Resource Guide for State DOT\u2019s Maintenance Equipment Fleet Management Decisions [supporting datasets]

University Transportation Centers Program2021XLSXDatasetShan, YongweiAhmed, SamirQiao, LeiTransportation Consortium of South-Central States (Tran-SET) University Transportation Center for Region 6Louisiana State University (Baton Rouge, La.). University Transportation Center for Region 6United States. Department of Transportation. University Transportation Centers (UTC) ProgramUnited States. Department of Transportation. Office of the Assistant Secretary for Research and TechnologyTransportation Consortium of South-Central StatesUnited StatesCostsDecision makingEquipment maintenanceFleet managementLife cycle costingMaintenance equipmentDynamic programmingEquipment replacementEconomic factors20OPOSU03769A3551747106This research created a guide for state Departments of Transportation fleet management on utilizing equipment fleet management system data to make informed fleet management decisions. The research team took the historical equipment fleet data from the Oklahoma Department of Transportation and developed workflows, algorithms, and examples to demonstrate the use of historical equipment data for equipment decisions. Specifically, the research team demonstrated 1) the use of life cycle analysis and dynamic programming models for equipment replacement decisions; 2) developed algorithms to calculate equipment rental rates that can be used by the Department to forecast and allocate equipment operational budget among field districts and central office, 3) developed a procedure to make own-rent/lease decisions based on historical equipment management data. Using the two class codes of equipment (Class Code 5355 \u2013 2 Yd. front-end loaders and Class Code 5385 \u2013 1/2-ton fleetside pickup trucks) as examples, the research team presented the result of the equipment replacement models using both life cycle analysis and dynamic programming approaches and discussed the difference of those two methods. In addition, the impact of model input parameters (specifically depreciation cost estimation using both straight line and double declining balance depreciation calculation methods) on equipment replacement outcomes is discussed. The framework for deciding between on renting or owning for the two class codes of equipment was developed. Also, the equipment rental rates for the most frequently used equipment by ODOT were updated per class code.132