Productivity of harvesters and forwarders in CTL operations in Northern Sweden based on large follow-up datasets
... roundwood volume m 3 per 100 m of strip-road [m 3 ·(100 m) -1 ], is clearly the most important factor influencing forwarding productivity (Grönlund, Eliasson 2019;Hildt et al. 2020). Moreover, assortment type, the number of assortments, mean log volume, mean stem volume, number of logs per load, load-size, ground slope (if steep), and extraction distance have also been found to affect forwarding productivity (Nurminen et al. 2006;Eriksson, Lindroos 2014;Strandgard et al. 2017;Cadei et al. 2020;Hildt et al. 2020). The unit of observation in forwarding studies is typically a load (Strandgard et al. 2017;Cadei et al. 2020;Hildt et al. 2020), but it can also be a stand (Eriksson, Lindroos 2014). ...
... Moreover, assortment type, the number of assortments, mean log volume, mean stem volume, number of logs per load, load-size, ground slope (if steep), and extraction distance have also been found to affect forwarding productivity (Nurminen et al. 2006;Eriksson, Lindroos 2014;Strandgard et al. 2017;Cadei et al. 2020;Hildt et al. 2020). The unit of observation in forwarding studies is typically a load (Strandgard et al. 2017;Cadei et al. 2020;Hildt et al. 2020), but it can also be a stand (Eriksson, Lindroos 2014). ...
... Usually, forwarding productivity during thinning and clearcutting is modelled separately, both in boreal forests and beyond (Nurminen et al. 2006;Eriksson, Lindroos 2014;Proto et al. 2018). That said, unlike harvester work during typical boreal thinning operations, forwarding does not require tree-selection decisions from the operator. ...
Citation: Manner J., Ersson B.T. (2023): A pilot study of continuous cover forestry in boreal forests: Do remaining trees affect forwarder productivity? J. For. Sci., 69: 317-323. Abstract: According to the literature, forwarding productivity depends chiefly on log concentration, the number of assortments , mean log volume, load-size, slope, and extraction distance. However, there is not much scientific knowledge available on forwarding in continuous cover forestry (CCF) in boreal forests, nor whether the presence of remaining trees actually affects forwarding productivity. Thus, the objective of our study was to isolate the effect of remaining trees (i.e. stand density) on forwarding productivity during CCF, specifically selection cutting. The results showed that productivity was explained mainly by the log concentration, while other factors had at most minor effects. Most importantly, stand density did not significantly affect forwarding productivity, ceteris paribus. Thus, we conclude that remaining trees do not affect forwarding productivity in boreal forests. Although the study results from this CCF operation must only be cautiously applied to even-aged forestry, our results raise a general question: do we need separate productivity models for thinning and clearcut operations in boreal forests if remaining trees (stand density) do not affect forwarding productivity? Because of the small dataset, we consider our paper to be a pilot study whose findings need to be verified by studies based on larger datasets including several operators and stands.
... Productivity is further influenced by the approaching distance and the size of the load [12,13,14]. Other factors affecting productivity may include trunk volume [15] and number of assortments [11,16,17], terrainrelated factors such as terrain slope [18,19]. Last but not least, these factors can include work organization factors [20] and technical parameters such as the load capacity of the used machine [17,21]. ...
... Other factors affecting productivity may include trunk volume [15] and number of assortments [11,16,17], terrainrelated factors such as terrain slope [18,19]. Last but not least, these factors can include work organization factors [20] and technical parameters such as the load capacity of the used machine [17,21]. ...
This work deals with finding out whether the heart rate values of operators of forwarding machines during the work shift are influenced by the individual activities that the operator has to perform during timber skidding, or by the operators themselves. Furthermore, the work deals with determining the difficulty of individual activities in terms of physical load. For this purpose, the work shift of operators carrying out timber skidding was divided into individual activities: Driving, Maintenance, Forwarding, Break. During these work activities, the heart rate of each operator was taken for subsequent evaluation. The results show that the highest pulse rates of the operators were achieved during the Maintenance of the entrusted machine, while the highest pulse fluctuations in the operators were recorded during Forwarding. As part of this activity, the highest heart rate of the entire measurement process was recorded (132.0000 bpm), but also the lowest (42.0000 bpm). Furthermore, it was proven that both the operator and the activity he performs affect the pulse rate. The activities themselves did not differ from each other in only one of the six cases of comparison. Specifically, it was Driving and Forwarding.
