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AB - Abstract Between 30 and 40% of private and state forest lands in the US Pacific Northwest are in steep terrain, making forest harvest residues difficult and costly to obtain. Turnarounds in steep terrain are particularly problematic. In 2010, Hermann Brothers Logging (Port Angeles, WA), in collaboration with Western Trailers (Boise, ID), designed a self-steering chip van to increase large trailer access in steep areas of the Olympic Peninsula (WA). Following a series of mobility tests of the self-steering trailer, Arena Simulation by Rockwell Automation was used to compare the self-steering trailer system cost-effectiveness against a hook-lift truck system on a total system cost BDMt-1 basis. Under a base scenario, the self-steering system had a lower cost ($60.01 BDMt-1) than the hook-lift truck application ($101.27 BDMt-1) with a total system cost, including mobilization, piling, support equipment, and profit and risk. Assuming a 13.72 m (45 ft) standard trailer could reach a percentage of the harvest units, the hook-lift/standard trailer combination system was still not competitive with the self-steering trailer under the base case scenario until the percent allocation for the hook-lift trucks was reduced to 13%. After altering the base case scenario to favor the hook-lift application, the self-steering system was still more cost-effective until the allocation for hook-lift trucks was reduced to 21%. forest biomass, primary transport, biomass energy, chip van, balance Management and Policy Implications Biomass operations can become limited by the equipment used to obtain forest harvest residues. Steep areas provide challenges for larger chip van access unless specialized equipment is used such as the 48 ft (14.63 m) self-steering chip van or smaller vehicles such as a hook-lift truck or dump truck. However, even though an area may have access for transporting the residues, depending on the system used, it can become too costly to be viable. In areas where a specialized vehicle is needed, it is recommended to use a self-steering trailer over a hook-lift or dump truck system due to the latter system having limited carrying capacity and a higher number of machine interactions, which can increase the cost of transportation. Using a larger chip van in the field reduces the re-handling process and allows transport of more tonnage over a longer distance. Recently, there has been a push to reduce the dependency on fossil fuels by using alternative sources of energy. Forest harvest residues provide a promising alternative for the creation of liquid fuels and energy production. Forest harvest residues are defined as the mixture of varying-sized tree parts that were not taken during the initial harvest (Zamora-Cristales et al. 2015). This includes branches, tree tops, log butts, logs with defects, as well as noncommercial species and small-diameter trees. Historically, piling and burning harvest residues was a popular practice to prepare a harvested unit for replanting. However, there are limitations with piling and burning residues that can restrict the practice or make it costly to perform. Such limitations include risk due to wildfire and smoke control regulations (Anderson et al. 2012). Utilizing forest harvest residues reduces the need to pile and burn and, under some conditions, can be profit generating. Nearly 49 million dry metric tons of forest harvest residues are produced annually in the United States (US Department of Energy 2011). However, topography, among other factors, restricts how much biomass is economically available for extraction. In the Pacific Northwest, 30–40% of private and state forest lands are in steep terrain, making biomass difficult and costly to obtain. The location of biomass (flat vs. steep terrain) and how it is collected/transported can make it costly (generating less profit than a more favorable condition), or it can become economically infeasible. If operating conditions are favorable (good truck access, flatter terrain, correct equipment, short transport times), costs are lower and a higher profit can be generated. The biomass supply chain shares similarities with the sawtimber supply chain (e.g., Ackerman et al. 2017). One major determinant of available harvest residues in a given harvest unit is the type of harvest system used. Whole tree harvesting is a popular method used in Oregon and Washington (US) on both steep slopes and flatter terrain (Zamora-Cristales and Sessions 2016). On steep-slope operations, most of the residues are located near log landings as a byproduct of the log manufacturing process. On flatter terrain, where ground-based operations are most often used, most residues do not make it to the landing due to breakage during the re-handling process of the ground-based equipment. Kizha and Han (2015) studied recovery rates for both steep-slope cable operations and ground-based shovel-excavator operations, reporting that 60% of the residues could be recovered under a cable operation and 70% of the residues recovered in a shovel-excavator operation. Several delivery systems have been developed to extract biomass from areas in steep terrain. A common system includes moving a grinder to roadside and processing the residues at each pile. This requires transporting a grinder to the harvest unit and using chip vans to transport the processed residues. However, most forest roads were designed for stinger-steered log trailers without concern for chip van access (Sessions et al. 2010). A stinger-steered trailer is a trailer steered by the tongue (reach) of the trailer attached to an extension of the truck tractor frame (stinger). Typically, chip vans are pulled by a truck tractor with the chip van attached just forward of the center of the tractor driving axles (a stinger length of approximately zero). Finding an adequate turnaround for a chip van can be challenging. Even if there is an accessible turnaround location, the maneuver could be difficult and time consuming, making the system economically infeasible. In 2010, Hermann Brothers Logging (Port Angeles, WA), in collaboration with Western Trailers (Boise, ID), designed a self-steering trailer (Force Steer) to increase large trailer access in steep areas of the Olympic Peninsula, Washington. The 48 ft (14.63 m) trailer is pulled by a 6x6 (all-wheel drive) logging truck tractor. The Force Steer trailer gets its maneuverability from a pair of rear hydraulic steering axles, which are controlled by the operator with a hand-operated joystick (Figure 1). Hermann Brothers Logging has stated that the trailer has zero-off tracking, meaning the trailer follows in the truck’s path and can operate in any area that a log truck can access. The body of the trailer has been reinforced to better withstand off-road conditions than a standard trailer, as the twisting and turning of forest roads puts a strain on the walls and cross members of the trailer. Bill Hermann’s trailers were designed for high capacity at the expense of low ground clearance (Figure 1). To provide additional vertical clearance for forest roads, an inflatable airbag was added to the self-steering trailer to lift the trailer by four inches, allowing it to operate in more constrained areas. The 6x6 truck tractor provides the necessary traction to climb steep grades while pulling the empty trailer. Figure 1. View largeDownload slide (Left) All-wheel drive truck paired with a 14.63 m self-steering trailer. (Right) Hand-operated