Automated planning and coordination of construction machinery complexes in a changing production environment

Abstract

Construction schedules for mechanized earthworks rest on deterministic elemental estimating norms, whereas the set of operable machines, the availability of work faces and the haulage cycle time change within a single shift. The gap between the normative model and the variability of the production environment generates organizational losses whose magnitude has not been quantified in a way that separates the planning component from the short-interval control component. The study aims to measure the share of productivity losses of a construction machinery set attributable to the interval between successive reallocations of resources, and to identify the disturbance sources that govern this share. Monte Carlo simulation was performed on an author's model of a set comprising two excavators with a 1.25 m³ bucket and nine 20-tonne dump trucks for an excavation volume of 68,430 m³; ten-day, shift-based and two-hour rescheduling were compared, and the contribution of individual disturbances was isolated by sequential deactivation. Shortening the rescheduling interval from ten days to two hours reduces the mean duration of the excavation from 60.77 to 55.61 shifts, raises the time utilization factor of the leading machines from 0.702 to 0.767 and compresses the standard deviation of duration from 4.85 to 1.62 shifts. Organizational downtime of the leading machine falls from 1.89 to 1,37 hours per shift, while the share of maintenance downtime remains near 4%. Haulage cycle variability accounts for 19,8% of the discrepancy, machine failures and loss of work face for more than four fifths. The time gain obtained coincides, within 0,2%, with the gain from adding a tenth dump truck under ten-day planning, which demonstrates the quantitative interchangeability of organizational coordination and physical fleet expansion. The lag between the arrival of data on the state of the machinery set and the recalculation of resource allocation thus constitutes an independent source of losses, separable from the technical condition of the machines and from the accuracy of estimating norms.