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STATISTICS PROJECT
Sample Masters Project Management Dissertation Proposal
December 7, 2020
STATISTICS PROJECT
Sample Masters Project Management Dissertation Proposal
December 8, 2020
STATISTICS PROJECT

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Building Information Modeling (BIM); Is This the Key to a Sustainable Future?

Exploring the utilization of technological developments & intelligent techniques for enhanced productivity in construction projects

Introduction

Project management of construction projects is considered a challenging task due to its involvement with various project teams, higher labor levels, complex processes, higher risk elements, and budgetary constraints.

Moreover, the increasing expectations of higher profits using minimum resources and increasing sustainability requirements from the users have further influenced the project managers to adopt new methods that are cost-efficient and productive, and sustainable (Gharehchopogh, 2011).

Thus, much research was conducted in the last few decades to develop new integrated methods that can facilitate sustainable and cost-efficient developments, and this continues research effort lead to the development of various methods and computer-aided systems, and one of the most influential of which is Building Information Modeling (BIM)

Construction projects have been visualizing the designs through paper-based drawings or through physical models, which are utilized for transforming a ‘sketch’ to a physical model,’ and this was the point where there was a lack of integration and coordination amongst the team working of a certain project.

According to Conradi (2009), hundreds of drawings are designed for doing a certain project. Still, all these drawings are stand-alone segments of the complete design structure, which requires some central point of integration to present it into meaningful information.

Hence human intervention is required for connecting all these disintegrated pieces into one continuous block of information. Such scenarios were significantly changed with the introduction of Computer Aided Drafting (CAD). However, still, some issues arise in exchanging graphical information from one CAD system to another.

The construction industry has undergone a paradigm of such changes. Various other criteria can be introduced in one central framework in the form of BIM, which offers 3D integrated modeling with additional costs and time.

This enables the construction designer to perceive the building from the point of view of 3D designing and management of the building throughout its development and life cycle.

Moreover, they can also integrate the high-quality structures with comfortable designs complying with the defined regulations, optimizing energy, using sustainable and green constructional models while integrating elements of costs, quantities, and time frame-works of all activities within the same one model.

Hence all these requirements can only be fulfilled by utilizing a more developed and sophisticated digital-based information system known as Building Information Modeling (BIM) (Kumanayake & Bandara, 2012).

Research Problem / Scope

Much research has been performed on BIM utilization as it is a powerful tool for modeling and analysis, which provides integrative and collaborative processes.

However, the aspect on which this research will focus will be the critical factors of the utilization of BIM for enhanced project management, saving cost, and construction time. Therefore this research will examine the use of technology in project management related to cost estimation of sustainable construction projects, particularly in Australia.

Research Aims/Objectives

1. this research aims to find how current technological developments can assist stakeholders in; performing more accurate project cost estimations, reducing costings, reducing project risks, and improving project management, leading to in-time delivery of projects.

This research will discuss processes that will improve project delivery by applying intelligent costing solutions and will also provide methods for reducing the associated risks.

2. This research will then investigate the current use of intelligent solutions from a practical point of view in a case study. This will review how such systems have recently been applied and what results were or can be obtained.

The focus will be to gain critical information on how small and medium-scale construction industries in Austria can adapt to such changes to improve their productivity.

3. Finally, the research will review the Australian construction industry's status in utilizing these new revolutionary methods, the efforts the Government has made in this regard, and the industry's response.

This research will aim to influence the industrial stakeholders towards the adaptation of this technology via providing a clear framework or a path that can be followed for successful transformation.

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Literature Review

Information technology has always made its appearance in every field of life, and now it has been able to make its way to address the construction industry's challenges (Succar et al., 2012). This industry is facing several challenges, some of which were so complicated that they need integrated solutions to address the stakeholders' modern needs.

The researchers and stakeholders have been able to develop some measures that can assist them in dealing with these complicated challenges. Hence, intelligent techniques and cost estimation models are being introduced for handling the underlying problems (Gharehchopogh, 2011).

Enhancement in technology has thus created fundamental changes in the designs and infrastructure of the global construction sector. These changes can be easily observed through the increasing use of 2D and 3D CAD (Virtual Construction, 3 Dimensional AutoCAD), IS (Information System), CIC (Computer Information Construction), and IT (Information Technology). These systems have contributed to creating integrated and informative models that facilities the engineering aspects of construction projects.

The comindustry's plicated challenges whilude sustainable designing, information sharing across the stakeholders, predicting project performance at different phases and above all, mitigating risks associated with disputes, and undertaking risk estimations of cost overruns of a project (Ameh, and Osegbo, 2011). Currently, civil engineering has started to consider the introduction of Artificial Intelligence in cost estimations and other aspects.