joystick controller for the self-steering trailers. Figure 1. View largeDownload slide (Left) All-wheel drive truck paired with a 14.63 m self-steering trailer. (Right) Hand-operated joystick controller for the self-steering trailers. A few studies have examined the maneuverability of chip vans on turnarounds. Sessions et al. (2010) evaluated (1) backing into a road intersection, (2) turning around on a wide space such as a landing, and (3) turning around on the nose of a ridge. Depending on the location of the turnaround, the truck will either back up to the active job site or drive forward. Sessions et al. (2010) observed that a standard truck-trailer combination with a wheelbase of 16.76 m (55 ft) could successfully turn around on a road intersection that has at least a throat width of 21.34 m (70 ft) with an 18.28 m (60 ft) transition. However, under some situations, road modification may need to be done to successfully navigate a turnaround, such as filling in the ditches and protecting culvert inlets. The specific objectives of this study are (a) to conduct physical tests to document the maneuverability of the self-steering trailer paired with a 6x6 (all-wheel drive) truck tractor, (b) to estimate the productivity and costs of this system, and (c) to compare it to the alternative of using a hook-lift truck. Study Methods The mobility study was conducted in two phases: a controlled experiment and a field trial. The specifics of these operations are reported below. Controlled Experiment Study The controlled experiment study was done in Port Angeles, Washington, at a chip yard owned by Hermann Brothers Logging. The chip yard was large enough to simulate a series of road layouts and to maneuver a chip van with the self-steering mechanism in the on (active) and off (not active) position. A single driver was used to avoid variability between drivers. The driver used in this study had several years of experience using both self-steering and conventional trailers. Each maneuver was timed to determine the length of the turnaround operation. A series of road layouts were prepared, ranging from a 90-degree intersection to a 65-degree intersection. Site limitations restricted any layout smaller than a 65-degree intersection. The self-steering trailer was also compared against using the self-steering mechanism turned off performing a 180-degree turnaround on a rectangular landing-based road design. For the standard setting of the trailer, the driver performed a multi-part turn within the given space, maneuvering the trailer into a jackknife position and pivoting on the trailer’s axles (Sessions et al. 2010). For the self-steering setting, the driver jackknifed the trailer but positioned the rear axles to turn the trailer as it backed up or drove forward. Laying out the course involved using traffic cones to simulate a forest road. Vertical PVC pipe with flagging was used to increase visibility for the driver. Both the road intersection and the rectangular multi-part turn course used a 4 m (13 ft) road width typical in the Pacific Northwest. The position of the chip van as it moved along the course was marked using a high-visibility marking paint and a roller on the gravel. For the rectangular multi-part turn test, the distance from the edge of the layout to the chip van’s path was recorded to determine the surface area needed to successfully turn around. If the chip van could successfully turn around, the traffic cones were moved inward until the vehicle could no longer turn around within the designated space. For the road intersection course, the driver was instructed to drive one time in each direction to determine if the driver handled the turn differently based on the position of the driver relative to the road centerline. The forward distance past the intersection, backing distance into the secondary road, path of restrictive tire along the curve, and any location where the van went off-course were marked. The distance between the marks on both sides of the road and along the curve was measured to determine the road geometry needed to successfully maneuver the van. Both the self-steered mechanism and the standard setting of the chip van were tested and compared. Field Trial A field trial was conducted to test how the self-steering trailer operated in field conditions. Under the hypothesis that the self-steering chip van was able to operate on any road designed for stinger-steered log trailers, the field study was limited to more constrained areas. The self-steering trailer was tested in areas that had challenging road conditions, such as steeper slopes (up to around +15% slope), small curve radii, deep road ditches, vegetation, and limited space. The controlled study was used as the basis to determine road conditions to look for under field conditions. Because the field trials were in constrained areas, only the self-steering function was tested, as non-steering trailer operation was not possible. The same driver was used as in the controlled study, and each trial was timed. As with the controlled study, the path of the most limited tire on each side of the chip van was marked with a high-visibility marking paint using a paint roller on the gravel. Both the driving forward distance past the intersection and the backing distance into the secondary road were marked. The angle of intersection, road widths, and general slope of the roads were recorded. Any area that the chip van navigated off-course was marked and measured for future analysis. Road Design The information taken from the control and field study was used to create road designs to show what the general road geometry should look like, as well as the minimum surface area needed to successfully turn around a self-steering trailer. The Civil 3D program in AutoCAD was used to model the road geometry with a simple curve connecting the two intersection roads. The actual truck path, represented by an “x” in Figures 3–6, is the minimum surface area needed for a successful chip van turnaround. Results and Discussion Landing/Ridgetop Turnaround Finding an accessible turnaround in steep terrain is challenging. Wide areas such as ridgetops or landings are possible spots to turn around, but they must be near the active job site to be economically feasible. These areas vary in size and shape and could be limited by vegetation, side slopes, and logging debris. A self-steering chip van was used to evaluate the surface area needed to successfully turn around in a rectangular-shaped area (Figure 2). Results showed that a 16 × 24 m (53 × 80 ft) area should be adequate to successfully turn around a 14.63 m (48 ft) self-steering trailer. The trailer did not utilize the entire area during the maneuver, following more of a teardrop shape. The total time for the maneuver was approximately 10 minutes. The results for the self-steering trailer with the steering mechanism turned off indicated that an 18 × 27 m (60 × 90 ft) rectangle should be adequate to turn around successfully. The trailer utilized the entire area with a maneuver time of around 3 minutes. The time difference between the two tests was largely due to positioning the rear trailer tires before backing or driving forward. Also, because there were multiple tests completed using the self-steering mechanism prior to the final result, the air in the self-steering mechanism was not fully charged. The driver had to stop twice during the test to allow the air to fully charge, which took about a minute. Even though the standard