... Productivity is further influenced by the approaching distance and the size of the load [12][13][14]. Other factors affecting productivity may include trunk volume [15] and number of assortments [11,16,17], and terrain-related factors such as terrain slope [18,19]. Last but not least, work organization factors [20] and technical parameters such as the load capacity of the used machine may also affect productivity [17,21]. ...
... Other factors affecting productivity may include trunk volume [15] and number of assortments [11,16,17], and terrain-related factors such as terrain slope [18,19]. Last but not least, work organization factors [20] and technical parameters such as the load capacity of the used machine may also affect productivity [17,21]. ...
The aim of this work was to determine the dependence of the heart rate of operators of forwarding machines on the activities performed during the working day within the framework of timber forwarding and to compare individual activities in terms of the level of physical workload. For this purpose, the work shift of operators carrying out timber forwarding was divided into individual activities: driving, maintenance, forwarding, and break. During these work activities, the heart rate of each operator was taken for subsequent evaluation. A portable device, a Garmin smartwatch, was used to measure their heart rate. The results show that the highest pulse rates of the operators occurred during the maintenance of the entrusted machine, while the highest pulse fluctuations were recorded during forwarding. During this activity, the highest heart rate of the entire measurement process was recorded (132.0000 bpm), but also the lowest (42.0000 bpm). Furthermore, it was proven that both the operator and the activity he performs affect the pulse rate. The activities themselves did not differ from each other in only one of the six cases of comparison, specifically, between driving and forwarding.
... Linking unit costs and the volume of merchantable timber in a tree characterizes the variability of the harvesting process well (Eriksson & Lindroos 2014). The observed logarithmic relationships of these variables, visible in our experiment, are consistent with the data published by Lazdiņš et al. (2016). ...
The aim of the study was to determine the unit costs of mechanized timber harvesting in pine stands where early thinning was being performed, and to determine the relationship between the cost level and the volume of harvested trees, the harvester model and field conditions. Analysis focused on timber harvesting with the use of small- and mid-sized harvesters. The tested harvesters were specialized forestry machines (Vimek, Sampo, Profi-Pro, Ponsse) and a construction machine (Fao-Far). Terrain accessibility variants were distinguished in relation to furrows between which trees had been planted in the past: flat terrain with the depth of unevenness up to 20 cm, up to 40 cm, and over 40 cm. The operating costs of the analyzed harvesters varied significantly, an hour of operation of the machine that was the cheapest to use (Fao-Far) cost nearly 2.5 times less (37.3 €) than the Profi-Pro harvester, which was the most expensive in operation (89.1 €). In stands without furrows, the lowest unit costs were noted for the Sampo harvester: 8.4 €·m-3. The other small harvesters, Vimek and Fao-Far, were slightly more expensive to use: 10.3 €·m-3 and 9.1 €·m-3, respectively. In areas where furrows were up to 20 cm deep, the cheapest solution was timber harvesting with the Fao-Far harvester (9.9 €·m-3). In areas where furrows were up to 40 cm deep, timber harvesting was the cheapest with the Sampo harvester (10.7 €·m-3), while harvesters Vimek and Fao-Far were characterized by a similar cost intensity, amounting to just over 12 €·m-3. In stands with furrows deeper than 40 cm, it was cheapest to use the Ponsse harvester (10.4 €·m-3). The cost of operation of the Profi-Pro harvester was higher by approx. 25% (14.0 €·m-3). With the current level of the financing of mechanized timber harvesting in Poland (about 11 €·m-3), small harvesters Vimek, Sampo and Fao-Far are cost-effective when single tree volume exceeds 0.05-0.06 m3. Medium harvesters, Profi-Pro and Ponsse, are cost-effective when unit volumes of harvested trees reach 0.08 and 0.11 m3 respectively. The cost-effectiveness of the tested harvesters increased when working shifts were extended.