Hence research is being performed for addressing the challenges faced by the industry with new logic and application of methods for handling problems in areas of poor design definition and uncertainty. Cost estimation is considered the prime process in any construction project as it is required to predict the costs required to complete the work within the project's scope.

Making accurate cost estimations is a knowledge-intensive engineering job and is crucial for ensuring the construction project's successful completion. Hence, various models were developed using computer-aided systems to facilitate this process, but most of them were stand-alone systems (Rogalska, 2008).

However, as discussed previously, the increasing requirements of the integrated approach that facilitates both sustainable and efficient engineering and project management aspects necessitated the need to develop and use systems that can eventually enhance the overall productivity of construction projects.

Thus, one such revolutionary system that has been developed is Building Information Modelling (BIM), which has since the last few years been increasingly used in the construction industry throughout the world, and more so in the developed countries. The systems are considered capable of producing highly efficient results.’ Thus many countries across the globe emphasized the use of this technology in their public and private sector projects, as evident from the research conducted by Khosrowshahi and Arayici 2012 for UK and Becerik-Gerber and Samara 2010 for the USA.

The fundamental reason for this gain in popularity is because of its ability to process data in real-time (real-time base modeling), project visualization in 4D with integrated dimensions of cost and time, making it a 6D model, along with its capabilities of simulation and analysis (Kumanayake and Bandara, 2012).

This means that the project data can be updated and shared across all the teams, ensuring that data and any revisions in the project plans are shared across all the project teams in real-time – saving time, costs and reducing chances of disputes. Moreover, this also ensures that the cost and project activity-related data are processed more accurately, reducing the risk of project overruns.

With the rapid increase in the concerns of global warming and greenhouse impacts, the trend of designing and implementing the infrastructure of sustainable construction has been increased in recent years (Wong and Fan 2013; Liua et al. 2015). An important aspect of BIM is to facilitate sustainable building designs to optimize the design of sustainable buildings.

As per Shane, et al. (2009), comprehensiveness and cost accuracy are essential in project planning, requiring concentration on different parameters for attaining an acceptable level of accuracy during the process. On the other hand, inaccurate planning often leads to many problems such as delays in construction, design changes, or even business bankruptcy in worst cases.

This detailed literature to be reviewed in this research would highlight how BIM can facilitate computer-aided cost estimations through the generation of accurate bill of quantities, integration of accurate data, which includes cost and sizes of each element of the structure, modeling, and planning. This use of BIM and its engineering aspects will be elaborated through undertaking a critical review of related case studies, taking a practical approach.

There are major concerns found in the global construction industry's performance related to lack of productivity and inefficiency apart from the project deliveries in fragments (Abubakar, et al., 2014; Ameh, and Osegbo 2011). Therefore, the industry required a need for mindset in setting the standards of performance and efficiency in delivering sustainable projects (Succar et al., 2013).

The important factors of consideration are infrastructure, quality, value, design attributes, cost-effectiveness, and effective collaboration of all stakeholders of particular construction projects (Nederveen, et al., 2011). Building Information Modelling (BIM) is one of the several initiatives adopted by the global construction sector in recent years to address these major factors. This collaboration framework's rapid popularity that has evolutionarily transformed the technology of construction infrastructure, quality, and designs has encouraged developed economies to utilize BIM on a mass scale.

However, Barati et al. (2013) asserted that BIM has the potential for the developed economies, but its awareness is important in the construction industry of developing countries. There are microscopic researches found on the application of BIM in Austria.

Infrastructure and designing of structures in the sustainable method are an important concern of Australia as the country is expected to develop considerable infrastructure projects in the years to come.

Hence, this research is proposed to study the level of awareness and the factors affecting the development of the sustainable construction sector in the subject country, primarily to evaluate the level of awareness and the potential barriers in the effective implementation of BIM in this region.

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Research Methods

This research will be carried out by conducting an extensive literature review in which relevant theories related to intelligent techniques utilized in the construction industry will be discussed. Various renowned journals will be selected related to construction management and the ones associated with information technology. Next, all the identified techniques will be classified based on their scientific concepts and their application in the construction industry.

