Construction completion forecasting on the basis of statistical modeling and heterogeneous monitoring data

Abstract

Modern construction represents a complex production process whose effective regulation is based on information about the period of construction works, obtained by way of monitoring. Any delay in the execution of certain works frustrates scheduled project commissioning, which results in increased project management costs, forfeits and lost benefits. Existing monitoring systems need to be improved through the use of probabilistic scheduling geared towards the forecasting of completion dates of certain works and the construction process as a whole. Construction monitoring may be improved by means of taking management quality into account by means of distributing random work durations in the process of statistical modeling of functions. The introduction of six random duration distribution functions, reflecting management quality, is proposed for the improvement of statistical modeling, whereas the use of scheduled durations of works is expedient for identifying optimistic characteristics. The data, extracted from monitoring reports, needs to be used as pessimistic distributions. Monitoring reports contain heterogeneous data, and they may even have no information on particular types of works. Therefore, pessimistic durations based on missing data should be calculated using the time-space analogy method.