A large tunnel construction project used two Tunnel Boring Machines (TBMs) approaching each other from either side of a hill. Sources of uncertainty included tunnelling & supply chain productivity rates and the existence of caverns and rock fissures that would require costly and timely remediation. Greater than anticipated presence of flint and gravel in the ground would damage the cutters and lead to unplanned maintenance of TBMs.
An additional complication was that all excavated material had to be moved to the south side of the tunnel. Due to the uncertainties mentioned above it was not known at which point the two TBMs would meet. If closer to the south entrance then the majority of the spoil would have to be first moved to the north then moved south through the tunnel once it was complete. This ‘double handling’ would delay the project and increase cost, particularly if it was undertaken during winter when the earth would be wetter and harder to move.
Data for the analysis was gathered through briefings and one-to- one meetings with experts from the different disciplines on the project. The forecast was produced by combining Monte Carlo models. One was a Gantt/Network based forecast of the overall project schedule using off the shelf software (Pertmaster/Oracle Prmavera Risk Analysis). The model to forecast the meeting point of the two TBMs was created in Microsoft Excel and required development of a bespoke Visual Basic / VBA script. Supply chain productivity was forecast using an Excel model in conjunction with Palisade @Risk.
The first pass of the model was focused on time and schedule. The model was then ‘cost loaded’ to provide an integrated cost and schedule analysis. This gave better insight into how schedule variability drove the project costs.