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Olanrewaju, O. Building Information Modelling and Project-Lifecycle. Encyclopedia. Available online: https://encyclopedia.pub/entry/13241 (accessed on 19 April 2024).
Olanrewaju O. Building Information Modelling and Project-Lifecycle. Encyclopedia. Available at: https://encyclopedia.pub/entry/13241. Accessed April 19, 2024.
Olanrewaju, Oludolapo. "Building Information Modelling and Project-Lifecycle" Encyclopedia, https://encyclopedia.pub/entry/13241 (accessed April 19, 2024).
Olanrewaju, O. (2021, August 17). Building Information Modelling and Project-Lifecycle. In Encyclopedia. https://encyclopedia.pub/entry/13241
Olanrewaju, Oludolapo. "Building Information Modelling and Project-Lifecycle." Encyclopedia. Web. 17 August, 2021.
Building Information Modelling and Project-Lifecycle
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The Architecture, Engineering, Construction and Operations (AECO) industry constitutes a cornerstone of a country’s economy and is predicted to account for circa 15% of the World’s Gross Domestic Product (GDP) by 2030. Construction outputs create critical infrastructure and buildings that cumulatively constitute the built environment which provides the basis for society and other industries to flourish; hence, the economic contribution is perhaps greater than the estimated “direction” contribution to the GDP. Annually, the AECO industry is responsible for nearly 40% of the total energy use, 32% of CO2 emissions and 25% of the generated waste in Europe. Furthermore, in many developing countries, the construction industry has undergone substantial fluctuations to accomplish its local economic objectives. As a result, many developing countries’ financial procedures are in the process of improvement. In these countries, construction projects frequently face several time-schedule delays. Furthermore, the industry is faced with numerous productivity issues stemming from the lack of adoption of emerging technologies or concepts such as Building Information Modelling (BIM), blockchain, Internet of Things (IoT) and Industry 4.0. As a result, the construction industry in developing countries does not achieve government goals for society and clients, and a need for developing “overall success construction projects” that are resource-efficient has been underlined in the literature.

building information modelling drivers Awareness

1. Introduction

BIM implementation continues to gain exponential momentum among global construction professionals [1]. For example, the National Building Specification (NBS) [2] revealed that there is a high level of BIM awareness in the UK, Canada, Finland and New Zealand. Consequently, BIM awareness and adoption have grown expeditiously from 10% in 2011 to nearly 70% in 2019 [3]. McGraw-Hill [4] revealed the implementation rate of BIM in Australia to be 64% while Rodgers, et al. [5] indicated a 48% level of adoption among Small–Medium Enterprises (SMEs). However, Tookey [6] revealed that there are doubts about the advantage of BIM in New Zealand’s construction industry.
In sub-Saharan Nigeria (as an exemplar of a developing country), Anifowose, et al. [7] indicated the adoption level of BIM as 50% while Ogunmakinde and Umeh [8] recorded a 58% level of awareness. Olanrewaju, et al. [9] also reported a high level of BIM awareness at the design stage which concurs with the findings of Onungwa and Uduma-Olugu [10] where client satisfaction and drawing improvement were identified as the major reasons for BIM usage at the design stage. However, Olapade and Ekemode [11] reported that there is very low awareness of BIM implementation for facility management practices in Nigeria. Literature suggests that many Nigerian construction professionals are aware of BIM and its potential benefits. For other developing countries, Gamil and Rahman [12] highlighted that 38% of Yemen’s construction practitioners are aware of the benefits of BIM while 8% are already implementing it. Similarly, Ismail, et al. [13] assessed the level of BIM uptake in Asian developing countries including China, Malaysia, India, Indonesia, Thailand, Myanmar, Sri Lanka, Mongolia, Vietnam and Pakistan. The study reported a low level of BIM implementation in the region. Nonetheless, China is at the forefront of BIM adoption due to its hybrid system, i.e., it has attributes of both a developed and developing country. Mehran [14] reported that the use of BIM in the United Arab Emirates (UAE) is gathering momentum while Shibani, et al. [15] indicated a low level of BIM awareness in Lebanon.
Recently, there has been positive feedback regarding BIM awareness in some developing countries such as South Africa [16]. This connotes that much work has been done regarding promoting the use of BIM in developing economies. Conclusively, construction professionals in developing countries are becoming aware of the benefits BIM offers, and the major problem lies in implementing BIM for construction projects. For instance, Olanrewaju, et al. [9] stated that only the Eko Atlantic City project has fully implemented BIM (i.e., from design to operation stage) in Nigeria.

