BUILDING INFORMATION MODELLING AND MONTE CARLO SIMULATION APPLICATION: ENHANCEMENT MITIGATING RISK OF CONTRACTOR'S SELECTION IN THE CONSTRUCTION PROJECT

• Published in: Planning Malaysia
• Main Author: Halil F.M.; Azman M.A.; Sekak S.N.A.A.; Nasir N.M.; Romeli N.S.
• Format: Article
• Language: English
• Published: Malaysian Institute Of Planners 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210922495&doi=10.21837%2fpm.v22i34.1621&partnerID=40&md5=87b975d28891552864b33483f122064d

Low-bid selection can significantly impact construction delivery, leading to delays, substandard quality, and cost overruns if pricing risks are not considered. This research, however, provides a solution that empowers Quantity Surveyors (QS) to act. They can implement BIM to ensure the accuracy of the prepared pretender estimate. Furthermore, the application of Monte Carlo (MC) simulation, using probability distribution, can provide a range of tender prices that can be accepted by the client, thereby mitigating the risk of pricing error by the contractor. As demonstrated in this research, the combination of BIM and MC simulation offers a powerful tool for the construction industry. A case study method through document analysis has been chosen to investigate the patterns of tender prices the bidders offer for a bridge construction project. Then, using a pre-tender estimate as a starting point, MC simulates thousands of probable tender prices in a random sequence based on normal distribution. The outcomes indicate that the clients could avoid the high risk of choosing a contractor based on the lowest tender price in a construction project by using Monte Carlo. Therefore, the research shows that applications of Building Information Modelling and Monte Carlo simulation are not just beneficial but crucial for judgment for clients in the construction industry, and it is up to the stakeholders to implement these findings. © 2024 by MIP.