test was faster than the self-steering test, the area needed to successfully turn around the chip van was larger. Figure 2. View largeDownload slide (Left) Road design for a 14.63 m self-steering trailer on a landing type turnaround. (Right) Road design for a 14.63 m standard trailer on a landing type turnaround. Figure 2. View largeDownload slide (Left) Road design for a 14.63 m self-steering trailer on a landing type turnaround. (Right) Road design for a 14.63 m standard trailer on a landing type turnaround. Road Intersections Road intersections may be more available than landings or ridgetop areas and can be a suitable place to turn around large chip vans. However, road intersections can be difficult to turn around on. A successful turnaround operation depends on the maneuvering skill of the driver and the shape of the intersection. Maneuverability can be limited by vegetation, road gradient, road surface conditions, culverts, and ditches. The self-steering trailer showed a greater ability to maneuver a road intersection than a standard chip van. The self-steering trailer with a 6x6 truck allowed the driver to drive off the road over ditches, giving the driver more room to navigate. Also, the ability of the trailer to turn while moving saved the driver time by allowing the trailer to swing into the turn while the driver positioned the chip van past the intersection when preparing to back up. As mentioned earlier, a series of road layouts were tested in a controlled system and were later used as the basis for testing in the field. The traffic cones in the controlled study proved difficult to see, which limited the driver’s ability to navigate the road layout. Because of this, the driver was not able to successfully turn around a chip van without self-steering on the 65-degree road intersection. Figures 3 and 4 represent a controlled study on a 90-degree intersection navigated by the self-steered trailer with the steering mechanism turned on and off. With the steering mechanism turned on, the chip van could successfully turn around at an intersection, with the secondary road having a throat width of at least 18 m (60 ft) and a transition of 18 m (60 ft). The truck drove forward about 20 m (66 ft) to position the truck before backing. The self-steering truck took 4 minutes and 32 seconds to turn around. With the steering mechanism turned off, the trailer could turn around on the intersection with a secondary road having a throat width of at least 24 m (79 ft) and a transition of 23 m (75 ft). The truck drove about 26 m (85 ft) past the intersection to position the truck before backing. To successfully turn around, the trailer drove off the road near the intersection by about 7 m (23 ft). The standard truck took 4 minutes and 40 seconds to successfully turn around. Figure 3. View largeDownload slide Controlled study of a 90-degree intersection using the self-steering trailer. The number next to an arrow represents the stage of movement. Truck completed turnaround with a throat width of 18 m (60 ft) and a transition of 18 m (60 ft). Figure 3. View largeDownload slide Controlled study of a 90-degree intersection using the self-steering trailer. The number next to an arrow represents the stage of movement. Truck completed turnaround with a throat width of 18 m (60 ft) and a transition of 18 m (60 ft). Figure 4. View largeDownload slide Controlled study of a 90-degree intersection without self-steering. The number next to an arrow represents the stage of movement. Truck completed turnaround with a throat width of 24 m (79 ft) and a transition of 23 m (75 ft). Figure 4. View largeDownload slide Controlled study of a 90-degree intersection without self-steering. The number next to an arrow represents the stage of movement. Truck completed turnaround with a throat width of 24 m (79 ft) and a transition of 23 m (75 ft). There was a slight difference in road geometry depending on which side the driver entered the course. For example, the self-steering test in Figure 3 was also done with the driver entering the opposite side of the course. In Figure 3, the driver was facing the intersection upon entering, making it easier to see the curve while backing up. However, while pulling out of the secondary road, the driver position was offset by the width of the truck and the driver did not have a clear view of the curve. When the driver was facing away from the intersection upon arrival, it was more difficult to see the road curve while backing, but easier to pull out of the secondary road. The only difference in road geometry from the two tests was that the throat width on the secondary road was 3 m (10 ft) less when the limiting curve was on the side of the driver while pulling out of the secondary road. As mentioned earlier, the field study was done in areas with constraining road conditions limiting the maneuvers to the self-steering system only. Figure 5 shows the results of a maneuver using the self-steering trailer on a 52-degree intersection where the driver entered the course facing the intersection. The main road began on a +8.5% slope with a secondary road branching off on a +10% slope. The road widths in the course varied from 3.96 m (13 ft) to 4.27 m (14 ft). The secondary road was obscured by vegetation, with only about 23 m (75 ft) visible before the road intersection. The self-steering truck drove forward 38 m (125 ft) past the intersection to position the trailer before backing into the secondary road. Backing into the spur road proved challenging due to the steeper terrain and limited road length, but the vehicle was successfully able to navigate the course using 21 m (69 ft) of the spur road. The truck took 3 minutes and 32 seconds to successfully turn around. Figure 5. View largeDownload slide Field trial of a 52-degree intersection using the self-steering trailer. The number next to an arrow represents the stage of movement. Figure 5. View largeDownload slide Field trial of a 52-degree intersection using the self-steering trailer. The number next to an arrow represents the stage of movement. An advantage of the self-steering trailer paired with an all-wheel drive truck is its ability to drive off the road, within limits. Figure 6 shows a case where the chip van made its own turnaround by using part of a turnout and backing about half the length of the trailer into the woods. The trailer is able to push over small saplings but can be limited by larger trees and rocks. The self-steering chip van could turn around on the 90-degree intersection with the secondary road having a throat width of at least 10 m (33 ft) and a transition of 15 m (49 ft). The truck drove 24 m (79 ft) forward past the intersection to position the truck before backing into the secondary road. However, because the secondary road distance was limited, the truck had to drive off the road above the intersection and over the inside ditch by about 4 m (13 ft). The truck took 4 minutes and 48 seconds to successfully turn around. Figure 6. View largeDownload slide Field trial of a self-made 90-degree intersection turnaround using the self-steering trailer. The trailer had to back into the woods to turn around. The number next to an arrow represents the stage of movement. Figure 6. View largeDownload slide Field trial of a self-made 90-degree intersection turnaround using the self-steering trailer. The trailer had to back into the woods to turn around. The number next to an arrow represents the stage of movement. Backing The average speed while backing