2. BIM and Project Lifecycle

Raouf et al. [17] proffered that BIM has transformed traditional construction-project-management practices which in turn impact the project lifecycle. BIM usage varies across this lifecycle which is periodically punctuated by inputs from diverse professionals at various stages of development—defined for brevity as design (e.g., designers and architects), construction (e.g., contractors) and operation stages (e.g., facility managers) [9][18]. The BIM usage at different project lifecycle stages is shown in Table 1 which was adapted from our previous study. 
Table 1. BIM usage and awareness in project lifecycle.
Constructs Code
Design stage  
Cost Estimation AW1
Construction Planning AW2
3D Coordination AW3
Prefabrication AW4
Visualization AW5
Constructability Analysis AW6
Sequencing AW7
Construction stage  
Construction Monitoring AW10
Maintenance Scheduling AW11
Fabrication AW12
Operation stage  
Asset Management AW13
Building System Analysis AW8
Record Modelling AW9
Note: Adapted from Olanrewaju, et al. [19].

2.1. Design Stage

The design stage often involves a virtual collaboration between the architect/designer, structural engineer and mechanical and electrical services engineer to ensure design clashes are minimised in a federated model [20]. In addition, depending on the country’s legalizations, BIM models are implemented using different software (ArchiCAD, Revit or SketchUp, CYPE MEP, DDS-CAD,). These models are imported into simulation software packages (e.g., Ecotect or IES-VE) to assess building features and sustainability. After the successful design, the quantity surveyor is responsible for using BIM tools such as costX, Navisworks or Vico to generate thorough cost analysis and Bills of Quantities. The final designs and cost details are then presented to the client for contractor selection and project commencement. In summary, BIM in the design stage not only enables visualisation of the project and design but also enhances the project by reducing the cost without affecting the quality. Chahrour, et al. [21] expressed that BIM offers cost savings through early clash detection in design before the project execution. It has also been viewed as a tool that facilitates a smart contract-automation process and effective collaboration among team members [22][23]. Cheng, et al. [24] argued that BIM has the potential to enhance the efficiency of facility maintenance management for MEP components (mechanical, electrical and plumbing) in building projects.

2.2. Construction Stage

During the construction stage, the “as-designed” BIM model produced is used by the contractor and consultant to ensure appropriate cost and time management and track the project progress; however, changes will be needed to reflect the final “as-built” structure to cater to client variations [18]. Olanrewaju, et al. [9] also highlighted construction monitoring, maintenance scheduling and fabrication as the main uses of BIM during the construction stage. Similarly, Eastman, et al. [25] mentioned monitoring, modelling and fabrication as the major uses of BIM. The 3D models contain essential data related to building projects essential for BIM procedures, far better than usual construction methods [26]. BIM techniques deliver the chance to organize project data, such as building geometry, and construction typology that can be used in creating informed decisions [27][28]. Consequently, BIM represents an effective tool for obtaining an accurate model that reflects the “as-is condition” or “as-built” condition in a project [26]. Currently, key technological advances enabled detailed three-dimensional (3D) models to illustrate the “as-is condition” of buildings projects [29][30]. Three-dimensional laser scanning is a reality-capture technique that aims to collect the greatest and extremely accurate data about “as-built” or “as-is condition” [26].

2.3. Operation Stage

The operation stage is characterised by maintenance and facility management operations aimed at improving the building’s lifespan. Comparatively, this area attracts less research, and general awareness is low (even in developed countries); however, some advanced applications in the industry are apparent [31]. Within the developing country of Nigeria, Olapade and Ekemode [11] expressed the low level of BIM awareness among facility management professionals. Additionally, Olanrewaju, et al. [9] reported a low level of BIM awareness at the operation stage in the Nigerian construction industry and potential applications that include asset management, building system analysis and record modelling. Elsewhere, Xu, et al. [18] also mentioned that BIM could be used for emergency management, lifecycle management and facility management. In addition, the implementation of the BIM concept in the building industry also belongs to the category of the digital twin approach for enhancement of building maintenance [32]. Digital twin has been the subject of various classic studies for increasing performance and decreasing operating costs in assets, machines, processes and specific applications with different integration and levels [33]. As a result, throughout the BIM implementation process, the design concept is turned into a three-dimensional model and then progressively into architecture for better performance maintenance procedures [32].

