Construction Management and Economics (1998) 16, 41-48
Estimating project and activity duration: a risk management approach using network analysis
NASHWAN DAWOOD
Division of Civil Engineering and Building, School of Science and Technology, The University of Teesside, Middlesborough TS! 3BA, UK
Received 21 December 1995; accepted 14 August 1997
Variations in the durations of activities are commonplace in the construction industry. This is due to the fact that the construction industry is influenced greatly by variations in weather, productivity of labour and plant, and quality of materials. Stochastic network analysis has been used by previous researchers to model variations in activities and produce more effective and reliable project duration estimates. A number of tech-niques have been developed in previous literature to solve the uncertain nature of networks, these are: PERT (program evaluation and review techniques), PNET (probabilistic network evaluation technique), NRB, (narrow reliability bounds methods) and MCS (Monte Carlo simulation). Although these techniques have proved to be useful in modelling variations in activities, dependence of activity duration is not considered. This can have a severe impact on realistically modelling projects. In this context, the objective of the present research is to develop a methodology that can accurately model activity dependence and realistically predict project duration using a risk management approach. A simulation model has been developed to encapsulate the methodology and run experimental work. In order to achieve this, the following tasks are tackled: iden-tify risk factors that cause activity variations using literature reviews and conducting interviews with contrac-tors; model risk factors and their influence on activity variations through conducting case studies and identifying any dependence between them; develop a computer based simulation model that uses a modi-fied Monte Carlo technique to model activity duration and dependence of risk factors; and run experimental work to validate and verify the model,
Keywords: Network analysis, Monte Carlo simulation, PERT, stochastic analysis
Background
Uncertainty in network analysis has been used by pre-vious researchers in an attempt to model activity dura-tion variations more accurately and produce more effective and reliable project duration estimates. Variations of activity duration do occur due to the expo-sure of construction projects to numerous uncontrol-lable risk factors. Several probabilistic methods have been developed to solve the problem of uncertainty in network analysis. Amongst these methods are (Illumoka, 1987; Chapman, 1990): PERT (program evaluation and review technique), PNET (probabilistic network evaluation technique), NRA (narrow reliability
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bounds), and MCS (Monte Carlo simulation). Diaz and Hadipriono (1993) found that PERT is the simplest method and yields the most optimistic results, while MCS produces the most conservative results. They used several types of network and the evaluation is based on survival function and computer time. Ranasinghe (1994) has introduced an equation to model the uncer-tainty in activity duration, and developed a quantifica-tion for uncertainty in project duration. The research in the area of uncertainty in network analysis which has been developed over the last decade has refined the techniques used; however, a number of problems still exist. Uncertainty in analysis is applied with survival of the project in mind, rather than