Simulation applications in construction-project management are primarily limited to academic research. Where simulation has been used in project risk assessment in the industry, it has not been used to its potential. This research addresses two problems: the difficulty associated with using simulation, and the lack of project risk models that correctly reflect the risk identification assumptions.
Surveys show that facilitating the modelling process and reducing programming efforts are the most important factors in increasing the appeal to simulation. Large models are impractical for standalone computers. Simulation methodologies serving construction projects are built around the cyclic operations that do not support seamless data transfer between the models and the data storage media. Project management systems are data driven where data are updated regularly, making it difficult to simultaneously keep models current.
Project risk management attempts to increase the chances of achieving project objectives; however, simulation-based risk-assessment models use range estimates that do not reflect the causal relationship between the risk events and the objectives’ outcomes. The literature on risk assessment recommends integration between risk-assessment tools and those of cost and schedule management. However, current simulation-based risk-assessment applications are standalone models built around the independent creation of random numbers that do not support integration within the project or within a portfolio of projects.
This research has two objectives: increasing the appeal of simulations and facilitating the modeling process, and measuring project risks in an integrated environment. The researcher identified criteria that improve current simulation methodologies and simulation-based risk assessment methods, and developed the computer applications that incorporate these criteria. The simulation methodology provides a user-friendly interface with a built-in code generation and database integration for standalone and distributed models. The risk assessment framework allows the effects of risks on projects and portfolio objectives to be measured in an integrated environment. The risk assessment model was used by graduate students at the University of Calgary as part of the verification and validation process. Feedback from students confirmed that the simulation methodology increases the appeal to simulation and that calculating risk effects using the proposed framework produces better risk assessment than range estimate