Sessions John, PhD. Prof.

Storm damages result in serious losses in many regions, primarily by stem breakage or blowdown. Extraction of storm-damaged trees often requires more difficult than normal skidding activities due to obstacles created during the storm. In this study, the productivity of a portable winch was evaluated as a possible alternative to recover storm-damaged timber. Field measurements were conducted in the Alabarda Forest Enterprise Chief located near the city of Kütahya in western Turkey, where storm damage often occurs during the winter season. The time study was implemented in two slope classes (35% and 55%) and two skidding distances (40 m and 60 m). All timber was skidded uphill. A regression mode was developed that related productivity to log volume, ground slope and skidding distance. The highest percentage of total cycle time was observed for skidding logs to the landing. The highest productivity (3.96 m3/hour) was found at the shorter skidding distance (40 m) and the lower ground slope (35%). Statistical analyses indicated that productivity was most highly affected by log volume, followed by skidding distance and ground slope. Larger log loads increased productivity, while both longer skidding distances and steeper slopes reduced productivity.

Forest roads are the key infrastructures that provide access to forest areas for sustainable management, protection, and utilization of forest resources. In order to benefit from the important functions of forest roads, they should be built in with adequate technical road standards. The road network with low technical standards require more frequent major repairs to ensure continues access to forest resources. In addition, only small trucks with low load capacity can move on the low standard roads. Furthermore, the low road standards limit the truck speed that increases vehicle travel time. These negative effects increase the transportation costs which are an important part of the timber production costs in Turkey. Thus, improving the road standards and developing forest transportation planning should be evaluated together in the most appropriate way. Large logging trucks with high load capacity are generally preferred for efficient transportation of wood-based forest products. In Turkey, large logging trucks, however, cannot operate on the most of the forest roads because insufficient technical road standards (road width, curve radius, surface materials, road structures) limit the maneuverability of large logging trucks. In this study, the objective is to determine the effects of improving forest road standards on total net profit of forest products by using the NETWORK 2000 program, a heuristic approach for solving forest transportation problems. Three Forest Enterprise Chiefs (FECs) located in Mustafakemalpaşa Forest Enterprise Directorate (FED) in Bursa Forest Regional Directorate were selected as the study area. The digital data layers for forest road network was generated by using ArcGIS 10.4 software. In the solution process, firstly, the optimum routes that minimize the transportation cost and maximize the total net profit of forest products on existing forest road networks were investigated for a truck type (15 ton) currently used in the region. In the second case, forest transportation was planned for the high load capacity truck (29 ton) moving on the forest roads with improved standards. In the first case, the transportation costs and annual major repair costs were considered in the calculation of the net profit of forest products, while one time cost of road improvement activities (i.e. road improvement construction, road structure installation, road surface construction) and annual maintenance costs were considered along with transportation costs in the second case. In both cases, the costs of other forest operations (i.e. felling, logging, etc.) were not considered since it was assumed that they do not vary with the forest transportation alternatives. As a result of the transportation plan developed for high load capacity truck, the annual transportation cost decreased by 46.85% comparing to the local logging trucks with low load capacity. Using improved road standards, the total road costs computed for the time period of 30 years (i.e. the average expected life cycle of forest roads) were reduced by 4.64%. The total net profit of forest products transported by using a high load capacity truck was 473,340 Euro more than that of using low load capacity truck on the existing forest road network. Thus, improving road standards might result in some additional costs in the road construction stage, but total net profit of forest products increase since transportation costs along with maintenance and repair costs considerably decrease in the long term.

As mechanization increases, the percentage of the total cost of the logging operation due to equipment purchase and operation increases. This makes assumptions about machine life, machine maintenance costs, and fuel consumption more critical in understanding the costs of logging operations. For many years machine rate calculations have followed a fixed format based on the concept of scheduled and productive machine hours. When equipment utilization is less than 100%, the traditional machine rate calculation assumes that the machine continues to depreciate and machine wear occurs during the non-productive time at the same rate as during the productive time. This can lead to overestimates of the hourly cost of machine operation by effectively shortening the machine lifetime productive hours as the utilization decreases. The use of inflated machine rates can distort comparisons of logging systems, logging strategies, equipment replacement strategies, and perhaps the viability of a logging operation. We propose adjusting the life of the machine to account for non-productive time: machine life in years should be increased with a decrease in machine utilization, while cumulative machine life in hours remains the same. Once the life has been adjusted, the traditional machine rate calculation procedure can be carried out as is normally done. We provided an example that shows the traditional method at 50% utilization yielded a machine rate per productive hour nearly 30% higher than our modified method. Our sample analysis showed the traditional method consistently provided overestimates for any utilization rate less than 100%, with lower utilization rates yielding progressively increasing overestimates. We believe that our modified approach yields more accurate estimates of machine costs that would contribute to an improved understanding of the machine costs of forest operations.