... The literature has discussed the use of machine learning for predicting the productivity of forest machines used in mechanized timber harvesting. Eriksson and Lindroos [23] trained machine learning models to estimate the productivity of harvesters and forwarders. Estimation accuracy was higher for harvesters. ...
Tactical planning in timber harvesting involves aspects related to forest macro-planning and, particularly, the allocation of resources and sequencing of activities, all of which affect the allocation of timber in forest yards and roads and the productivity of forest machines. Data-driven approaches encourage the use of information obtained from data to enhance decision-making efficiency and support the development of short-term strategies. Therefore, our investigation was intended to determine whether a data-driven approach can generate sufficient input for modeling forwarder productivity in timber forwarding in Pinus and Eucalyptus planted forests, to support tactical planning. We utilized 3812 instances of raw data that were generated over a 36-month period. The data were collected from 23 loggers who operated in Pinus and Eucalyptus planted forests. We applied 22 regression algorithms that applied a supervised learning method from an experimental machine learning approach to the data instances. We evaluated the fitted models using three performance metrics. Out of the tested algorithms, the default mode of light gradient boosting produced a root mean squared error of 14.80 m3 h−1, a mean absolute error of 2.70, and a coefficient of determination of 0.77. Therefore, data-driven methods adequately support forwarder productivity modeling in timber forwarding in planted forests and help forest managers with tactical planning.
... In Scandinavian countries such as Sweden and Finland, CTL technology is largely dominant, with harvesters and forwarders extensively used to manage the large extensions of coniferous stands [43]. In central Europe, in countries such as Poland, Slovakia, and Germany, CTL technology is largely applied in coniferous stands, while skidding via cable or grapple skidders is very common in the management of broadleaf forests [40]. ...
Precision forestry is a useful technique to help forest stakeholders with proper sustainable forest management. Modern sensors and technologies, with special reference to the sustainability of forest operations, can be applied on a variety of levels, including the monitoring of forest activities regarding the three pillars (economy, environment, and society). In this review, we summarised the current level of knowledge regarding the use of precision forestry techniques for monitoring forest operations. We concentrated on recent data from the last five years (2019-2023). We demonstrated how an Industry 4.0 strategy for remote and proximal monitoring of working performance can be effective when using CAN-bus and StanForD data collected by modern forest machines. The same information can be effectively used to create maps of soil trafficability and to evaluate the patterns of skid tracks or strip roads built as a result of forest intervention. Similar information can be gathered in the case of small-scale forestry by using GNSS-RF (Global Navigation Satellite Systems-Radio Frequency) or even monitoring systems based on smartwatches or smartphones. LiDAR and Structure for Motion (SfM) photogrammetry are both useful tools for tracking soil rutting and disturbances caused by the passage of forest machinery. SfM offers denser point clouds and a more approachable method, whereas laser scanning can be considerably faster but needs a more experienced operator and better data-processing skills. Finally, in terms of the social component of sustainability, the use of location sharing technologies is strongly advised, based for instance on GNSS-RF to monitor the security of forest workers as they operate.
... • compact class forwarder [22][23][24], middle class [25][26][27][28][29] and large forwarder [17; 30; 31]; ...
Latvia is one of the leaders in production and use of forest biofuel in Europe. The rapid increase of forest biofuel market raises questions about sustainability of the supply chains and contribution of the forest biofuel produced in Latvia to the climate change mitigation. Sustainability of forest biofuel is addressed in multiple recent international political initiatives; particularly, the European 2030 climate and energy package and the nature restoration regulation. Climate change mitigation potential of forest biofuel is surrounded by multiple speculations, which have to be addressed by comprehensive evaluation of greenhouse gas (GHG) emissions due to production and delivery of forest biofuel. According to the study results, average GHG emissions due to delivery of harvesting residues from the state forests correspond to 1.4 kg CO2 eq GJ-1, including forwarding, comminution and delivery to a 68 km distance. This is significantly less than the default values provided in the regulation (EC) 2018/2001, particularly during the delivery of forest biofuel. GHG emissions due to delivery of forest biofuel from removal of vegetation in abandoned farmlands are 1.9 kg CO2 eq GJ-1, from forest drainage ditches – 1.7 kg CO2 eq GJ-1, from pre-commercial thinning – 2.1 kg CO2 eq GJ-1. Estimation of the GHG emissions is complicated by limited information on some of the sources and productivity. Building of the system for collection of activity data is a crucial task for transparent demonstration of GHG emissions and the effect of applied mitigation measures.
