A cost estimate method for bridge superstructures using regression analysis and bootstrap

Preliminary cost estimates rely on the conceptual design of the project and use only basic design technologies. Although they present the lowest expected accuracy, they are often used by key people involved in the construction process, thus playing a significant role. Bridge construction has increased over the last years, often exhibiting substantial overruns above estimated costs. To overcome this problem, it is crucial for the decision makers to have an early estimate of the final cost based on previous experience. This paper addresses the need for easy-to-use and reliable cost estimates during the early stages of projects for bridge superstructures, presenting a major impact on the total bridge construction cost. It proposes a conceptual cost estimate method that involves the estimation of both the material quantities and the relevant costs. It describes the development of prediction models for the material quantities of concrete and reinforcing and prestressing steel for three major bridge deck construction methods using regression analysis, while a bootstrap resampling method is used to produce estimate ranges. The material estimating models rely on the development of a database after collecting actual data from a large sample of modern bridges. The major assumptions underlying the correct application of the regression methodology were tested, and necessary adjustments were made. The proposed conceptual cost-estimating methodology uses information known before detailed plans are developed to provide fast and reliable results that can be very useful in the early stages of a road project

Earth loading and hauling optimal trade-off

AbstractIn loading and hauling of earth with loader and trucks, it is reasonable to expect that the truck's capacity (either gravimetric or volumetric) is not a whole multiple of the loader's bucket volume. Therefore, the truck's maximum exploitation requires a partially filled pass, which inevitably prevents the loader from achieving its maximum performance. This research investigates the cost implications that the above loading and hauling trade-off involves for the fleet and introduces a method for the selection of the most expedient Loading Practice

Reforming civil engineering studies in recession times

AbstractThe recent global economic and financial crisis has led the economies of many countries into recession, in particular at the periphery of the European Union. These countries currently face a significant contraction of both public investment in infrastructure and private investment in buildings and, as a result, the unemployment is particularly noticeable in the civil engineering and building sectors. Consequently, in all countries in recession the professional development of fresh civil engineering graduates is disproportionate to their high study effort and qualifications, since they rarely have the opportunity to gain experience in practice and their knowledge gradually becomes obsolete. Under these circumstances, it is imperative for the technical universities in countries in recession to plan and implement a substantial reform of the civil engineering studies syllabus. The objective should be to enable graduates to broaden the scope of their professional activity and increase their employability.In this paper, the widening of civil engineering studies curricula is proposed, in particular in the light of the development of the graduates’ potential on project, programme and portfolio management. In this direction, after a thorough literature review, including ASCE's Body of Knowledge for the 21st century and IPMA's Competence Baseline, it is recommended among others: to increase significantly the offered modules on project management and add new modules on strategy management, leadership behavior, delivery management, organization and environment etc; to provide adequate professional training during the university studies five year period; and to promote fresh graduates’ certification by professional bodies. The proposals are exemplified by presenting a reformed syllabus for the civil engineering studies offered currently by the National Technical University of Athens

Preliminary cost estimate model for culverts

AbstractThe construction of modern high-speed motorways has increased over the last decade all over the world. However, the financial crisis led many financial institutions worldwide to impose stricter credit limitations and seek to finance only high-profit investments. As a result, the financing of transport projects was made even more difficult. At the same time, accurate cost estimates at the preliminary stages of a project are essential to all the major project stakeholders, since they are necessary for the budget determination, allocation and monitoring, the comparison of alternative projects and technical solutions and finally, the selection of the projects to be implemented. However, the degree of accuracy required is very difficult to be achieved at the preliminary stages due to the limited extent of available information.This paper presents a preliminary predesign cost estimate model for culverts i.e. conduits for the passage of surface drainage water under the motorway. Although individual culverts present low construction cost when compared to bridges, tunnels or large retaining walls, their total number along a motorway is significant and thus, their total construction cost is also substantial. The proposed model utilizes a properly developed database derived from actual construction projects to produce accurate quantity estimates by means of the statistical technique of linear regression. Following the estimation of quantities, proper material unit prices are applied for quick and reliable cost estimates to be provided. The proposed model only requires limited input and thus, can be used in the early project stages, offering valuable contribution towards the accurate culverts’ cost prediction in motorway projects

Earthmoving trucks condition level prediction using neural networks

Purpose: The purpose of this paper is to present an artificial neural network (ANN) model that predicts earthmoving trucks condition level using simple predictors; the model’s performance is compared to the respective predictive accuracy of the statistical method of discriminant analysis (DA).Design/methodology/approach: An ANN-based predictive model is developed. The condition level predictors selected are the capacity, age, kilometers travelled and maintenance level. The relevant data set was provided by two Greek construction companies and includes the characteristics of 126 earthmoving trucks.Findings: Data processing identifies a particularly strong connection of kilometers travelled and maintenance level with the earthmoving trucks condition level. Moreover, the validation process reveals that the predictive efficiency of the proposed ANN model is very high. Similar findings emerge from the application of DA to the same data set using the same predictors.Originality/value: Earthmoving trucks’ sound condition level prediction reduces downtime and its adverse impact on earthmoving duration and cost, while also enhancing the maintenance and replacement policies effectiveness. This research proves that a sound condition level prediction for earthmoving trucks is achievable through the utilization of easy to collect data and provides a comparative evaluation of the results of two widely applied predictive methods