Research Plan

References

Abubakar, M., Ibrahim, Y., Kado, D., and Bala, K. (2014) Contractors' Perception of the Factors Affecting Building Information Modelling (BIM)

Adoption in the Nigerian Construction Industry. Computing in Civil and Building Engineering (2014): pp. 167-178. doi: 10.1061/9780784413616.022

Ameh, O.J., and Osegbo, E.E. (2011) Study of relationship between time overrun and productivity on construction sites, International Journal of Construction Supply Chain Management 1 (1). Pp 56-67

Barati, B., Charehzehi, A., and Preece,N. A., (2013), Enhancing the Planning and Scheduling Program by Using Benefits of BIM-Based Applications, Civil and Environmental Research 3(5).

Becerik-Gerber, B., and Samara R., 2010, The Perceived Value of Building Information Modeling in the U.S. Building Industry. Journal of Information Technology in Construction 15: 185-201.

Conradi, D., 2009. Building information modeling (BIM). Green building handbook South Africa, 1, pp.225-31.

Flood, I. & Karam, N., 1994. Neural networks in civil engineering. I: principles and understanding. Journal of Computing in Civil Engineering, 8(2), p. 131–148.

Abubakar, M., Ibrahim, Y., Kado, D., and Bala, K. (2014) Contractors' Perception of the Factors Affecting Building Information Modelling (BIM)

Adoption in the Nigerian Construction Industry. Computing in Civil and Building Engineering (2014): pp. 167-178. doi: 10.1061/9780784413616.022

Ameh, O.J., and Osegbo, E.E. (2011) Study of relationship between time overrun and productivity on construction sites, International Journal of Construction Supply Chain Management 1 (1). Pp 56-67

Barati, B., Charehzehi, A., and Preece,N. A., (2013), Enhancing the Planning and Scheduling Program by Using Benefits of BIM-Based Applications, Civil and Environmental Research 3(5).

Becerik-Gerber, B., and Samara R., 2010, The Perceived Value of Building Information Modeling in the U.S. Building Industry. Journal of Information Technology in Construction 15: 185-201.

Conradi, D., 2009. Building information modeling (BIM). Green building handbook South Africa, 1, pp.225-31.
Flood, I. & Kartam, N., 1994. Neural networks in civil engineering. I: principles and understanding. Journal of Computing in Civil Engineering, 8(2), p. 131–148.

Gharehchopogh, F.S., 2011. Neural Network Application in Software Cost Estimation. International Symposium on Innovations in Intelligent Systems and Applications (INISTA), pp.69-73.
Ji, S.-H., Park, M. & Lee, H.-S., 2012. Case adaptation method of case-based reasoning for construction cost estimation in Korea. Journal of Construction Engineering and Management, 138(1), p. 43–52.

Kumanayake, R.P. & Bandara, R.M.P.S., 2012. Building Information Modelling (BIM); How it Improves Building Performance. Faculty of Engineering General Sir John Kotelawala Defence University, pp.1-13.

Khosrowshahi F., and Arayici, Y., (2012), Roadmap for implementation of BIM in the UK construction industry, Engineering, Construction, and Architectural Management, Vol. 19 Iss 6 pp. 610 – 635

Liua, S. mengb, X., and Tamc, C., (2015), Building information modeling based building design optimization for sustainability, Energy and Buildings, 105 (15). Pages 139–153

Nederveen, V, Beheshti, S. Willems, P.R (2010) Building Information Modelling in the Netherlands; A Status Report. Proceedings of the 18th CIB World Building Congress 2010, 10‐13 May 2010 The Lowry, Salford Quays, United Kingdom 28-40

Pahariya, J.S., V. Ravi, M.C. & Vasu, M., 2010. Computational Intelligence Hybrids Applied to Software Cost Estimation. International Journal of Computer Information Systems and Industrial Management Applications, 2, pp.104-12.

Petroutsatou, K., Georgopoulos, E., Lambropoulos, S. & Pantouvakis, J. P., 2012. Early cost estimating of road tunnel construction using neural networks. Journal of Construction Engineering and Management, 138(6), p. 679–687.

Rogalska, W., 2008. Time/cost optimization using a hybrid evolutionary algorithm in construction project scheduling. Automation in Construction, 18(1), pp. 24-31.

Shane, J. S., Molenaar, K. R., Anderson, S. & Schexnayder, C., 2009. Construction project cost escalation factors. Journal of Management in Engineering, 25(4), p. 221–229.

Succar, B. Sher, W and Williams, A (2012) Measuring BIM Performance: Five Metrics. Journal of Architectural Engineering and Design Management. 8:2, 120-142

Wong, Kam‐din and Fan Qing (2013) "Building information modeling (BIM) for sustainable building design," Facilities, Vol. 31 Iss: 3/4, pp.138 – 157

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