conference paper
Maintaining project schedules in the face of uncertainties is vital for successful delivery in construction. Developing baseline schedules that inherently withstand disruptions offers a practical solution, yet reliable metrics for measuring schedule resilience have been lacking. A data-driven pattern analysis method establishes a preliminary baseline schedule relative resilience index, designed to quantify a schedule's inherent capacity to absorb perturbations. The approach identifies key scheduling factors from existing literature, gathers empirical data and actual delay records from real construction projects, and applies multiple linear regression alongside leave-one-out cross-validation. Findings reveal that characteristics such as activity floats and network topology substantially affect schedule resilience. The resulting index provides project teams with an empirical, quantitative benchmark to evaluate and improve the robustness of construction schedules.
Delays in construction projects often result in severe cost overruns and disputes. Providing project planners with an objective, data-driven way to measure schedule resilience helps teams identify structural schedule vulnerabilities early. By designing more robust timelines from the outset, organisations can better absorb unforeseen disruptions, keep projects on track, and mitigate financial and contractual risks associated with project delays.
The index could potentially be integrated into commercial project planning software for construction planners, contractors, and project management firms seeking to assess scheduling vulnerabilities. As the model is presented as a preliminary index developed and tested on historical project data, it currently sits at an applied research stage, requiring further refinement and testing on broader project datasets before practical adoption.
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In the construction industry, the ability to maintain project schedules despite uncertainties is crucial for successful project delivery. This can be achieved by developing baseline schedules that are inherently resilient to changes. Nevertheless, the current body of knowledge does not have a well-established resilience index for construction project schedules. To this end, this paper presents a data-driven pattern analysis approach to develop a preliminary baseline schedule relative resilience index (BSRI) that evaluates the schedule’s inherent ability to absorb perturbation. The research follows a three-step methodology: (1) identify common factors that describe resilience scheduling based on a literature review; (2) collect data from real construction projects capturing the identified factors and actual delays; and (3) develop preliminary BSRI based on statistical analysis of the collected data via multiple linear regression analysis and leave-one-out cross-validation (LOO-CV) to evaluate the model’s performance. Results highlight potential factors such as activity floats and network topology, which significantly influence schedule resilience. The proposed Preliminary BSRI provides a quantitative measure that is based on historical data to assess and enhance the resilience of construction project schedules.
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DOI: 10.1061/9780784486986.081
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