Case Studies, Netrisk

The PMA-sponsored team of engineering students at The University of Michigan presented their research project focusing on schedule risk analysis as a quantitative technique to better predict schedule performance. Schedule risk analysis is a tool used in combination with the project schedule to help a project finish on time and on budget. The team studied the effect of float use on project results during Monte Carlo simulation.

For this investigation, a generic schedule at two different levels of detail was used to compare the differences in the probabilistic completion dates. The researchers used PMA’s NetRisk software to carry out the analysis.

Watch the video presentation of findings:

Phase 1

In phase 1 of the project, three types of simulations were run where float consumption was varied. The three types of simulations that were run were optimistic (no float use), realistic (varied float use), and pessimistic (all float used).

Phase 2

In phase 2, the summary activities were correlated to the corresponding detailed schedule activities, resulting in a revised detailed schedule that was reanalyzed by the three simulation scenarios.


The results for all three floating simulations indicated that the detailed schedules for phase 1 and phase 2 have later probabilistic completion dates than the summary schedule. This observation demonstrates that, as a schedule becomes more detailed, the estimated project completion date is later.

Researchers additionally observed that when floating was applied and as the level of certainty in the completion date increased, the difference in completion dates between the summary and detailed schedules also increased. This demonstrates the significant impact float can potentially have on a project’s final completion date.

The other major observation was that the correlated detailed schedule (phase 2) and uncorrelated detailed schedule (phase 1) had no proven difference in the completion date. This tends to indicate that correlation has almost no effect on a project’s completion date.

Research Team

Xinyao Zhang, MS

Xinyao is a MSc student of Civil and Environmental Engineering at the University of Michigan. She earned her bachelors’ degree in Civil Engineering and Management from Chang’an University.

Dariya Protcheva, MEng

Dariya is a MEng student at the University of Michigan. She has experience in project management, estimation, cost management, and contract management.

Weixi Li, MEng

Weixi is a MEng student of Construction Management at the University of Michigan. He earned his bachelors’ degree in Civil Engineering from the University of Iowa.

Sara Freid, MEng

Sara recently completed her master’s degree in Construction Engineering and Management from the University of Michigan.

Professor SangHyun Lee

SangHyun is leading the Dynamic Project Management (DPM) Group at the University of Michigan that aims to understand and manage construction dynamics and human infrastructure interface through sensing, data analytics and computer simulation. Particularly, DPM is interested in achieving the maximum benefit from technologies like wearables, automation, and robotics for humans in construction and infrastructure. DPM also applies these technologies to direct smart and connected communities and cities toward social equality.

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