Improving Timber Trucking Performance by Reducing Variability of Log Truck Weights
Abstract We evaluated weight data from 79,760 truckloads delivered to 24 southern forest products mills to assess opportunities for improving trucking efficiency by reducing the variability of gross, tare, and net weights. We compared the mean gross vehicle weight (GVW) at each mill to the federal weight limit of 40 tons and to any mill overweight policy. A benchmark group of suppliers was identified at each mill as the five with the lowest coefficient of variation (CV) on their GVWs to compare with the other suppliers at each mill. All mills had mean GVWs significantly different from the federal limit at the 90% confidence level or stronger. A majority of loads delivered to each mill (77–100%) complied with mill GVW policies. At most mills, the benchmark group had higher mean GVWs and net weights, as well as lower GVW variability. Decreased GVW variability was associated with higher payloads. Mean tare weight and mean net weight exhibited an approximately 1:1 relationship at 15 mills. Benchmark groups at 14 mills had significantly larger payloads, and we project that they had 4–14% lower per-ton hauling costs than other suppliers at the mills. These results suggest that operating at the reduced variability level of the benchmark groups across the 221 million tons of roundwood annually consumed in the US South could result in a savings of $100 million annually.