Development of Cost and Schedule Data Integration Algorithm Based on Big Data Technology
Source abstract
Abstract
In the information age, the role of data in any industry is getting more and more important. In the construction industry, however, experts’ experience and intuition are still key determinants in decision-making, while other industries achieve tangible improvement in paradigm shifts by adopting cutting-edge information technology. Cost and schedule controls, which are closely connected, are decisive in the success of construction project execution. While a vast body of research has developed methodologies for cost-schedule integration over 50 years, there is no method used in practice; it remains a significant challenge in the construction industry. This study aims to propose a data processing algorithm for integrated cost-schedule data management employing big data technology. It is designed to resolve the main obstacle to the practicality of existing methods by providing integrity and flexibility in integrating cost-schedule data and reducing time on building and changing databases. The proposed algorithm is expected to transform field engineers’ current perception regarding information management as one of the troublesome tasks in a data-friendly way.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Big Data and Business Intelligence · BIM and Construction Integration
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Construction Big Data Research Center, Ninetynine Inc., Seoul 01905, Korea
Department of BIM Research Center, Yunwoo Technologies Inc., Seoul 05854, Korea
The Centre for Spatial Data Infrastructures and Land Administration, Department of Infrastructure Engineering, The University of Melbourne, Victoria 3010, Australia
Funding
Ministry of Land, Infrastructure and Transport
References (32)
Show source-provided references
1. Critical analysis of Big Data challenges and analytical methods10.1016/j.jbusres.2016.08.001 ↗
2. Big Data in the construction industry: A review of present status, opportunities, and future trends10.1016/j.aei.2016.07.001 ↗
3. Cost-and schedule-control integration: Issues and needs10.1061/(ASCE)0733-9364(1991)117:3(486) ↗
4. Database framework for cost, schedule, and performance data integration10.1061/(ASCE)CP.1943-5487.0000241 ↗
5. Planning for computer integrated construction10.1061/(ASCE)0887-3801(1999)13:4(217) ↗
6. Oinas, M. (1998, January 3–5). The utilization of product model data in production and procurement planning. Proceedings of the Life-Cycle of Construction IT Innovations—Technology Transfer from Research to Practice, Stockholm, Sweden.
7. LEAN, Green and Seen (The Issues of Societal Needs, Business Drivers and Converging Technologies Are Making BIM An Inevitable Method of Delivery and Management of the Built Environment)
8. An integrated construction project cost information system using MS AccessTM and MS ProjectTM10.1080/0144619042000201402 ↗
9. Teicholz, P.M. (1987). Current needs for cost control systems. Project Controls: Needs and Solutions, ASCE.
10. Hendrickson, C., Hendrickson, C.T., and Au, T. (1989). Project Management for Construction: Fundamental Concepts for Owners, Engineers, Architects, and Builders, Prentice-Hall.
11. Kim, J.J. (1989). An Object-Oriented Database Management System Approach to Improve Construction Project Planning and Control. [Ph.D. Thesis, University of Illinois].
12. Fleming, Q.W., and Koppelman, J.M. (2005). Earned Value Project Management. 3. Painos, Project Management Institute.
13. Information management to integrate cost and schedule for civil engineering projects10.1061/(ASCE)0733-9364(1998)124:5(381) ↗
14. Flexible work breakdown structure for integrated cost and schedule control10.1061/(ASCE)0733-9364(2004)130:5(616) ↗
15. Research on Technology Innovation Management in Big Data Environment10.1088/1755-1315/113/1/012141 ↗
16. Holst, A. (2019, October 20). Big Data Market Size Revenue Forecast Worldwide from 2011 to 2027. Available online: https://www.statista.com/statistics/254266/global-big-data-market-forecast/.
17. Manyika, J., and Chui, M. (2011). Big Data: The Next Frontier for Innovation, Competition, and Productivity, McKinsey Global Institute. Available online: https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/McKinsey%20Digital/Our%20Insights/Big%20data%20The%20next%20frontier%20for%20innovation/MGI_big_data_full_report.pdf.
18. Ma, G., and Wu, M. (2019). A Big Data and FMEA-based construction quality risk evaluation model considering project schedule for Shanghai apartment projects. Int. J. Qual. Reliab. Manag.10.1108/IJQRM-11-2018-0318 ↗
19. Investigating profitability performance of construction projects using big data: A project analytics approach10.1016/j.jobe.2019.100850 ↗
20. Predicting construction materials prices using fuzzy logic and neural networks10.1061/(ASCE)CO.1943-7862.0000707 ↗
21. Research on optimization of big data construction engineering quality management based on RNN-LSTM10.1155/2018/9691868 ↗
22. A big data-based workers behavior observation in China metro construction10.1016/j.proeng.2015.10.077 ↗
23. Cost, schedule, and time variances and integration10.1061/(ASCE)0733-9364(1993)119:2(245) ↗
24. Kitchin, R., and McArdle, G. (2016). What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets. Big Data Soc., 3.10.1177/2053951716631130 ↗
25. Technology management of IT in construction: A driver or an enabler10.1108/09576059910256583 ↗
26. Kim, H., Kim, W., and Yi, Y. (2014). Awareness on Big Data of Construction Firms and Future Directions, Construction & Economy Research Institute of Korea.
27. Sørensen, A.Ø., Olsson, N., and Landmark, A.D. (June, January 30). Big Data in Construction Management Research. Proceedings of the CIB World Building Congress 2016, Tampere, Finland.
28. A social–product–process framework for construction10.1080/09613218.2019.1691487 ↗
29. Cho, D. (2009). Construction Information Database Framework (CIDF) for Integrated Cost, Schedule, and Performance Control. [Ph.D. Thesis, University of Wisconsin].
30. Construction Specifications Institute (CSI) and Construction Specifications Canada (CSC) (2010). UniFormat, Available online: https://www.csiresources.org/standards/uniformat.
31. The Construction Specifications Institute and Construction (2016). MasterFormat, Available online: https://www.csiresources.org/standards/masterformat.
32. 3D property research from a legal perspective10.1016/j.compenvurbsys.2012.11.004 ↗