Development of Construction Performance Monitoring Methodology using the Bayesian Probabilistic Approach

抄録

Process planning is based on engineers′ experience. This often results in cost overruns and delays. Precise planning based on reliable data is required to avoid these issues. Accurate productivity prediction is one of the most important issues in process planning. However, it has been shown that the process of collecting enough data has severe limitations in terms of time and human resources. Numerous studies have attempted to overcome the difficulties of accurate productivity prediction. This paper proposes a methodology for monitoring construction projects by implementing a database that is developed using the Bayesian posterior-probabilistic method. This method is considered to be appropriate in civil engineering because it provides reliable probabilities by presenting updated results based on continuously collected data rather than focusing on a one-time observation and associated analysis. This paper focuses on high-rise, curtain wall operations as an example for database implementation and Bayesian application. The results obtained using the Bayesian method illustrate appropriate convergence to specific mean values with small variances of standard deviations. This result shows that a Bayesian probabilistic approach can be utilized in civil engineering, to provide more accurate prediction results based on updated information.