Application of discrete-event simulation to study the paving operation of asphalt concrete.

Purpose — To evaluate and optimize asphalt paving operations taking place in the reconstruction project of Interstate 74 in the USA using simulation. Design/methodology/approach — Data collected during construction was used to determine useful probabilistic density functions for the activities duration and to validate a developed simulation model. Upon validation, the developed model was used to study the impact of resources on the flow of operations, and on the cost-effectiveness of the construction process. Findings — The developed simulation model was successful in simulating the paving operation and its accuracy was acceptable compared to field measurements. Based on the results of a sensitivity analysis of the critical resources, multiple factors were identified in the decision-making process to ensure that all aspects of the operation were considered. For the conditions pertinent to this construction site, 30 trucks, one paver, and two rollers are recommended. Using this set of resources results in a prompt and effective execution of the construction process. Research limitations/implications — The developed model is applicable only to asphalt paving operations. The predictive capability of the developed model has not yet been investigated. Practical implications — Implementation of the presented model in practical applications can be accomplished by conducting short training courses. This will provide personnel with flexibility in addressing project-specifics conditions and limitations. If this approach is not feasible, production charts may be developed to easily determine the optimum resources that should be used given specific time constraints and quantity, issues. Originality/value — The presented methodology has great potential to optimize resources and production rates in similar asphalt paving operations. Moreover, benefits of simulation would be maximized if it was used during the planning phase, as it will affect equipment orders and material shipments. [ABSTRACT FROM AUTHOR]