up was approximately 8 kph (5 mph). However, simultaneous restrictions such as steep terrain, small curve radii, and weather could reduce the speed. Other challenges that could reduce the speed or preclude backing altogether include heavy wind, low visibility due to rain, fog, and dust, and reduced traction due to wet ground. An important advantage of the self-steering trailer is that the driver is able to use the trailer to steer while backing up rather than using the truck, making it easier to navigate on curves. This reduces the time needed to correct the truck’s position. Other advantages of the self-steering trailer when paired with a 6x6 truck are that it can drive on the side of the road over the inside ditch, allowing for increased space to maneuver in constrained situations or when other vehicles need to pass. Also, using an all-wheel drive truck increases the power and traction on steeper terrain, allowing for more areas that the truck can operate within, particularly when the trailer is empty. Decision Model An economic model was developed to estimate and compare the cost of two alternative systems for processing and transporting biomass from a harvest unit to a destination facility. The first system tested a 14.63 m (48 ft) self-steering trailer paired with a 6x6 truck on a harvest unit that used a road intersection as a turnaround that was located before the grinder location. The second system tested a hook-lift application transporting harvest residues to a central landing near the harvest unit. At the central landing, the residues were piled and held until the primary transport of harvest residues from the harvest unit was completed. The residues were then processed and transported to a destination facility using a 6x4 highway truck with a standard 16.15 m (53 ft) chip van. A discrete-event simulation model was designed in Arena Simulation (Rockwell Automation 2017) to model the two transportation systems during a single 10-hour shift duration. The discrete-event simulation model estimated the hourly cost per bone-dry metric ton ($ BDMt-1) for equipment that was either operating or waiting. Hourly machine rates were based on the standard machine rate calculation methods described in Miyata (1980) and Brinker et al. (2002). Equipment was assumed to be purchased new, and prices were provided by local contractors or determined by regional market prices for similar equipment (Table 1). For the hook-lift and chip vans, 2000 productive machine hours per year (PMH y-1) were estimated. For the Doosan DX300LL Log Loader and Peterson Pacific 5710D Horizontal Grinder, 1,500 PMH y-1 were estimated. Fixed costs (Eq. 1) for the transportation and processing equipment were based on the purchase price of the machines, interest (10% of average yearly investment), insurance and taxes (5% of average yearly investment), depreciation (based on 20% salvage value and tied to expected hours of use), and machine life (5 years for grinder and 8 years for the loader and trucks). Hourly variable costs (Eq. 2–4) included fuel cost that was assumed to be $0.79 liter-1 ($3.00 gallon-1) for diesel for in-woods equipment and $0.92 liter-1 ($3.50 gallon-1) for highway vehicles. Other variable costs included lubrication, calculated at 36% of total fuel cost, and repair and maintenance cost, calculated at 90% of the machine depreciation. Labor cost was assumed to be $23.61 hour-1 plus benefits (40% of hourly wage) using the average 2015 base wage for logging equipment operators in Washington State (Bureau of Labor Statistics 2015). Other system costs included the support equipment plus any administrative cost incurred during the operation. Profit and risk (10% of total fixed and variable cost) were also added to each machine cost. Table 1. Operating cost for machinery used in the self-steering and hook-lift applications. Operating cost Doosan DX300LL Peterson Pacific Kenworth T800 Rear steer-axle 14.63 m Standard 13.72 m Standard 16.15 m Log loader Hor. grinder 1050 HP Hook-lift truck (6x6 truck + trailer) (6x4 truck + trailer) (6x4 truck + trailer) Purchase price ($) 352,000 700,000 150,000 375,000 180,000 200,000 Depreciation ($ yr-1) 35,200 112,000 15,000 37,500 18,000 20,000 Interest ($ yr-1) 22,880 47,600 9,750 24,375 11,700 13,000 Insurance & taxes ($ yr-1) 11,440 23,800 4,875 12,188 5,850 6,500 Prod. mach. hours (hr yr-1) 1,500 1,500 2,000 2,000 2,000 2,000 Total fixed cost ($ hr-1) 46.35 122.27 14.81 37.03 17.78 19.75 Bits, grates, anvil ($ hr-1) – 22.70 – – – – Tires ($ hr-1) – – 5.11 9.53 6.41 7.98 Maintenance & repair ($ hr-1) 21.12 67.20 6.75 16.88 8.10 9.00 Fuel & lube ($ hr-1) 23.79 146.06 15.71 28.61 25.23 28.56 Overhead ($ hr-1) – 21.80 6.70 6.70 6.70 6.70 Support ($ hr-1) – 14.80 – – – – Labor ($ hr-1) 39.66 0.00 36.36 36.36 36.36 36.36 Total variable cost ($ hr-1) 84.58 272.56 70.63 98.07 82.80 88.60 Profit and risk 10% ($ hr-1) 13.09 39.48 8.54 13.51 10.06 10.83 Total cost ($ hr-1) 144.02 434.31 93.98 148.61 110.63 119.18 Operating cost Doosan DX300LL Peterson Pacific Kenworth T800 Rear steer-axle 14.63 m Standard 13.72 m Standard 16.15 m Log loader Hor. grinder 1050 HP Hook-lift truck (6x6 truck + trailer) (6x4 truck + trailer) (6x4 truck + trailer) Purchase price ($) 352,000 700,000 150,000 375,000 180,000 200,000 Depreciation ($ yr-1) 35,200 112,000 15,000 37,500 18,000 20,000 Interest ($ yr-1) 22,880 47,600 9,750 24,375 11,700 13,000 Insurance & taxes ($ yr-1) 11,440 23,800 4,875 12,188 5,850 6,500 Prod. mach. hours (hr yr-1) 1,500 1,500 2,000 2,000 2,000 2,000 Total fixed cost ($ hr-1) 46.35 122.27 14.81 37.03 17.78 19.75 Bits, grates, anvil ($ hr-1) – 22.70 – – – – Tires ($ hr-1) – – 5.11 9.53 6.41 7.98 Maintenance & repair ($ hr-1) 21.12 67.20 6.75 16.88 8.10 9.00 Fuel & lube ($ hr-1) 23.79 146.06 15.71 28.61 25.23 28.56 Overhead ($ hr-1) – 21.80 6.70 6.70 6.70 6.70 Support ($ hr-1) – 14.80 – – – – Labor ($ hr-1) 39.66 0.00 36.36 36.36 36.36 36.36 Total variable cost ($ hr-1) 84.58 272.56 70.63 98.07 82.80 88.60 Profit and risk 10% ($ hr-1) 13.09 39.48 8.54 13.51 10.06 10.83 Total cost ($ hr-1) 144.02 434.31 93.98 148.61 110.63 119.18 View Large Table 1. Operating cost for machinery used in the self-steering and hook-lift applications. Operating cost Doosan DX300LL Peterson Pacific Kenworth T800 Rear steer-axle 14.63 m Standard 13.72 m Standard 16.15 m Log loader Hor. grinder 1050 HP Hook-lift truck (6x6 truck + trailer) (6x4 truck + trailer) (6x4 truck + trailer) Purchase price ($) 352,000 700,000 150,000 375,000 180,000 200,000 Depreciation ($ yr-1) 35,200 112,000 15,000 37,500 18,000 20,000 Interest ($ yr-1) 22,880 47,600 9,750 24,375 11,700 13,000 Insurance & taxes ($ yr-1) 11,440 23,800 4,875 12,188 5,850 6,500 Prod. mach. hours (hr yr-1) 1,500 1,500 2,000 2,000 2,000 2,000 Total fixed cost ($ hr-1) 46.35 122.27 14.81 37.03 17.78 19.75 Bits, grates, anvil ($ hr-1) – 22.70 – – – – Tires ($ hr-1) – – 5.11 9.53 6.41 7.98 Maintenance & repair ($ hr-1) 21.12 67.20 6.75 16.88 8.10 9.00 Fuel & lube ($ hr-1) 23.79 146.06 15.71 28.61 25.23 28.56 Overhead ($ hr-1) – 21.80 6.70 6.70 6.70 6.70 Support ($ hr-1) – 14.80 – – – – Labor ($ hr-1) 39.66 0.00 36.36 36.36 36.36 36.36 Total variable cost ($ hr-1) 84.58 272.56 70.63 98.07 82.80 88.60 Profit and risk 10% ($ hr-1) 13.09 39.48 8.54 13.51 10.06 10.83 Total cost ($ hr-1) 144.02 434.31 93.98 148.61 110.63 119.18 Operating cost Doosan DX300LL Peterson Pacific Kenworth T800 Rear steer-axle 14.63 m Standard 13.72 m Standard 16.15 m Log loader Hor. grinder 1050 HP Hook-lift