Mid-Rise Commercial Building Construction Project

A realistic example project used to illustrate the full PRA workflow: schedule/cost uncertainty, earned value management, Bayesian risk inference, and dependency structure analysis. The project comprises six work packages for a mid-rise commercial building. The structure and parameter ranges are adapted from the illustrative construction-project examples in Damnjanovic and Reinschmidt (2020), the reference text this package operationalizes; the values are representative estimates for a project of this type rather than proprietary data from a specific project.

Usage

building_project

Format

A named list with the following components:

task_names

Character vector of the six work-package names.

task_distributions

List of six triangular duration distributions (weeks), each a list with type = "triangular" and a (optimistic/min), b (most likely/mode), and c (pessimistic/max). Suitable input to mcs() and sensitivity().

cor_mat

6x6 correlation matrix among task durations.

bac

Budget at completion (US dollars).

schedule

Numeric vector of cumulative planned-value fractions.

actual_costs

Numeric vector of per-period actual costs (US dollars).

time_period

Integer current reporting period.

actual_per_complete

Actual fraction of work complete.

cause_names

Character vector of root-cause names for the schedule-delay risk event.

cause_probs

Probabilities that each root cause is present.

risks_given_causes

P(delay | cause present) for each cause.

risks_given_not_causes

P(delay | cause absent) for each cause.

observed_causes

Mid-project observation of each cause (1 = occurred, 0 = did not occur, NA = not yet assessed).

resource_names

Character vector of the six shared resources.

resource_task

Resource-task incidence matrix S (resources x tasks) for parent_dsm() and grandparent_dsm().

risk_names

Character vector of the three structural risks.

risk_resource

Risk-resource incidence matrix R (risks x resources) for grandparent_dsm().

References

Damnjanovic, Ivan, and Kenneth Reinschmidt. Data Analytics for Engineering and Construction Project Risk Management. Cham, Switzerland: Springer, 2020. doi:10.1007/978-3-030-14251-3

Examples

# Monte Carlo schedule risk (tasks treated as independent)
sim <- mcs(10000, building_project$task_distributions)
sim$percentiles
#>       5%      50%      95% 
#> 64.30804 71.60191 79.37655 

# Earned value snapshot at the current period
bp <- building_project
spi(ev(bp$bac, bp$actual_per_complete), pv(bp$bac, bp$schedule, bp$time_period))
#> [1] 0.8888889