Sergios Lambropoulos

Critical path determination by incorporating minimum and maximum time and distance constraints into linear scheduling

A scheduling method for determining the critical path in linear projects is presented, that takes into account maximum time and distance constraints in addition to the commonly used minimum time and distance constraints. The maximum constraints, though often present in the specifications of a project, are not considered during the planning procedure, since no method existed to enable scheduling with them. The proposed method builds on the concept of the maximum constraints and expands on the necessary background for their implementation into the schedule. The introduced critical path algorithm allows for grouping linear activities into four categories regarding their critical status and their ability to influence project duration. The method is applied to a low‐pressure pipeline construction project and the results are presented.

Parametric Model for Conceptual Cost Estimation of Concrete Bridge Foundations

Motorway bridges constitute a major part of modern transportation infrastructure networks. Interestingly, although foundations substantially influence the bridge construction cost, few studies have focused on predesign cost estimates. This paper presents a conceptual cost-estimate model for bridge foundations that involves three stages: the selection of the foundation system, the estimation of the material quantities, and the estimation of the foundation cost. It describes an easy-to-use ground classification method, which combined with a rule-based system, leads to the choice of the foundation system. This paper also describes the development of prediction models for the material quantities of different types of foundations. The significant independent variables were identified by the experts in interview sessions. Despite its drawbacks, the stepwise regression methodology was applied to see whether the results are consistent with the experts’ opinion. The major assumptions underlying the correct application of the regression methodology were tested, and the necessary adjustments were made. The proposed conceptual cost-estimating methodology provides fast and reliable results that can be very useful in the early stages of a project.

Road tunnel early cost estimates using multiple regression analysis

Among construction projects, the risk in the production of road tunnels is particularly high due to the inherit uncertainties of the underground conditions. Equally, tunnel costs are considerably higher as compared to those of normal surface roads. As published literature on early cost estimating tools for road tunnels is scarce, projects sponsors, decision makers and engineers lack reliable tools, especially during the important early conceptual and preliminary design stages, to establish the project budget. The problem is addressed in this paper aiming at developing early parametric estimating models for road tunnels based upon the application of multiple regression analysis on real-world constructed projects. Thirty-three road tunnels totaling forty-six Km in single bore length constructed for the Egnatia motorway in northern Greece were analyzed for this purpose. To do so, data related to the encountered geotechnical parameters of rock masses and the corresponding quantities of primary and permanent support were gathered and put into a database. This database coupled with statistical techniques was subsequently used to establish the correlation between geotechnical and construction parameters. Following this stage, tests were performed to validate the correlations produced. The analysis highlighted the most important parameters affecting construction cost. It can be corroborated therefore that the approach employed in this work is valid for heavy construction projects and, furthermore, contributes to the long lasting problem of obtaining valid data to produce reliable early cost estimates for road tunnel construction.

Road tunnels construction cost estimation: a structural equation model development and comparison

Sound understanding of technical projects performance is very important at the preliminary design phase. A crucial element in the decision-making process for selection of the best alternative solution is reliable, early cost estimates. This becomes particularly significant in road tunnel construction where the construction cost is expressively high and subject to considerable cost overruns due to inherit risks of underground conditions. In this paper a structural equation model (SEM) for estimating the final construction cost of road tunnels is developed. In a comparative analysis of SEM with multiple regression analysis (MRA) and neural networks (NNs), SEM offers better results allowing the user to visually depict the paths of how several variables affect the cost of an underground project.

A Computer-Aided Conceptual Cost Estimating System for Pre-Stressed Concrete Road Bridges

The need for an environmentally friendly design of modern motorways increases the construction of bridges, which has exhibited substantial overruns above estimated costs. Therefore, easy to use, inexpensive and accurate methods for conceptual cost estimating are needed. This paper presents a computer-aided cost estimating system for pre-stressed concrete road bridges that provides estimates of the material quantities and cost of all bridge elements. It relies on a database incorporating actual data collected from recently constructed bridges and exploits material estimating models developed with statistical analysis. Different configurations are devised from short to long-span bridges, accounting for the major deck construction methods and foundation systems. The system can be easily used to provide different cost estimates to the owner, designer and contractor during the projects early stages. By allowing reliable cost estimates in a short time, the proposed computer-aided system represents a useful decision making tool.

Correspondence of activity relationships and critical path between time-location diagrams and CPM

Various methods for identifying the critical path in linear schedules have been proposed over the last years. Work done in comparing these methods has shown that in many activity configurations, their results do not coincide. This paper attempts a critical path comparison between the linear scheduling method KLRPM, developed by the authors, and the network scheduling method CPM. In order to achieve this comparison, a correspondence between activity relationships of the CPM and the KLRPM is established first. The results of the two methods are then tested for some simple activity configurations and applied on an illustrative example taken from the literature. The results are commented and recommendations for further research are proposed.

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 models 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’...

An Integrated Information System for Monitoring Construction Works

There is a global tendency towards implementing centralized project monitoring with the use of advanced information systems in large projects. This trend is mandated by issues such as the geographical dispersion of projects, the number of contractors and the total amount of works. In this respect, the integrated information system that has been utilized to monitor the construction works of the Egnatia Motorway project in Greece is presented. Reference is made to the software, hardware, information technology architecture, quality procedures and personnel training for the successful implementation of the system. Special mention is made to the data structures that are utilised (enterprise project structure, organizational breakdown structure, resource breakdown structure, and work breakdown structure). In addition, comments are made from the experiences drawn from the implementation of the system. Overall, it is concluded that the integrated system constitutes a central focal point for corporate scheduling and cost control.

Investigation of earthmoving trucks deterioration using Discriminant Analysis

Earthmoving equipment has a determinant role in the successful realisation of most civil engineering projects. However, it may suffer significant downtime due to the continuous and intense use in harsh working conditions. This downtime may be associated with certain deterioration parameters, which if known, would allow more accurate estimations to be made. For this purpose, the data sets from two large Greek construction companies containing the characteristics of 126 earthmoving trucks (capacity, age, kilometres travelled to date, maintenance class and condition level) have been analysed using discriminant analysis. The analysis allows for the assessment of the connection of each characteristic with the condition level of the sample trucks and also leads to rules that can be used for the prediction of the condition level of other trucks.

Algorithmic method for scraper load-time optimization

AbstractScrapers have established an important position in the earthmoving field as they are independently capable of accomplishing an earthmoving operation. Given that loading a scraper to its capacity does not entail its maximum production, optimizing the scraper’s loading time is an essential prerequisite for successful operations management. The relevant literature addresses the loading time optimization through a graphical method that is founded on the invalid assumption that the hauling time is independent of the load time. To correct this, a new algorithmic optimization method that incorporates the golden section search and the bisection algorithm is proposed. Comparison of the results derived from the proposed and the existing method demonstrates that the latter entails the systematic needless prolongation of the loading stage thus resulting in reduced hourly production and increased cost. Therefore, the proposed method achieves an improved modeling of scraper earthmoving operations and contribute...