3. Drivers of BIM

The construction industry is characterized by poor document and information management which negatively impacts the project’s lifecycle. Saka and Chan [34] also reported that the industry is notoriously slow to adopt modern digital technologies such as BIM which has stunted industry growth and modernity. In recent years, BIM has grown in popularity as a tool for design and construction in the built environment across the world [1][35]. BIM has developed as a solution, with significant promise for generating, consolidating and maintaining these connected databases, which contain essential information for a facility (or a portfolio of facilities) to assist operations and maintenance [36]. In addition, Nieto-Julián, et al. [37] agreed that BIM can support members of a multi-disciplinary team from the heritage field by providing data interoperability. Furthermore, the study (ibid) revealed four major drivers of BIM adoption in Nigeria, viz.: (1) construction-related; (2) process-digitalization- and economics-related; (3) sustainability- and efficiency-related; and (4) visualization- and productivity-related. Stransky and Dlask [38] suggested that BIM aids decision making during project execution and improves construction productivity. Similarly, Eastman, et al. [25] asserted that BIM improves collaboration among project teams. Studies also highlight the benefit of BIM in cost estimation and management processes [19][39].
BIM has also been considered as a crucial tool in promoting sustainable construction/buildings through the term “Green BIM” which aims to reduce the impact of construction activities on the environment [40][41]. Amarasinghe and Soorige [42] demonstrated the use of BIM for building Lifecycle Assessment (LCA) and made recommendations on how to improve BIM-LCA assessments. The innate visualization capability of BIM is another critical driver for its adoption as it enables the client to virtually preview their proposed structure before construction commences. This empowers the design team with the flexibility to adjust certain building features in line with the client’s comments [19][25]. Lin and Hsu [43] adopted BIM to support problem visualization and management using a web-based API. This demonstrates the ability of BIM to visualize problems and work progress at an early stage. Table 2 summarizes the BIM drivers extracted from existing literature reviewed and categorized based on the BIM drivers’ groups identified in [19].
Table 2. Drivers of BIM implementation.
Drivers Code
Construction-related driver  
Construction planning and monitoring D13
Synchronized design and construction planning D12
Facilities management record model D14
Improved decision-making process D11
Improved productivity and collaboration D10
Process-digitalization- and economics-related driver  
BIM-enabled estimating capabilities D2
Controlled whole-life costs and environmental data D4
Potential economic benefits D3
Lifecycle data D8
Sustainability- and efficiency-related driver  
Green building standards incorporation D6
Increased efficiency and coordination D9
Improved customer service D7
Visualization- and productivity-related driver  
Construction process visualization D1
Improved quality and increased sustainability D5
Note: Adapted from Olanrewaju, et al. [19].

