Modeling construction time in Spanish building projects

The literature states that project duration is affected by various scope factors. Using 168 building projects carried out in Spain, this paper uses the multiple regression analysis to develop a forecast model that allows estimating project duration of new builds. The proposed model uses project type, gross floor area (GFA), the cost/GFA relationship and number of floors as predictor variables. The research identified the logarithmic form of construction speed as the most appropriate response variable. GFA has greater influence than cost on project duration but both factors are necessary to achieve a forecast model with the highest accuracy. We developed an analysis to verify the stability of forecasted values and showed how a model with high values of fit and accuracy may display an anomalous behavior in the forecasted values. The sensitivity of the proposed forecast model was also analyzed versus the variability of construction costs.

Excavated housing in Crevillente (Spain). Constructive and typologycal study

Underground architecture has sheltered man for many centuries, but the current need to emphasize the bioclimatic approach makes the study of excavated housing essential. This traditional construction is a part of the collective human living experience but also a reference in using the natural conditions of each region through simple proposals based on ground thermal inertia. The aim of this paper is to show the typological evolution of the excavated dwelling in Crevillente, in southeast Spain, compared to other worldwide architectural proposals or urban solutions. To show their adaptation to the regional geography and to comprehend both formal and material characteristics of these simple typologies, which do not need extra energy contribution for interior conditioning. This work is part of the doctoral thesis of the author.

Implementation Feasibility of a Digital Nervous System for the Construction Industry: For Efficient and Effective Information Management across the Project Lifecycle

The construction industry has long been considered as highly fragmented and non-collaborative industry. This fragmentation sprouted from complex and unstructured traditional coordination processes and information exchanges amongst all parties involved in a construction project. This nature coupled with risk and uncertainty has pushed clients and their supply chain to search for new ways of improving their business process to deliver better quality and high performing product. This research will closely investigate the need to implement a Digital Nervous System (DNS), analogous to a biological nervous system, on the flow and management of digital information across the project lifecycle. This will be through direct examination of the key processes and information produced in a construction project and how a DNS can provide a well-integrated flow of digital information throughout the project lifecycle. This research will also investigate how a DNS can create a tight digital feedback loop that enables the organisation to sense, react and adapt to changing project conditions. A Digital Nervous System is a digital infrastructure that provides a well-integrated flow of digital information to the right part of the organisation at the right time. It provides the organisation with the relevant and up-to-date information it needs, for critical project issues, to aid in near real-time decision-making. Previous literature review and survey questionnaires were used in this research to collect and analyse data about information management problems of the industry – e.g. disruption and discontinuity of digital information flow due to interoperability issues, disintegration/fragmentation of the adopted digital solutions and paper-based transactions. Results analysis revealed efficient and effective information management requires the creation and implementation of a DNS.

Intelligent Decision-Making System Frameworks for a Digital Plan of Work: A Theoretical Investigation for the Construction Industry

The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.

The Impact of BIM on the Distribution of Cost and Return on Investment in UK Construction Projects

It has been widely documented that when Building Information Modelling (BIM) is used, there is a shift in effort to the design phase. Little investigation into the impact of this shift in effort has been done and how it impacts on costs. It can be difficult to justify the increased expenditure on BIM in a market that is heavily driven by costs. There are currently studies attempting to quantify the return on investment (ROI) for BIM for which these returns can be seen to balance out the shift in efforts and costs to the design phase. The studies however quantify the ROI based on the individual stakeholder’s investment without consideration for the impact that the use of BIM from their project partners may have on their own profitability. In this study, a questionnaire investigated opinions and experience of construction professionals, representing clients, consultants, designers and contractors, to determine fluctuations in costs by their magnitude and when they occur. These factors were examined more closely by interviewing senior members representing each of the stakeholder categories and comparing their experience in using BIM within environments where their project partners were also using BIM and when they were not. This determined the differences in how the use and the investment in BIM impacts on others and how costs are redistributed. This redistribution is not just through time but also between stakeholders and categories of costs. Some of these cost fluctuations and how the cost of BIM is currently financed are also highlighted in several case studies. The results show that the current distribution of costs set for traditional 2D delivery is hindering the potential success of BIM. There is also evidence that stakeholders who don’t use BIM may benefit financially from the BIM use of others and that collaborative BIM is significantly different to the use of ‘lonely’ BIM in terms of benefits and profitability.