truck (6x6 truck + trailer) (6x4 truck + trailer) (6x4 truck + trailer) Purchase price ($) 352,000 700,000 150,000 375,000 180,000 200,000 Depreciation ($ yr-1) 35,200 112,000 15,000 37,500 18,000 20,000 Interest ($ yr-1) 22,880 47,600 9,750 24,375 11,700 13,000 Insurance & taxes ($ yr-1) 11,440 23,800 4,875 12,188 5,850 6,500 Prod. mach. hours (hr yr-1) 1,500 1,500 2,000 2,000 2,000 2,000 Total fixed cost ($ hr-1) 46.35 122.27 14.81 37.03 17.78 19.75 Bits, grates, anvil ($ hr-1) – 22.70 – – – – Tires ($ hr-1) – – 5.11 9.53 6.41 7.98 Maintenance & repair ($ hr-1) 21.12 67.20 6.75 16.88 8.10 9.00 Fuel & lube ($ hr-1) 23.79 146.06 15.71 28.61 25.23 28.56 Overhead ($ hr-1) – 21.80 6.70 6.70 6.70 6.70 Support ($ hr-1) – 14.80 – – – – Labor ($ hr-1) 39.66 0.00 36.36 36.36 36.36 36.36 Total variable cost ($ hr-1) 84.58 272.56 70.63 98.07 82.80 88.60 Profit and risk 10% ($ hr-1) 13.09 39.48 8.54 13.51 10.06 10.83 Total cost ($ hr-1) 144.02 434.31 93.98 148.61 110.63 119.18 View Large Fm= (Dm+ Im+ Tm)/Hm (1) VG= FG+ BG+ RG+ OG+ SG (2) VL= FL+ RL+ LL (3) VT= FT+ TT+ RT+ LT+ OT c (4) where Fm  hourly total fixed cost for machine m ($ hr-1) Dm  annual depreciation cost for machine m ($) Im  annual interest cost for machine m ($) Tm  annual insurance and taxes cost for machine m ($) Hm  annual productive machine hours, varies by machine (hr) VG  hourly total variable cost for grinder ($ hr-1) FG  hourly fuel cost for grinder ($ hr-1) BG  hourly bits (teeth) cost for grinder ($ hr-1) RG  hourly repair and maintenance cost for grinder ($ hr-1) OG  hourly overhead cost for grinder ($ hr-1) SG  hourly support equipment for grinder ($ hr-1) VL  hourly total variable cost for loader ($ hr-1) FL  hourly fuel cost for loader ($ hr-1) RL  hourly repair and maintenance cost for loader ($ hr-1) LL  hourly labor cost for loader ($ hr-1) VT  hourly total variable cost for truck ($ hr-1) FT  hourly fuel cost for truck ($ hr-1) TT  hourly tire cost for truck ($ hr-1) RT  hourly repair and maintenance cost for truck ($ hr-1) LT  hourly labor cost for truck ($ hr-1) OT  hourly overhead cost for truck ($ hr-1) To calculate the total cost for each system, the waiting cost for transportation and processing equipment were calculated based on the waiting time caused by truck-machine interaction. Total hourly waiting cost included the interest cost, insurance and taxes, overhead cost, support equipment cost, labor, and profit and risk to account for the opportunity cost lost due to machine waiting (Eq. 5–7). WTCL= ((Im+ Tm)/Hm) + LL+ PRL (5) WTCG= ((Im+ Tm)/Hm) + OG+ SG+ PRg (6) WTCTm= ((Im+ Tm)/Hy) + LT+ OT+ PRT (7) where WTCL  hourly waiting cost for loader ($ hr-1) WTCg  hourly waiting cost for grinder ($ hr-1) WTCTm  hourly waiting cost for truck type m ($ hr-1) PRL  hourly profit and risk for loader ($ hr-1) PRG  hourly profit and risk for grinder ($ hr-1) PRT  hourly profit and risk for truck ($ hr-1) Both transportation systems were compared using similar conditions, but also had varying characteristics based on the type of transportation equipment used (Figure 7). Under both scenarios, it is assumed that the harvest unit was a whole-tree cable operation with the forest harvest residues pre-piled at roadside. The material in the unit encompassed a mixture of species, including Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), western hemlock (Tsuga heterophylla (Raf.) Sarg.), Sitka spruce (Picea sitchensis (Bong.) Carriere), and western red cedar (Thuja plicata Donn ex D. Don). The mean specific gravity used in the model was assumed to be 0.38 with a moisture content of 34% wet basis (Cross et al. 2013). Under the self-steering system, the forest harvest residues were processed in the field using a grinder and a loader and then transported to a bioenergy facility. It was assumed that the equipment was transported to the active unit by lowboy at a rate of $120 hr-1 and the mobilization took a total of six hours. Although the harvest residues were piled post-harvest, it was assumed that additional piling was needed before the grinding process to rearrange and move the piles closer together to allow for optimal grinder efficiency. The number of available vehicles, distance from the turnaround to the grinder, and distance to the facility was varied to evaluate sensitivity to scenario parameters, and how machine interactions affected the overall utilization of each machine. Figure 7. View largeDownload slide Base case scenario for the self-steering trailer system, hook-lift truck system, and parameters used in the Arena Simulation model. Figure 7. View largeDownload slide Base case scenario for the self-steering trailer system, hook-lift truck system, and parameters used in the Arena Simulation model. The total cost of processing and transportation for the self-steering system was based on $ BDMt-1 and derived from the working and waiting cost of each machine and the amount of biomass brought to the bioenergy facility (Eq. 8–13). The processing cost is dependent on the working and waiting time per shift of the loader and grinder. The processing working time is calculated based on the number of loads that enter the system multiplied by the grinding time. Each load took 28 minutes to fill a 14.63 m (48 ft) self-steering trailer with a capacity of 26.05 green metric tons. The processing waiting time was calculated by subtracting the working time from the total time the equipment was in the system during the shift duration. The transportation cost is dependent on the average working and waiting time of the trucks during a shift multiplied by the number of trucks in the system. The working time of a single truck is dependent on its inter-arrival time, round-trip time, and number of cycles it completed. Under the base case scenario, the average truck waiting time per shift is an accumulation of the waiting time (if any) at the turnaround and/or turnout. Because the turnaround is located before the grinder location, a truck can wait in the turnaround until the grinder is free. The truck waiting in the turnaround must remain until the truck at the grinder finishes processing and drives past the turnaround. If there are too many vehicles in the system and a truck enters the unit with both the grinder and turnaround occupied, then the truck must wait at the turnout near the entrance of the harvest unit. The truck waiting at the turnout must then remain until the turnaround is free and allow the other truck that just finished processing to drive past the turnout. Self-Steering System PC = CP+ MP (8) CP= ((WL+ WG)*HLG) / BDMt (9) MP= ((WTCL+ WTCG)*YLG) / BDMt (10) TC = CT+ MT (11) CT= ((WT*HT)*N) / BDMt (12) MT= ((WTCSS*YT)*N) / BDMt (13) where PC  total processing cost of self-steering system, $ BDMt-1 CP  total processing working cost of self-steering system, $ BDMt-1 WL  hourly working cost of loader ($ hr-1) BDMt  bone-dry metric tons transported WG  hourly working cost of grinder ($ hr-1) HLG  working time of grinder and loader (hr) MP  total processing waiting cost of self-steering system, $ BDMt-1 YLG  waiting time of grinder and loader (hr) TC  total transportation cost of self-steering system, $ BDMt-1 CT  total transportation working cost of self-steering system, $ BDMt-1 WT  hourly working cost of self-steering truck ($ hr-1) HT  working time of self-steering truck (hr) N  number of transportation vehicles MT  total transportation waiting cost of self-steering system, $ BDMt-1 WTCSS  hourly waiting cost of self-steering truck ($ hr-1) YT  waiting