Search results

A review of techniques used in industry showed that there is an absence of a formalised, systematic approach to earthworks planning. The techniques used tend to be subjective and time consuming with a heavy reliance given to the experience and knowledge of the planner. This absence of a formalised technique can lead to inaccurate planning and makes explanation of the techniques difficult. This paper describes the development of a new automated approach for use by the planners to generate earthworks activities that overcomes such limitations. As well as creating activity sets in a much shorter time, the ability to compare various sets allows the planner more scope when planning earthworks. The model is able to generate activity sets that are comparable to those generated by a project planner.

This paper describes the development and initial use of a management game to teach project planning and control. It covers all aspects of the game including its design, the choice of the project to be modelled, the user interface and how it makes use of the computer power available. The sections on the use of the game describe experience gained in its use as part of an undergraduate course and as a demonstration on a course run for industry. Both the design and the use of the game are critically assessed and suggestions for improvement are made. The game was produced as a result of international collaboration between British and Dutch academics with input, where appropriate from construction companies of both nations.

Disputes frequently occur on engineering and construction projects. In this paper it is argued that these disputes need to be evaluated and managed, with proper attention being paid to planning of time and money. Since the way in which dispute management is approached will depend on the perceived self‐interest of the parties, it is imperative that disputants have a sensible measure of their self‐interest. ‘Traditional’ probabilistic risk assessment techniques are shown to be of assistance and can be used to compute appropriate dispute management strategies. By way of example, a Monte Carlo simulation of a dispute is performed and discussed.

Errors occur everywhere and research into inaccuracy has become an important area of study. Managers make errors, and the effects include poor safety, reduced quality, increased cost and decreased profit. Despite this, management errors have received almost no study. The present paper contains a review of the definition and causes of human errors, and discusses the applicability of these factors to managers and the effect of time pressure on decision making. The concept of management errors is proposed and a network‐based project model is developed. This approach is used to simulate the occurrence of activity‐based errors, and to determine the influence of pressure on management and the effects of inaccuracies on the project duration.

Several different simulation techniques, such as discrete event simulation (DES), system dynamics (SD) and agent-based modelling (ABM), have been used to model complex construction systems such as construction processes and project management practices; however, these techniques do not take into account the subjective uncertainties that exist in many construction systems. Integrating fuzzy logic with simulation techniques enhances the capabilities of those simulation techniques, and the resultant fuzzy simulation models are then capable of handling subjective uncertainties in complex construction systems. The objectives of this chapter are to show how to integrate fuzzy logic and simulation techniques in construction modelling and to provide methodologies for the development of fuzzy simulation models in construction. In this chapter, an overview of simulation techniques that are used in construction is presented. Next, the advancements that have been made by integrating fuzzy logic and simulation techniques are introduced. Methodologies for developing fuzzy simulation models are then proposed. Finally, the process of selecting a suitable simulation technique for each particular aspect of construction modelling is discussed.

This paper describes the integration of various models to provide a realistic decision support system for linear project site layout. Initially, the paper describes an investigation to determine the actual methods currently used by project managers and planners. A review of both techniques adopted by the managers and the knowledge acquisition methods employed are included in the paper. Following this, this paper describes the work done to automate the existing systems. This resulted in a system which has been used in practice and has been shown to be a great help to managers. It is based on the traditional method of mass‐haul diagrams used to determine the earthworks activities. A separate simulation and artificial intelligence model of earthworks are described. This will be extended to model linear projects more realistically than does mass‐haul.

This paper aims to describe work carried out by the authors using simulation games to teach key aspects of construction management to civil engineering students. The use of simulation games for this purpose is well documented but is still not fully accepted. The work described in this paper aims to address this by analysing the use of simulation games as the primary teaching mechanism in a teaching module, Applied Construction Management.

Two simulation games are described along with the software used to manage and monitor their operation. The two games are functionally similar though the construction scenario's represented, 30 m high dam and 7 km of clay lined canal, are quite different. The Applied Construction Management module is detailed, including the instructional design, assessment procedures and operation during its first three years. This is compared with the more traditional use of the simulation games as a coursework element as employed at Curtin University of Technology in Western Australia.

Student performance is tracked during operation of the module, and statistics for each year of teaching are given along with examples of student feedback. Examples of individual student behaviour are used to illustrate behaviour patterns identified during the course of the research. Conclusions and implications for the use of simulation games are provided.

The novelty of this work lies in the acquisition and analysis of quantitative data on performance collected during the learning process. It focuses on the simulation games as the sole source of teaching and the comparison with more traditional use of the games previously provide additional value.

An accurate estimation of project costs is always a great challenge for a construction company, particularly when there is a commitment with the owner to achieve a project at a given price. It is thus essential to develop technical and logistic solutions (TLS) ensuring a good organisation and improving the productivity. These improvements are not yet well assessed because relevant models are not available at the right time. This paper presents a new approach for assessing productivity by using an analytical cost model and indicators widely used to measure the site productivity. A case study is described to validate the cost and indicator model. They can be used in a decision making process consisting of a comparative study of different TLS in order to select, in a predicted term, the TLS ensuring the best productivity. A decision support system for generating different alternatives to be compared is currently under development.

The purpose of this paper is to explore how construction projects should be conceived and how the productivity of the construction industry impacts upon a nation’s wealth.

The approach has been to marshal the extant literature about the construction industry, construction industry productivity and the economic value of the built environment. Whilst there are many lenses that are used to understand the industry, different ways to measure productivity performance and differing practices between nations, it has been determined that construction industry productivity improvement significantly lags behind other industries.

There is a strong argument that construction productivity improvement correlates to advances in a nation’s economy. Nonetheless, it is the decisions about the nature of infrastructure, the standardisation of infrastructure and the effect upon labour productivity that will have the greatest implications for a nation’s economic future. These economic improvements will be inhibited by legacy infrastructure, particularly in densely populated areas. If substantial innovation occurs, the nations currently holding the highest stock of infrastructure might be economically constrained.

The construction industry is highly fragmented and has the uncertainties of a cyclic industry. It is, therefore, necessary for governments to identify standards and facilitate innovation. The implications for short- and long-term economic performance require that the industry is a fundamental at the highest level of government.

Scholars can use the propositions to further analyse construction productivity improvement and the provision of different types of infrastructure with regard to a nation’s economic performance. Hypotheses are offered to support future research.

The application of an artificial neural network (ANN) to forecast the construction duration of buildings at the predesign stage is described in this paper. A three‐layered back‐propagation (BP) network consisting of 11 input nodes has been constructed. Ten binary input nodes represent basic information on building features (i.e. building function, structural system, foundation, height, exterior finishing, quality of interior decorating, and accessibility to the site), and one real‐value input represents functional area. The input nodes are fully connected to one output node through hidden nodes. The network was implemented on a Pentium‐150 based microcomputer using a neurocomputer program written in C+ +. The Generalized Delta Rule (GDR) was used as learning algorithm. One hundred and thirty‐six buildings built during the period 1987–95 in the Greater Bangkok area were used for training and testing the network. The determination of the optimum number of hidden nodes, learning rate, and momentum were based on trial‐and‐error. The best network was found to consist of six hidden nodes, with a learning rate of 0.6, and null momentum. It was trained for 44700 epochs within 943 s such that the mean squared error (judgement) of training and test samples were reduced to 1.17 × 10−7 and 3.10 × 10−6, respectively. The network can forecast construction du‐ration at the predesign stage with an average error of 13.6%.