References

  1. Olugboyega, O.; Edwards, D.J.; Windapo, A.O.; Omopariola, E.D.; Martek, I. Development of a conceptual model for evaluating the success of BIM-based construction projects. Smart Sustain. Built Environ. 2020.
  2. NBS. NBS National BIM Report. 2014. Available online: https://www.thenbs.com/knowledge/nbs-national-bim-report-2014 (accessed on 30 January 2021).
  3. NBS. NBS National BIM Report. 2019. Available online: https://www.thenbs.com/knowledge/national-bim-report-2019 (accessed on 30 January 2021).
  4. McGraw-Hill. The Business Value of BIM in Australia and New Zealand: How Building Information Modelling Is Transforming the Design and Construction Industry. Available online: https://download.autodesk.com/temp/pdf/mcgraw_hill_business_value_of_bim_anz.pdf (accessed on 30 January 2021).
  5. Rodgers, C.; Hosseini, M.R.; Chileshe, N.; Rameezdeen, R. Building information modelling (BIM) within the Australian construction related small and medium sized enterprises: Awareness, practices and drivers. In Proceedings of the ARCOM 2015 31st Annual Conference of the Association of Researchers in Construction Management, Lincoln, UK, 7–9 September 2015; pp. 691–700.
  6. Tookey, J.E. Shaving BIM: Establishing A Framework for Future BIM Research in New Zealand. Int. J. Constr. Supply Chain. Manag. 2012, 2, 66–79.
  7. Anifowose, O.M.; Babarinde, S.A.; Olanrewaju, O.I. Adoption level of building information modelling by selected professionals in Kwara state. Environ. Technol. Sci. J. 2018, 9, 35–44.
  8. Ogunmakinde, O.E.; Umeh, S. Adoption of BIM in the Nigerian Architecture Engineering and Construction (AEC) Industry. Available online: https://www.researchgate.net/publication/328031625_Adoption_of_BIM_in_the_Nigerian_Architecture_Engineering_and_Construction_AEC_Industry (accessed on 30 January 2021).
  9. Olanrewaju, O.; Babarinde, S.A.; Salihu, C. Current State of Building Information Modelling in the Nigerian Construction Industry. J. Sustain. Archit. Civ. Eng. Geod. 2020, 27, 63–77.
  10. Onungwa, I.O.; Uduma-Olugu, N. Building information modelling and collaboration in the Nigerian construction industry. J. Constr. Bus. Manag. Prod. Eng. Rev. 2017, 1, 1–10.
  11. Olapade, D.T.; Ekemode, B.G. Awareness and utilisation of building information modelling (BIM) for facility management (FM) in a developing economy: Experience from Lagos, Nigeria. J. Facil. Manag. 2018, 16, 387–395.
  12. Gamil, Y.; Rahman, I.A.R. Awareness and challenges of building information modelling (BIM) implementation in the Yemen construction industry. J. Eng. Des. Technol. 2019, 17, 1077–1084.
  13. Ismail, N.A.A.; Chiozzi, M.; Drogemuller, R. An Overview of BIM Uptake in Asian Developing Countries. Available online: https://www.researchgate.net/publication/321079523_An_overview_of_BIM_uptake_in_Asian_developing_countries (accessed on 10 January 2021).
  14. Mehran, D. Exploring the Adoption of BIM in the UAE Construction Industry for AEC Firms. Procedia Eng. 2016, 145, 1110–1118.
  15. Shibani, A.; Ghostin, M.; Hassan, D.; Saidani, M.; Agha, A. Exploring the Impact of Implementing Building Information Modelling to Support Sustainable Development in the Lebanese Construction Industry: A Qualitative Approach. J. Mech. Civ. Eng. Geod. 2021, 7, 33–62.
  16. Akinradewo, O.; Oke, A.; Aigbavboa, C.; Molau, M. Assessment of the Level of Awareness of Robotics and Construction Automation in South African. In Collaboration and Integration in Construction, Engineering, Management and Technology; Springer: New York, NY, USA, 2021; pp. 129–132.
  17. Raouf, A.M.; Al-Ghamdi, S.G. Building information modelling and green buildings: Challenges and opportunities. Archit. Eng. Des. Manag. 2019, 15, 1–28.
  18. Xu, X.; Ma, L.; Ding, L. A framework for BIM-enabled life-cycle information management of construction project. Int. J. Adv. Robot. Syst. 2014, 11, 126.
  19. Olanrewaju, O.I.; Babarinde, S.A.; Chileshe, N.; Sandanayake, M. Drivers for implementation of building information modeling (BIM) within the Nigerian construction industry. J. Financ. Manag. Prop. Constr. Econ. Build. 2021.
  20. Pärn, E.; Edwards, D.; Sing, M.C. Origins and probabilities of MEP and structural design clashes within a federated BIM model. Autom. Constr. 2018, 85, 209–219.