... Harvester productivity in final felling is about 24 m 3 /PMH (productive machine hours), while the mean productivity of forwarders is 21.4 m 3 /PMH ( Eriksson and Lindroos 2014). Moreover, large forwarders currently on the market carry around 20 tonnes of load ( Komatsu 2022, PONSSE 2022, indicating that the productivity of current forest machines is actually quite high, and as such the insufficient production capacity of the machinery no longer hinders further improvements in production efficiency. ...
To further develop forest production, higher automation of forest operations is required. Such endeavour promotes research on unmanned forest machines. Designing unmanned forest machines that exercise forwarding requires an understanding of positioning and angle estimations of logs after cutting and delimbing have been conducted, as support for subsequent crane loading work. This study aims to improve the automation of the forwarding operation and presents a system to realize real-time automatic detection, positioning, and angle estimation of harvested logs implemented on an existing unmanned forest machine experimental platform from the AORO (Arctic Off-Road Robotics) Lab. This system uses ROS as the underlying software architecture and a Zed2 camera and NVIDIA JETSON AGX XAVIER as the imaging sensor and computing platform, respectively, utilizing the YOLOv3 algorithm for real-time object detection. Moreover, the study combines the processing of depth data and depth to spatial transform to realize the calculation of the relative location of the target log related to the camera. On this basis, the angle estimation of the target log is further realized by image processing and color analysis. Finally, the absolute position and log angles are determined by the spatial coordinate transformation of the relative position data. This system was tested and validated using a pre-trained log detector for birch with a mean average precision (mAP) of 80.51%. Log positioning mean error did not exceed 0.27 m and the angle estimation mean error was less than 3 degrees during the tests. This log pose estimation method could encompass one important part of automated forwarding operations.
Designing an optimal machine trail network is a complex locational problem that requires an understanding of different machines’ operations and terrain features as well as the trade-offs between various objectives. With the overall goal to minimize the operational costs of the logging operation, this paper proposes a mathematical optimization model for the trail network design problem and a greedy heuristic method based on different randomized search scenarios aiming to find the optimal location of machine trails —with potential to reduce negative environmental impact. The network is designed so that all trees can be reached and adapted to how the machines can maneuver while considering the terrain elevation’s influence. To examine the effectiveness and practical performance of the heuristic and the optimization model, it was applied in a case study on four harvest units with different topologies and shapes. The computational experiments show that the heuristic can generate solutions that outperform the solutions corresponding to conventional, manual designs within practical time limits for operational planning. Moreover, to highlight certain features of the heuristic and the parameter settings’ effect on its performance, we present an extensive computational sensitivity analysis.
Extraction of timber is expensive, energy intensive, and potentially damaging to the forest soil. Machine development aims to mitigate risks for environmental impact and decrease energy consumption while maintaining or increasing cost efficiency. Development of rubber-tracked forwarders have gained renewed interest, partly due to climate change leading to unreliable weather, and the urgency of reducing emissions. The increased cost of rubber-tracks compared to wheels are believed to be compensated by higher driving speeds and larger payloads. Thus, the aim of this study was to theoretically investigate how productivity and cost efficiency of rubber-tracked forwarders can exceed that of wheeled equivalents. The calculations were made with fixed parameters, to evaluate performance in different conditions, and with parameters from 2 500 final felling stands in central Sweden, to evaluate performance in varied working conditions. Scenarios were compared to a baseline corresponding to mid-sized wheeled forwarders. The results show higher productivity with the increased driving speed and load weight enabled by rubber-tracks at all extraction distances, with larger differences at long extraction distances. Assuming 15% higher machine price for the rubber-tracked forwarder, increased speed and load weight lead to 40% cost reduction for 400 meters extraction distance. Furthermore, a rubber-tracked forwarder is likely to give access to a larger part of the harvest areas during longer seasons. The year-round accessible volumes are estimated to increase from 9% to 92% with a rubber-tracked forwarder. With rubber-tracks, good accessibility can be combined with low soil impact in a favourable way for both industry and ecosystem.