time of self-steering truck (hr) The effect of the number of available self-steering vehicles on the overall utilization for each machine type was analyzed by modeling the scenario under the base case situation and varying the number of trucks (Figure 8). Results from the operation concluded that six trucks minimized the processing and transportation cost ($44.95 BDMt-1) with 16 loads brought to the bioenergy facility. The maximum grinder utilization rate for six trucks was estimated to be 75% with a processing cost of $15.70 BDMt-1. Adding another truck to the system was found to increase the grinder utilization rate by 4% but was limited by road access. Using seven trucks under this scenario increased the transportation wait time upon arrival at the harvest unit, which increased both the transportation cost and total cost of production ($45.06 BDMt-1). Total cost decreased by 36% due to an increase in the grinder utilization from 17% (one truck) to 75% (six trucks). Figure 8. View largeDownload slide Total cost for the processing and transporting stages in the self-steering trailer system with variable number of trucks available. Costs are expressed in US dollars per bone-dry metric ton ($ BDMt-1). Figure 8. View largeDownload slide Total cost for the processing and transporting stages in the self-steering trailer system with variable number of trucks available. Costs are expressed in US dollars per bone-dry metric ton ($ BDMt-1). The distance and location of the turnaround to the grinding activity is an important parameter in the overall utilization for each machine. Under the current scenario for the self-steering trailer, the turnaround is located before the grinder, allowing a truck to wait in the turnaround rather than at the turnout near the harvest unit entrance. This reduces the distance a truck must drive once the grinder is free. A disadvantage of this setup is that the truck must back up from the turnaround to the grinder location and may limit the system if the distance is long or the road conditions are challenging. As mentioned earlier, the advantage of the self-steering trailers over a standard chip van is the ability to use the trailer as the steering mechanism while backing, making it easier to navigate. Also, the backing speed of the self-steering trailer is faster (8 kph or 5 mph) than a standard chip van (3 kph or 2 mph), allowing for a shorter time maneuver. A sensitivity analysis was completed to evaluate how altering the distance from the turnaround to the grinder affects the overall utilization for the grinder and the total cost (Figure 9). The number of available trucks in the base case was set to five trucks, and the distance from the turnaround to the grinder location varied from 0.08 km (0.05 miles) to 1.60 km (1 mile). Total cost increased by $7.74 BDMt-1 when changing the distance from 0.08 km (0.05 miles) to 1.60 km (1 mile). The grinder utilization decreased from 66% at 80 m (262 ft) to 50% at 1600 m (5249 ft). The closer the grinder was to the turnaround, the less time the truck had to wait at the turnaround or turnout near the unit entrance, reducing the transportation cost. Also, the grinder utilization increased due to shorter backing lengths. The greater the distance, the more time a truck had to wait at the turnaround, increasing the transportation cost. The backing distance was also increased, reducing the grinder utilization. Figure 9. View largeDownload slide Sensitivity analysis of total cost and grinder utilization to changes in the distance from the turnaround to the grinder location under the self-steering trailer system. Figure 9. View largeDownload slide Sensitivity analysis of total cost and grinder utilization to changes in the distance from the turnaround to the grinder location under the self-steering trailer system. The distance to the bioenergy facility is another factor in the overall utilization for each machine. By changing the distance between the harvest unit entrance and the bioenergy facility, the round-trip time will either increase or decrease. This could alter machine interactions and thus change working and waiting costs of the equipment. By altering the round-trip time of the transportation, the number of cycles in the system could change, affecting the grinder utilization. A sensitivity analysis was completed to evaluate how changing the distance to the bioenergy facility from the unit entrance affects the grinder utilization and the total cost (Figure 10). There were five trucks available under this scenario, with the distance to the bioenergy facility varying from 16 km (10 miles) to 113 km (70 miles). The results of the operation concluded that total cost increased by $20.83 BDMt-1 when changing the distance to the bioenergy facility from 16 km (10 miles) to 113 km (70 miles). As the distance to the facility increased, the number of cycles decreased due to the trucks not having enough time to return to the unit. It was observed that at the 16 and 32 km (10 and 20 mile) distance, the waiting time for the trucks increased as the interaction between trucks was more frequent upon arrival to the unit. On the other hand, the increased distance to the facility reduced truck interaction but limited the number of loads through the system. The grinder utilization under this scenario decreased from 79% (16 km, 10 miles) to 52% (113 km, 70 miles). Figure 10. View largeDownload slide Sensitivity analysis of total cost and grinder utilization to changes in the distance to the end facility under the self-steering trailer system. Figure 10. View largeDownload slide Sensitivity analysis of total cost and grinder utilization to changes in the distance to the end facility under the self-steering trailer system. Hook-lift trucks provide another way of utilizing forest harvest residues located in areas with limited road access. These smaller, more flexible trucks provide a way to access remote locations (Han 2008). Typically, the hook-lift truck application is used with a central location within or near the harvest unit and is limited by the distance the hook-lift truck must travel due to its small load and high cost per ton-mile. Harril et al. (2009) reported that the central location should ideally be less than 5 km (3 miles) from the harvest sites. An advantage of using a central location is the ability to draw from multiple harvest units, reducing the mobilization cost of the system. For example, the grinder does not have to move to each unit individually, but rather can remain at the central location. However, the central location can be limited if there is not enough space for the incoming forest residues. In most cases, the hook-lift application may require more equipment than other transportation systems, such as the self-steering system, increasing the total cost of the operation. For example, as the hook-lift trucks bring material to the central location, the trucks are limited as to how high the residues can be piled. A second loader may be required to arrange the material as it comes into the central landing to increase the efficiency of the grinder. Grinding can be completed as the material arrives or be delayed for later grinding. The grindings can be either processed directly into a standard chip van or piled. If the grindings are piled at the central location, then a wheeled loader is required to load the chip vans as they arrive. In the modeled hook-lift application, the costs include both the primary stage and secondary stage costs. The primary stage