  21. Chahrour, R.; Hafeez, M.A.; Ahmad, A.M.; Sulieman, H.I.; Dawood, H.; Rodriguez-Trejo, S.; Kassem, M.; Naji, K.K.; Dawood, N. Cost-benefit analysis of BIM-enabled design clash detection and resolution. Constr. Manag. Econ. 2021, 39, 55–72.
  22. McNamara, A.J.; Sepasgozar, S.M. Intelligent contract adoption in the construction industry: Concept development. Autom. Constr. 2021, 122, 103452.
  23. Badi, S.; Ochieng, E.; Nasaj, M.; Papadaki, M. Technological, organisational and environmental determinants of smart contracts adoption: UK construction sector viewpoint. Constr. Manag. Econ. 2021, 39, 36–54.
  24. Cheng, J.C.; Chen, W.; Chen, K.; Wang, Q. Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms. Autom. Constr. 2020, 112, 103087.
  25. Eastman, C.M.; Eastman, C.; Teicholz, P.; Sacks, R.; Liston, K. BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors, 2nd ed; John Wiley & Sons: Hoboken, NJ, USA, 2011.
  26. Almukhtar, A.; Saeed, Z.O.; Abanda, H.; Tah, J.H. Reality capture of buildings using 3D laser scanners. Civ. Eng. 2021, 2, 214–235.
  27. Ham, Y.; Golparvar-Fard, M. Mapping actual thermal properties to building elements in gbXML-based BIM for reliable building energy performance modeling. Autom. Constr. 2015, 49, 214–224.
  28. Sanhudo, L.; Ramos, N.M.; Martins, J.P.; Almeida, R.M.; Barreira, E.; Simões, M.L.; Cardoso, V. A framework for in-situ geometric data acquisition using laser scanning for BIM modelling. J. Build. Eng. 2020, 28, 101073.
  29. Lagüela, S.; Díaz-Vilariño, L.; Armesto, J.; Arias, P. Non-destructive approach for the generation and thermal characterization of an as-built BIM. Constr. Build. Mater. 2014, 51, 55–61.
  30. Sanhudo, L.; Ramos, N.M.; Martins, J.P.; Almeida, R.M.; Barreira, E.; Simões, M.L.; Cardoso, V. Building information modeling for energy retrofitting—A review. Renew. Sustain. Energy Rev. 2018, 89, 249–260.
  31. Edwards, D.J.; Pärn, E.; Love, P.E.; El-Gohary, H. Research note: Machinery, manumission, and economic machinations. J. Bus. Res. 2017, 70, 391–394.
  32. Sun, L.; Pei, A.; Qi, X.; Cao, S.; Yang, R.; Liu, X. Dynamic Analysis of Digital Twin System Based on Five-Dimensional Model. In Proceedings of the Journal of Physics: Conference Series, Chengdu, China, 13–15 December 2019; p. 072038.
  33. Aheleroff, S.; Xu, X.; Zhong, R.Y.; Lu, Y. Digital twin as a service (DTaaS) in industry 4.0: An architecture reference model. Adv. Eng. Inform. 2021, 47, 101225.
  34. Saka, A.B.; Chan, D.W. A scientometric review and metasynthesis of building information modelling (BIM) research in Africa. Buildings 2019, 9, 85.
  35. Chan, D.W.; Olawumi, T.O.; Ho, A.M. Perceived benefits of and barriers to Building Information Modelling (BIM) implementation in construction: The case of Hong Kong. J. Build. Eng. 2019, 25, 100764.
  36. Cavka, H.B.; Staub-French, S.; Poirier, E.A. Developing owner information requirements for BIM-enabled project delivery and asset management. Autom. Constr. 2017, 83, 169–183.
  37. Nieto-Julián, J.E.; Lara, L.; Moyano, J.J.S. Implementation of a TeamWork-HBIM for the Management and Sustainability of Architectural Heritage. Sustainability 2021, 13, 2161.
  38. Stransky, M.; Dlask, P. Process of matching work items between bim model and cost estimating software. Eng. Rural. Dev. 2018, 17, 856–864.
  39. Nagalingam, G.; Jayasena, H.S.; Ranadewa, K. Building information modelling and future quantity surveyor’s practice in Sri Lankan construction industry. In Proceedings of the Second World Construction Symposium, Colombo, Sri Lanka, 14–15 June 2013; pp. 81–92.
  40. Chileshe, N.; Jayasinghe, R.S.; Rameezdeen, R. Information flow-centric approach for reverse logistics supply chains. Autom. Constr. 2019, 106, 102858.
  41. Wu, J.; Lepech, M.D. Incorporating multi-physics deterioration analysis in building information modeling for life-cycle management of durability performance. Autom. Constr. 2020, 110, 103004.
  42. Amarasinghe, I.A.; Soorige, D.; Geekiyanage, D. Comparative study on Life Cycle Assessment of buildings in developed countries and Sri Lanka. Built Environ. Proj. Asset Manag. 2021.
  43. Lin, Y.-C.; Hsu, Y.-T. Enhancing the Visualization of Problems Tracking and Management Integrated BIM Technology for General Contractor in Construction. In Collaboration and Integration in Construction, Engineering, Management and Technology; Springer: New York, NY, USA, 2021; pp. 427–432.
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