Current issue: 56(1)
Under compilation: 56(2)
Because today’s tree planting machines do a good job silviculturally, the Nordic forest sector is interested in finding ways to increase the planting machines’ productivity. Faster seedling reloading increases machine productivity, but that solution might require investments in specially designed seedling packaging. The objective of our study was to compare the cost-efficiency of cardboard box concepts that increase the productivity of tree planting machines with that of today’s two most common seedling packaging systems in southern Sweden. We modelled the total cost of these five different seedling packaging systems using data from numerous sources including manufacturers, nurseries, contractors, and forest companies. Under these southern Swedish conditions, the total cost of cardboard box concepts that increase the productivity of intermittently advancing tree planting machines was higher than the cost of the cultivation tray system (5–49% in the basic scenario). However, the conceptual packaging system named ManBox_fast did show promise, especially with increasing primary transport distances and increased planting machine productivities and hourly costs. Thus, our results show that high seedling packing density is of fundamental importance for cost-efficiency of cardboard box systems designed for mechanized tree planting. Our results also illustrate how different factors in the seedling supply chain affect the cost-efficiency of tree planting machines. Consequently, our results underscore that the key development factor for mechanized tree planting in the Nordic countries is the development of cost-efficient seedling handling systems between nurseries and planting machines.
In wintertime, the payload capacity of a timber truck is reduced by snow that accumulates on the structures of the truck. The aim of this study was to quantify the potential payload loss due to snow and winter accessories and to predict the loss with weather variables. Tare weights of eight timber trucks were collected at mill receptions in Finland over a one-year period. Monthly and annual loss of potential payload was estimated using the tare measurements in summer months as a reference. Each load was also connected with weather data at the location and time of delivery and payload loss explained by the weather data with the aid of regression models. The maximum loss of payload varied between 1560 kg and 3100 kg. On a monthly basis, the highest losses occurred in January, when the median values varied between 760 kg and 2180 kg. Over the year, the payload loss ranged between the trucks from 0.5% to 1.5% (from 1.9% and 5.1% in January) of the total number of loads in the study. Payload loss was found to increase with decreasing temperature, increasing relative humidity and increasing precipitation. Although the average payload loss was not very high, the biggest losses occur just during the season of highest capacity utilization. Big differences were also found in the tare weights between the trucks. The results of the study give incentive to develop truck and trailer structures that reduce the adherence of snow.
This review systematically analyses and classifies research and review papers focusing on discrete event simulation applied to wood transport, and therefore illustrates the development of the research area from 1997 until 2017. Discrete event simulation allows complex supply chain models to be mapped in a straightforward manner to study supply chain dynamics, test alternative strategies, communicate findings and facilitate understanding of various stakeholders. The presented analyses confirm that discrete event simulation is well-suited for analyzing interconnected wood supply chain transportation issues on an operational and tactical level. Transport is the connective link between interrelated system components of the forest products industry. Therefore, a survey on transport logistics allows to analyze the significance of entire supply chain management considerations to improve the overall performance and not only one part in isolation. Thus far, research focuses mainly on biomass, unimodal truck transport and terminal operations. Common shortcomings identified include rough explanations of simulation models and sparse details provided about the verification and validation processes. Research gaps exist concerning simulations of entire, resilient and multimodal wood supply chains as well as supply and demand risks. Further studies should expand upon the few initial attempts to combine various simulation methods with optimization.