cost is the accumulation of the loader cost (in-woods loader + central area loader) and the hook-lift transportation cost. The in-woods loader was assumed to be continually moving and rearranging piles when not filling the setout bins for the hook-lift truck. Each bin was 40 cubic yards and had an average weight of 4.95 green metric tons (3.27 BDMt) and took 14 minutes to fill (Harril et al. 2009). The working time of the secondary loader at the central area is dependent on the distance it must travel to move the pile as well as the height of the pile. It was assumed that each load took 14 minutes to move and rearrange. The waiting time for the secondary loader was dependent on loader simulated operating time and scheduled shift time. Similar to the self-steering model, the hook-lift truck working time is dependent on its inter-arrival time, round-trip time, and number of cycles completed. Under the base case scenario, the truck waiting time is based on waiting time (if any) at the turnout before the loader. If a hook-lift truck arrives at the turnout and there is another truck already at the in-woods loader location, then the truck must wait until the other truck drops the empty bin, picks up the loaded bin, and then drives past the turnout location. The secondary stage cost is the sum of the processing and transportation costs. Like the self-steering system, the processing cost is dependent on the working and waiting times in a shift of the loader and grinder. The transportation cost is dependent on the average working and waiting times in a shift of the standard trailer multiplied by the number of trailers in the system. A 16.15 m (53 ft) standard trailer was used to transport the material to the bioenergy facility and was assumed to have a loading time of 32 minutes with a capacity of 28.34 green metric tons. Hook-Lift System PS = CL+ CHL (14) CL= (IWL+ (WL*HL) + (WTCL*YL)) / BDMt (15) CHL= ((WHL*HHL) + (WTCHL*YHL)*N) / BDMt (16) SS = Kp+ QT (17) Kp= (((WL+ WG)*HLG) + ((WTCL+ WTCG)*YLG)) / BDMt (18) QT =((WST*HST) + (WTCST*YST)*N) / BDMt (19) where PS  total cost for primary stage in a hook-lift application ($ BDMt-1) CL  total cost for loaders in hook-lift application ($ BDMt-1) CHL  total cost for hook-lift transportation ($ BDMt-1) IWL  total cost for in-woods loader in a hook-lift application ($) HL  working time for loader at central area in a hook-lift application ($ hr-1) YL  waiting time for loader at central area in a hook-lift application ($ hr-1) WHL  hourly working cost for hook-lift trucks ($ hr-1) HHL  working time for hook-lift trucks (hr) WTCHL  hourly waiting cost for hook-lift trucks ($ hr-1) YHL  waiting time for hook-lift trucks (hr) SS  total cost for secondary stage in a hook-lift application ($ BDMt-1) Kp  total processing cost at central area in a hook-lift application ($ BDMt-1) QT  total secondary stage transportation cost in a hook-lift application ($ BDMt-1) WST  hourly cost for a standard chip van in a hook-lift application ($ hr-1) HST  working time for a standard chip van in a hook-lift application ($ hr-1) WTCST  hourly waiting cost for a standard chip van in a hook-lift application ($ hr-1) YST  waiting time for a standard chip van in a hook-lift application (hr) A hook-lift truck application was modeled under the base case (Figure 7) to compare the total cost and efficiency of the system to the self-steering trailer. Under this scenario, only one harvest unit provided material to the central location, as opposed to Harril et al. (2009), which had multiple units providing material. It was assumed that the grinding application took place after all the harvest residues were brought to the central location and was directly processed into 16.15 m (53 ft) standard chip vans. At the central landing, there were three chip vans available, with the distance to the bioenergy facility set to 48 km (30 miles). A loader was needed in the woods to fill the setout bins for the hook-lift truck, with a second loader at the central location piling the residues as they were delivered. The round-trip time was much less for the hook-lift trailers as compared to the self-steering chip vans because the travel distance was shorter. A shorter round-trip time may increase the number of cycles during a shift, but can also increase machine interactions and therefore increase the system cost. A sensitivity analysis was done to look at the effect of the number of available hook-lift trucks to the total cost and efficiency (Figure 11). Results from the operation conclude that two trucks minimized the transportation cost ($53.40 BDMt-1) with 23 loads per shift delivered to the central area. The transportation cost for three trucks was $65.37 BDMt-1 delivering 24 loads to the central area. Having only one truck available was the more expensive option under this scenario, delivering 14 loads to the central area at a cost of $67.43 BDMt-1. From the central location to the facility, the transportation cost plus processing totaled $40.71 BDMt-1 for delivering 9 loads to the bioenergy facility. Figure 11. View largeDownload slide Total cost of the first and second stages in hook-lift truck system with variable number of trucks available. Figure 11. View largeDownload slide Total cost of the first and second stages in hook-lift truck system with variable number of trucks available. A sensitivity analysis was done to evaluate how altering the distance between the harvest unit and the central location affected the total cost and efficiency (Figure 12). Two hook-lift trucks were available to transport material with the same setup at the central location. The distance between the harvest unit and the central location varied from 1 to 4 miles. Total cost increased from $94.47 BDMt-1 (1.6 km or 1 mile) to $113.46 BDMt-1 (6.4 km or 4 miles), showing that the distance between the central location and harvest unit is an important factor in determining whether a hook-lift truck application will be more economical than the self-steering chip van. Figure 12. View largeDownload slide Sensitivity analysis of the total cost to changes in the distance to the central landing with the hook-lift truck system. Figure 12. View largeDownload slide Sensitivity analysis of the total cost to changes in the distance to the central landing with the hook-lift truck system. Mobilization and piling costs were added to account for total system costs. Mobilization cost is sensitive to the total amount of biomass transported to the bioenergy facility during the whole operation and not just under the shift duration. The piling cost is sensitive to the time a machine moved, rearranged, or touched harvest residues to prepare an area for the grinder operation and the total amount of biomass transported to the bioenergy facility. Under the base case scenario, it was assumed that 317 BDMt were moved, piled, and transported to a bioenergy facility. For the self-steering option, the processing and transportation costs were $46.03 BDMt-1, with a piling cost of $9.46 BDMt-1 and a moving cost of $4.54 BDMt-1. The total system cost for the self-steering trailer system option was $60.01 BDT-1. For the hook-lift truck application, a piling cost was not added, as the in-woods loader was assumed to be rearranging material in-between filling the setout bins. There was a higher mobilization cost for the hook-lift truck application ($6.80 BDMt-1) than the self-steering trailer option, because more equipment was needed with the same amount of biomass being transported to