Abstract
In this article, we present our own construction process model consisting of 16 stages and eight phases, which is particularly applicable to large investment projects. In the context of each project phase, we examine how the appropriate way of scheduling construction processes affects the problem of the risk of prolonging individual phases and the whole project, as well as of not meeting deadlines (which is one of the main problems faced by management practitioners in the construction industry). There are many methods for assessing risk in this context, but they tend to be overly complex and rarely used by construction practitioners. On the other hand, the risks associated with potential schedule delays can be considered holistically. One tool that can serve this purpose is the combined Monte Carlo simulation and Time-at-Risk (TaR) approach, which originates from the world of finance. We show how the implementation of the process model (individual phases) and the whole project can be considered in the context of the covariance matrix between all its phases and how changes in the arrangement of these phases can affect the risk of time extension of the whole project. Our study is based on simulation data for a large development project (Fort Bema/Parkowo-Leśne housing estate complex) in Bemowo, a district of Warsaw, carried out between 1999 and 2012. The entire investment project involved the construction of almost 120,000 m2 of floor space.
Highlights
Time uncertainty is ubiquitous in all disciplines of project planning and scheduling, yet in the construction industry it is of particular importance [1,2,3,4,5,6]
Triangular distributions can be assumed instead of programme evaluation and review technique (PERT) distributions for short phases such as the realisation of the opportunity study (OS) or for the conceptual phase (CONC), while Weibull distributions can be used for the other longer implementation stages, as they are inherently characterised by fat tails on the right side of their distributions [67,86]
The paper presents a practical application of the combined Monte Carlo and Time-atRisk (TaR) methods, which, under certain assumptions, can be used to estimate the risks associated with scheduling a construction project conducted in conditions of uncertainty
Summary
Time uncertainty is ubiquitous in all disciplines of project planning and scheduling, yet in the construction industry it is of particular importance [1,2,3,4,5,6]. Among the methods used for project scheduling, the best known (and most commonly used) are the critical path method (CPM) [11,12] and the programme evaluation and review technique (PERT) [10] These methods are based on the determination of minimum times assigned to individual tasks/activities of the project, without which its realisation is not possible. These methods lack the adequacy to model complex logic and resource constraints in a construction process [13,14,15,16,17,18,19] This form of scheduling seems to be unsatisfactory for construction projects, where exceeding completion dates carries heavy penalties [9]. The application of CCPM leads to a reduction in indirect costs due to shorter project implementation times and a reduction in direct costs as a result of better allocation of resources and ensuring their timely availability
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