Non-linear models with heteroscedasticity are commonly used in forestry modeling, and logarithmic regression and weighted regression are usually employed to estimate the parameters. Using the single-tree biomass data of large samples, the bias correction in logarithmic regression and comparison with weighted regression for non-linear models are studied in this paper. The immanent cause producing bias in logarithmic regression is analyzed, and a new correction factor is presented with which three commonly used bias correction factors are examined together, and the results show that the correction factors presented here and by Baskerville (1972) should be recommended which could insure the corrected model to be asymptotically consistent with that fitted by weighted regression. Sec-ondly, the fitting results of weighted regression for non-linear models, using the weight function based on residual errors of the model estimated by ordinary least squares (OLS) and the general weight function (W = 1/f(x)2) pres-ented by Zeng (1998) respectively, are compared with each other that show two weights works well and the general function is more applicable. It is suggested that the best way to fit non-linear models with heteroscedasticity would be using weighted regression, and when the total relative error of the estimates from the model fitted by the general weight function is more than a special limit such as ±3%, a better weight function based on residual errors of the model fitted by OLS should be used in weighted regression.
It is well-known that machine operators vary in their performance when undertaking mechanized forestry harvesting operations. Nevertheless, the human factor is still largely disregarded in productivity calculations. In the present study, operator performance is evaluated by analysing archived production data collected automatically by computers on-board single grip harvesters driven by 32 operators working in 3,351 stands over a period of three years. The experimental conditions were all approximately the same. The effect of the operators is modelled by a multilinear regression analysis. Seventeen operators were found to have performance levels that differed significantly from the mean model. Together, ‘tree volume’ and ‘operator’ explained 84% of the overall variance. However, since 37.3% of the variance in productivity is explained by the operator, the influence of the operator on productivity is quite large. The minimum and maximum significant mean productivity values for all the operators differed by a factor of 2.2, which reduced to a factor of 1.8 if only data from experienced operators were analysed, although this still demonstrates that the best operators are nearly twice as productive as the worst. The operator, therefore, has an important influence on productivity and should be considered a key factor in productivity models.
Forwarding has been carried out for 50 years, but much is still unknown about this work. Its complexity comes from both stand features and essential decision-making. Forwarding time consumption is influenced by e.g. log concentrations and number of assortments. Traditionally, focus has been on the total log concentration (TLC), referring to all logs at the harvesting site. However, we focused on forwarded log concentration (FLC), the load-specific log concentration which depends on the assortment distribution at harvesting site and the load-specific number of assortments. To evaluate the effects of TLC, number of assortments in a load and FLC on the loading and unloading times, a standardized field experiment was carried out. Pile and load sizes were constant, while TLC and FLC were manipulated by varying the pile distribution on the test path. For all work elements, the time consumption per m3 was significantly affected by the number of assortments that were loaded, but only the "driving while loading" work element was also significantly influenced by TLC. However, when untangling the intercorrelation between tested factors, it was found that the time consumption for driving while loading significantly decreased as a function of FLC and was unaffected by the number of assortments in a load. That FLC influences the forwarding time consumption highlights the need to study the effects of combining various assortment proportions in a load. Such knowledge will enable analysis of the most efficient number and assortment proportions to combine in the various loads required to forward a given stand.
Harvesting equipment productivity studies have been conducted in many countries around the world spanning over 25 years. These studies have shown that many factors influence individual machine productivity. These factors include stand and site conditions, equipment configuration, management objectives, and operator experience. Productivity can increase or decrease with slight changes in any of these factors. This literature review also highlights the variety of experimental designs and data collection methods encountered in a cross section of those studies. It further shows the variation in species composition, stand density, tree diameter, and harvest prescription. Although studies that include the influence of operator performance on harvest equipment productivity are limited, they were included in this review where appropriate and available. It is clear that productivity equations should be developed using population-level data with several operators. Some studies were conducted in stands similar to Maine, but they used harvesting equipment that is not commonly used in logging operations in this state. Therefore the applicability of existing studies to the logging industry in Maine, USA, is very limited. Our conclusion is that in order to accurately predict harvesting productivity it is necessary to develop regional harvesting productivity equations using harvesting equipment commonly used in Maine. Forest operations researchers in other regions will be able to use this summary to explore the difficulty of applying productivity information to regional logging operations.