the bioenergy facility. The total processing and transportation cost under the hook-lift truck application was $94.47 BDMt-1, and after adding the mobilization cost the total system cost was $101.27 BDMt-1. At the landscape level, not all material will require a hook-lift truck. Some proportion of the landings could be accessible by a standard 13.72 m (45 ft) chip van, so that a grinder could be mobilized to the roadside landing. Thus, some combination of hook-lift trucks and standard trailers might be used. An analysis was completed to see how the total cost of the hook-lift system changes if a percentage of the transportation type was reserved for using a 13.72 m (45 ft) standard chip van with a capacity of 24.29 green metric tons (16.03 BDMt). The hourly cost for a 13.72 m (45 ft) chip van ($110.63 hr-1) was less than the self-steering chip van, and it is hypothesized that reserving some of the area for a standard trailer will reduce the hook-lift application total system cost. This is under the assumption that some of the area (changes with percent allocation) in the harvest unit is accessible using a standard chip van. Also, the same round-trip time was assumed for the standard chip van and the self-steered trailer. The self-steering trailer remained less expensive than the combination of hook-lift trucks and standard trailers (Figure 13) until the allocation for the hook-lift trucks was reduced to approximately 13% (87% allocation to the standard chip vans). Hook-lift trucks are sensitive to the distance they must travel as well as the carrying capacity of the bins. To evaluate the sensitivity of reducing the distance from the turnout to the grinder/loader and increasing the bin load, the hook-lift truck travel distance was reduced to 1.6 km (1 mile) and the specific gravity of material being transported (larger pieces, heavier species) was increased to 0.47. Under these assumptions, the self-steering system remained less costly ($55.34 BDMt-1) than the hook-lift/standard trailer application but the margin narrowed and the breakeven point was around 21% (Figure 14). The combined hook-lift/standard trailer combination system was not competitive with the self-steering system until the percentage allocation of the standard chip van was high enough to offset the limitation of having more equipment in the field and the limited capacity of the hook-lift trucks. Figure 13. View largeDownload slide Comparison of the total cost for the hook-lift truck + 13.7 m standard chip van combination to the self-steering trailer with regard to changing the percent allocation of the hook-lift truck. As hook-lift truck percent use (x-axis) decreases, the allocation of hook-lift trucks is reduced and standard chip van use increased. The analysis used the base case parameters. Figure 13. View largeDownload slide Comparison of the total cost for the hook-lift truck + 13.7 m standard chip van combination to the self-steering trailer with regard to changing the percent allocation of the hook-lift truck. As hook-lift truck percent use (x-axis) decreases, the allocation of hook-lift trucks is reduced and standard chip van use increased. The analysis used the base case parameters. Figure 14. View largeDownload slide Comparison of the total cost for hook-lift truck + 13.7 m standard chip van combination to the self-steering trailer with regard to changing the percent allocation of the hook-lift truck. As hook-lift percent use (x-axis) decreases, standard chip van use increased. Analysis was completed using the base case parameters, but reducing the distance from the turnout to the grinder/loader location and increasing the specific gravity of the harvest residues. Figure 14. View largeDownload slide Comparison of the total cost for hook-lift truck + 13.7 m standard chip van combination to the self-steering trailer with regard to changing the percent allocation of the hook-lift truck. As hook-lift percent use (x-axis) decreases, standard chip van use increased. Analysis was completed using the base case parameters, but reducing the distance from the turnout to the grinder/loader location and increasing the specific gravity of the harvest residues. Conclusion In recent years, there has been a push to use alternative sources for energy production. Forest harvest residues provide a promising option, but can be costly and difficult to obtain. Large chip van trailer access to reach harvest residues can be challenging, as roads were generally designed for trucks pulling stinger-steered log trailers. Field tests and modeling of the self-steering trailer system demonstrated that it can be competitive with other transportation options. The self-steering trailer required less area to turn on road intersection type turnarounds as well as landing-based turnarounds. For the landing-based turnarounds, a 16 × 24 m (53 × 80 ft) area should be adequate to turn around a self-steering trailer with an 18 × 27 m (60 × 90 ft) area being adequate to turn around a standard trailer. For the road intersection type turnarounds, the self-steering trailer could successfully turn around in areas that were too limiting for the standard trailer. Pairing a 6x6 truck with the self-steering trailer allowed the vehicle to navigate off-road, giving it more room if needed. Under the type of road conditions tested out in the field, the average turnaround time for the self-steering trailer was around 4 minutes. Arena Simulation by Rockwell Automation was used to model the self-steering system against a hook-lift application to compare their cost-effectiveness on a total system cost BDMt-1 basis. The simulation was used to derive working and waiting machine times. A cost model was created to calculate an hourly machine cost to determine the total system cost when considering working and waiting times. Under the base case scenario, the self-steering trailer system was lower in cost than the hook-lift truck application, with a total system cost, including mobilization and piling, of $60.01 BDMt-1. The hook-lift truck application total cost was $101.27 BDMt-1. Assuming a 13.72 m (45 ft) standard trailer could access a percentage of the harvest unit, the hook-lift/standard trailer combination system was not competitive under the base case scenario until the percent allocation for the hook-lift trucks was reduced to about 13%. After favoring the hook-lift application by reducing the distance to 1.6 km (1 mile) from the turnout to the grinder/loader and increasing the specific gravity of the material to 0.47, the self-steering system was still more cost-effective until the allocation for hook-lift trucks was reduced to about 21%. Acknowledgments This research was funded by the Northwest Renewables Alliance (NARA). NARA is supported by the Agriculture and Food Research Initiative Competitive Grant 2011-68005 30416 from the US Department of Agriculture, National Institute of Food and Agriculture. Literature Cited Ackerman , P. , E. van der Merwe , and R. Pulkki . 2017 . A South African softwood sawtimber supply chain case study . 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Copyright © 2018 Society of American Foresters This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - Improving Large Trailer Access for Biomass Recovery in Steep Terrain
JF - Forest Science
DO - 10.1093/forsci/fxx020
DA - 2018-08-01
UR - https://www.deepdyve.com/lp/springer-journals/improving-large-trailer-access-for-biomass-recovery-in-steep-terrain-jropYFXt9m
SP - 429
EP - 441
VL - 64
IS - 4
DP - DeepDyve
ER -