In this paper, we introduce a Microsoft Excel Workbook containing the software Equipment Selection Problem DS (ESPDS) that recognizes the special structure of the equipment selection problem. The ESPDS approach is based on the context of the Brazilian forestry sector using detailed equipment maintenance schedules. No special restrictions are needed on cost inputs over time or technologies. The output is an equipment schedule that can be used to project equipment investment needs, operational costs, and tree harvesting costs. ESPDS can be applied to support companies and contractors in order to choose the best option for their operations, as well as to achieve better equipment purchase agreements. We will show how ESPDS will also be useful in providing longer term estimates of production costs. The sensitivity analysis shows how different inputs and maintenance polices can affect the best alternative. A numerical example is included considering the entrance of a specific technology that increases the equipment productivity in order to examine whether it can change the solution. ESPDS is intuitive, flexible, and easy to calculate. Although designed for the forestry industry, the approach is readily transferable to other sectors. ESPDS may be found on the web at the following URL: https://www.researchgate.net/publication/350811380_ESPDS_workbook.

Harvest from plantations can provide both industrial wood and forest residues for bioenergy, including stumps. The literature suggests that the choice of cutting system can affect the division between industrial wood recovery and remaining stump volume. In this study, two felling techniques - motor-manual chainsaw and feller-buncher, were compared based on stump-height-related timber value loss for four ground slope classes: high, medium, low, and flat. The economic value loss of wood material for three products - sawlogs, pulpwood, and fiber-chip wood, was determined based on the estimated volume of stumps left in the woods. The results indicated that the average stump height for the motor-manual chainsaw and feller-buncher was 17.16 cm and 8.69 cm. The economic value loss of wood material per stump was higher in felling by manual chainsaw as compared to the feller-buncher operation (log: €0.60­, paper wood: €0.29­, fiber-chip: €0.15­). However, volume loss due to high stumps could contribute to wood for bioenergy if stumps are subsequently removed. Additional research is needed to evaluate the benefits and costs of stump removal for bioenergy as part of a total supply chain to provide both industrial wood and wood for bioenergy.

A dynamic programing algorithm to identify schedules that minimize the discounted cost (DC) of logging machines over a planning horizon including gains from technological progress was used. The identified schedules were also compared with three alternative replacement policies derived from the literature and Brazilian forestry companies. The case study used a harvester and a forwarder and a 100-year planning horizon, where the maximum replacement limit was 8 years. To apply the dynamic programing algorithm, it was necessary to generate lists from cash flows, which incorporated the possible replacement combinations of a series of machines according to the length of the planning horizon and the maximum replacement limit. The lists were formed by three descriptors: predecessor node (moment of purchase of the machine), future node (point of sale for the acquisition of a new machine), and arc value (DC information, the mean production cost and mean production). The results show that the DC identified for the series of harvester replacements was higher compared to the forwarder. It was also identified that the harvester's economic life is shorter, and with technological progress, there was a reduction in the economic life of both machines. Technological progress was also responsible for reducing the average production cost and increasing the average production of machines. When comparing the alternative schedules (AS), it was found that, although AS had a higher DC value and mean production costs, there was very little difference between them. In the harvester's case, AS01 had the highest DC value ($4.36 million). By choosing it, the decision maker would bear a DC boost of $54,000, while AS02 and AS03 would trigger an increase of $43,000 and $32,000, respectively. For the forwarder, the schedule with the highest DC value was AS03 ($3.69 million). The postponement of the replacements made in alternative schedule 01 and alternative schedule 02 resulted in an increase in the DC of $5000, while the anticipation of the replacements made in the alternative schedule 03 resulted in an increase of $48,000. The aspect that stood out the most, in relation to the results presented, was the small variation that the alternative schedules presented in relation to the schedules obtained using the dynamic programing algorithm. With a DC variation of less than 1.4%, the results lead us to conclude that the decision maker will not suffer much harm in choosing any of the alternative schedules tested.

Range is a primary issue regarding the adoption of battery-electric vehicles. In-shift charging offers an alternative to extending range without the need for a heavier, more expensive battery. This paper recognizes that daily log truck productivity is a result of a small number of discrete events (loads delivered to a demand point). Delays such as in-shift charging become very important if they result in a lost load. If n is the number of loads a truck can deliver in a day without delays from in-shift charging, then the expected number of loads a truck can deliver with in-shift charging delays is n-1 + prob, where prob is the probability of completing the last load. The choice between a larger battery capable of a full day’s operation and a smaller battery that requires in-shift charging is formulated as a breakeven problem. Solving for the value of prob where the net revenue earned by the larger battery truck is equal to the net revenue earned by the smaller battery truck provides a battery size decision-point. Conducting a sensitivity analysis, the three factors that had the greatest impact on battery size selection were the hauling rate ($/tonne), the difference in net load, and the difference in depreciation cost between the large and small battery trucks.