Machines with lower investment and operating costs can be one solution in solving the harvesting costs problem of first thinnings. The long-term productivity of thinning harvesters and harvester-forwarders was investigated in a joint project between Finnish research institutions. In the follow-up study, three harvester-forwarders and five thinning harvesters were studied. The total harvested volume was almost 30000 m³.
The work performed by harvester-forwarders includes both cutting and forwarding. The average productivity of a harvester-forwarder varied from 3.81 m³/E15 hours in first thinnings to 7.87 m³/E15 hours in regeneration cuttings. The productivity was calculated for a 250 m forwarding distance. Average stem size of the stand, removal per hectare, and number of timber assortments were the factors affecting productivity when the forwarding distance was standardized. The productivity of thinning harvesters varied from an average of 6.92 m³/E15 hours in first thinnings to 16.18 m³/E15 hours in clear cuttings. Some of the harvesters were well capable in small dimensioned clear cuttings, the smallest machines being solely designed for thinnings.
Harvesting costs were compared at the harvesting system level. The costs of a medium–sized forwarder were added to the costs of harvesters. Cost data for the widely used medium–sized harvester system were added to the comparisons made for the forwarding distance of 250 metres. The thinning harvester system had the lowest costs for both two and five timber assortments. In the case of five assortments, which is the typical number in thinnings in Finland, the medium–sized harvester system had lower costs than the harvester–forwarder above a stem size of 60 dm³. At an average stem size of 200 dm³ the difference between the harvester systems was minimal. In the case of two assortments, the competitiveness of the harvester–forwarder was better, and below a stem size of 100 dm³ its costs were lower and between 100–200 dm³ at the same level as for the medium-sized harvester system. The thinning harvester system was still the cheapest alternative.
Thinning harvesters and harvester-forwarders are interesting alternatives for thinnings. The high capacity and all the properties of medium-sized harvesters cannot be fully exploited in thinnings. Thus machinery with lower capital costs and reasonable productivity can be competitive. Some of the studied machines can be used effectively in clear cuttings with a reasonable stem size. The harvester-forwarder is an interesting type of machine that is currently undergoing rapid development. The harvester-forwarder is most competitive in small stands with a short forwarding distance.
Time and productivity data were collected on 12 different models of rubber-tired, grapple skidders transporting southern pine. Of the 495 cycles studied, 416 loads were accumulated from bunched trees with the remaining 79 loads accumulated from scattered trees. For 338 cycles, tree limbs were removed with a gate delimber. Equations to predict elemental and total cycle times were developed from five independent variables. Load weights and travel loaded speeds were also compared.
The authors developed a general productivity model for the harvesters and processors currently used in Italy. The model consists of a set of mathematical relationships that can estimate the productivity of these machines under the whole range of specific work conditions faced in Italy. Such relationships can provide general directions to prospective users and can contribute to the development of scenario predictions. The original data pool contained more than 15,000 individual timestudy records, each representing a single harvesting cycle (most often one tree). The records were extracted from 38 studies conducted with the same methods and by the same principal investigators between 1998 and 2008. Statistically significant models were developed for all cyclic work phases, such as moving, brushing, felling, and processing. Accessory time and delay time were added as percent factors, also estimated from the same studies. Model development aimed at achieving the best compromise solution between accuracy and easy use, avoiding the introduction of an excessively large number of input variables. Selected independent variables were tree volume, tree species, task type (harvesting or processing), machine power and type, density of residual stand and of harvest trees, stand type, and slope gradient. These models could predict a large proportion of the variability in the data and were successfully validated using reserved cycle records, extracted from the same data pool and not used for model development. Comparison with similar Nordic and German standards confirmed the sound structure of the Italian models while highlighting the need for specific productivity norms due to the different work conditions faced by Italian operators.