H., and R. Burgueno. 2018. “Emerging artificial intelligence methods in structural engineering.” Eng. Struct. 171 (Sep): 170–189. https://doi.org/10.1016/j.engstruct.2018.05.084.
Sapra, V., M. L. Saini, and L. Verma. 2021. “Identification of coronary artery disease using artificial neural network and case-based reasoning.” Recent Adv. Comput. Sci. Commun. 14 (8): 2651–2661. https://doi.org/10.2174/2666255813999200613225404.
Shen, K., X. Li, X. Cao, and Z. Zhang. 2021. “Research on the rework risk core tasks in prefabricated construction in China.” Eng. Constr. Archit. Manage. 28 (10): 3299–3321. https://doi.org/10.1108/ECAM-07-2020-0521.
Shen, K., X. Li, X. Cao, and Z. Zhang. 2022. “Prefabricated construction process optimization based on rework risk.” J. Constr. Eng. Manage. 148 (6): 04022031. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002277.
Shen, L., H. Yan, H. Fan, Y. Wu, and Y. Zhang. 2017. “An integrated system of text mining technique and case-based reasoning (TM-CBR) for supporting green building design.” Build. Environ. 124 (Nov): 388–401. https://doi.org/10.1016/j.buildenv.2017.08.026.
Sierra, L. A., V. Yepes, T. Garcia-Segura, and E. Pellicer. 2018. “Bayesian network method for decision-making about the social sustainability of infrastructure projects.” J. Cleaner Prod. 176 (Mar): 521–534. https://doi.org/10.1016/j.jclepro.2017.12.140.
Tan, W., X. Yan, J. Lin, X. Zhao, and C. Lian. 2019. Structural technology of prefabricated concrete buildings. [In Chinese.] Beijing: China Architecture and Building Press.
Tang, M. 1997. “A knowledge-based architecture for intelligent design support.” Knowl. Eng. Rev. 12 (4): 387–406. https://doi.org/10.1017/S0269888997004025.
Tian, Y., and S. Spatari. 2022. “Environmental life cycle evaluation of prefabricated residential construction in China.” J. Build. Eng. 57 (Oct): 104776. https://doi.org/10.1016/j.jobe.2022.104776.
Wang, C., Y. Huang, W. Ding, and Z. Cao. 2021. “Attribute reduction with fuzzy rough self-information measures.” Inf. Sci. 549 (Mar): 68–86. https://doi.org/10.1016/j.ins.2020.11.021.
Wang, J., S. X. Xu, and G. Xu. 2020. “Intelligent decision making for service and manufacturing industries.” J. Intell. Manuf. 31 (Dec): 2089–2090. https://doi.org/10.1007/s10845-019-01482-z.
Xie, X., Z. Long, and W. Liao. 2015. “Improvement and analysis of ID3 algorithm in decision-making tree.” In Vol. 9808 of Proc., Int. Conf. on Intelligent Earth Observing and Applications 2015, 98083E. Bellingham, WA: SPIE. https://doi.org/10.1117/12.2222194.
Xiong, W., Z. Xiong, Y. Cui, and Y. Lv. 2020. “A discriminative distillation network for cross-source remote sensing image retrieval.” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 13 (Mar): 1234–1247. https://doi.org/10.1109/JSTARS.2020.2980870.
Xu, Z., S. Li, H. Li, and Q. Li. 2018. “Modeling and problem solving of building defects using point clouds and enhanced case-based reasoning.” Autom. Constr. 96 (Dec): 40–54. https://doi.org/10.1016/j.autcon.2018.09.003.
Yardim, Y., A. M. T. Waleed, M. S. Jaafar, and S. Laseima. 2013. “AAC-concrete light weight precast composite floor slab.” Constr. Build. Mater. 40 (Mar): 405–410. https://doi.org/10.1016/j.conbuildmat.2012.10.011.
Ying, S., and H. Liu. 2021. “The application of big data in enterprise information intelligent decision-making.” IEEE Access 9 (Aug): 120274–120284. https://doi.org/10.1109/ACCESS.2021.3104147.
Yuan, Z., C. Sun, and Y. Wang. 2018. “Design for manufacture and assembly-oriented parametric design of prefabricated buildings.” Autom. Constr. 88 (Apr): 13–22. https://doi.org/10.1016/j.autcon.2017.12.021.
Zhang, B., X. Li, B. Lin, and Y. Zhu. 2021a. “A CBR-based decision-making model for supporting the intelligent energy-efficient design of the exterior envelope of public and commercial buildings.” Energy Build. 231 (Jan): 110625. https://doi.org/10.1016/j.enbuild.2020.110625.
Zhang, F., A. P. C. Chan, A. Darko, Z. Chen, and D. Li. 2022. “Integrated applications of building information modeling and artificial intelligence techniques in the AEC/FM industry.” Autom. Constr. 139 (Jul): 104289. https://doi.org/10.1016/j.autcon.2022.104289.
Zhang, X. P., J. X. Liu, B. Q. Cao, and M. Shi. 2021b. “Web service classification based on information gain theory and bidirectional long short-term memory with attention mechanism.” Concurrency Comput. Pract. Exp. 33 (13): e6202. https://doi.org/10.1016/j.autcon.2022.104289.
Zhang, Y., I. Flood, Q. Yang, and C. J. Kibert. 2016. “Using genetic algorithm-based dependency structure matrix for prefabrication design management.” ICCCBE 2016 (1): 1211–1218.
Zhang, Y., H. Wei, D. Zhao, Y. Han, and J. Chen. 2021c. “Understanding innovation diffusion and adoption strategies in megaproject networks through a fuzzy system dynamic model.” Front. Eng. Manage. 8 (1): 32–47. https://doi.org/10.1007/s42524-019-0082-8.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 5 • May 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Aug 16, 2022
Accepted: Jan 17, 2023
Published online: Mar 3, 2023
Published in print: May 1, 2023
Discussion open until: Aug 3, 2023
ASCE Technical Topics:
- Buildings
- Business management
- Case studies
- Construction engineering
- Construction management
- Decision making
- Engineering fundamentals
- Geotechnical engineering
- Geotechnical investigation
- Joints
- Methodology (by type)
- Model accuracy
- Models (by type)
- Penetration tests
- Practice and Profession
- Research methods (by type)
- Slabs
- Structural engineering
- Structural members
- Structural systems
- Structures (by type)
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.