SILVA Silva Balcanica 22(2): 81-90 (2021) BALCANICA doM10-3897/silvabaleanica.22.669240 RESEARCH ARTICLE Predicting productivity of timber loading operations: a literature review Mohammad Reza Ghaffariyan Forest Industries Research Centre, University of the Sunshine Coast, Locked Bag 4, Maroochydore DC, Queensland Corresponding author: Mohammad Reza Ghaffariyan (mghaffar@usc.edu.au; ghafari901@yahoo.com) Academic editor: Ivaylo Markoff | Received 28 May 2021 | Accepted 26 August 2021 | Published 20 October 2021 Citation: Ghaffariyan, M. R. (2021) Predicting productivity of timber loading operations: a literature review 22(2): 81-90. https://doi.org/10.3897/silvabalcanica.22.e69240 Abstract Loading is considered a bottleneck of the forest harvesting system as it acts as a connection between primary transport and secondary transport (from roadside/ landing to mills or central yards). Any delay during the loading component can cause delay in the primary wood extraction and/ or secondary trans- portation. This article reviewed the current knowledge on loading productivity studies. Based on the results, the main variables impacting the loading productivity include log size, log lengths, load volume per truck, number of logs (or pieces) per truck and number of safety straps. The productivity of loading operations ranged from 3.4 m3/PMH, in a manual loading to 168.9 m3/PMH, using mechanised load- ers. The results of this review can assist the academic and industrial users for predicting, controlling and managing the productivity of loading operations. Keywords Harvesting, Productivity, Time, Loading, Log volume, Mechanised loader, Manual loader Introduction Forest harvesting as a system includes various components, such as felling/ process- ing, primary transport, loading, secondary transport, unloading and road construc- tion (Conway, 1982). Loading is seen as a bottleneck of the forest harvesting system as it acts as a connection between primary transport (from stands to the roadside/ land- Copyright Mohammad Reza Ghaffariyan. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 82 Mohammad Reza Ghaffariyan / Silva Balcanica 22(2): 81-90 (2021) ing) and secondary transport (from roadside/ landing to the mills or central yards). Any delay in loading components can cause delay in the operations carried out by extraction machines and/ or trucks/ trailers (especially in hot-decking operations). In the case of cold decking (when timber is transported after finishing timber extraction phase), if the loading component is delayed it may result in larger volume of logs/ trees accumulated on the landings, which may reduce further the total efficiency of the harvesting system. When harvesting small trees, a feller can fell the trees with a chainsaw and manu- ally load them to the timber trucks; this is called a Bobtail system. In the case of load- ing large trees, the logs or tree lengths can be loaded by powerful mechanised load- ers. The mechanised loaders (powered systems) may be big-stick loaders, self-loading timber trucks, pallets, grapple loaders, front-end loaders, loading cranes and booms (Conway, 1982). Russell and Mortimer (2005) reviewed small- scale harvesting sys- tems and described two types of loaders, including wire-crane loaders and grapple loaders. Wire-crane loaders are powered by a winch that uses a high A-frame and sta- biliser legs that can be used to load the timber trucks. Grapple loaders use hydraulic crane equipped with a grapple that can pick up single or a bunch of logs/trees to lift and load into the timber trucks. Materials and methods Productivity is defined as a relationship between some measures of output to some measures of input uses (Griliches, 1998 cited in Heinimann, 2021). Loading produc- tivity is calculated by dividing volume per cycle (m’*) to the time per cycle (h) (http:// www.fao.org/3/t0579e/t0579e07. htm) Different factors such as stand conditions, machine type, work method and op- erator skills may impact on the work productivity of forest harvesting machines. Working time can be measured using the time study methods including using plot level, work shift level, work cycle or elemental level (Magagnotti et al. 2012). The results of time studies can be used by the forest harvesting planners to schedule the production, prepare the budget and compare different equipment and work meth- ods (Murphy, 2005). This review article aimed to review the current knowledge on loading productivity studies to identify the main variables impacting the work pro- ductivity and provide productivity range of loading operations for the academic and industrial users. The literature published in English language was found through online journal articles and technical reports by searching electronic databases including Google Scholar, Scopus and Web of Science. The following keywords were used for the elec- tronic search: timber, loading, productivity, loader and time study. The review results were Classified based on four main geographical areas (Asia/ Oceania, America and Europe). Predicting productivity of timber loading operations: a literature review 83 Results: Loading productivity studies Asia/ Oceania A time study was conducted in East Indonesia by Kewilaa and Tehupeiory (2015) to evaluate the productivity of a log loader Caterpillar 966 F Type and WL 980 C in IUPHHK PD. The trees were manually processed with a chain saw into logs to be load- ed by mechanical loaders into the timber trucks at the landing. The log volume (and its weight) was assumed to be the main factor influencing the loading productivity. The developed regression model showed that there was a linear relationship between productivity and log volume. The larger log volume resulted in higher productivity. In this case study (Kewilaa and Tehupeiory, 2015), 51 logs were measured with an aver- age volume of 4.3 m’. The average loading productivity for both loaders was 22.2 m? per productive machine hours (PMH). In the northern part of Iran, the mountainous broad- leafed natural forests are mainly harvested using a combination of chain saw for felling/ processing trees to short or long logs, skidders/ tractors to extract the logs to landing and front-end loader to load the logs into the timber trucks at the land- ings (Ghaffariyan, 2008; Ghaffariyan, Sobhani, 2008). A time study was conducted by Ghaffariyan et al. (2012a) to estimate loading productivity of a Volvo BM4500, model TD706 in an unevenly- aged Iranian forest where the main species was beech (Fagus orientalis). The average log volume was 2.78 m’. The regression model was inverse type and the only factor influencing productivity was log volume. The study reported an average productivity of 41.9 m*/PMH,. Loading elements included selecting the log (19% of total work time), grappling (24%), loading (21%) and adjustment (13%). Major delays included operational (13%) and personal delays (4%). Plantations of Australian pine and eucalypt are mostly harvested using whole- tree and cut-to-length methods (Lambert, 2006). Within the whole- tree method, feller-bunchers are used to fell the trees then the grapple skidders extract the whole trees to the roadside to be processed by a processor into short or long logs (Ghaffa- riyan, 2019). Then front-end grapple loaders are used to load the logs to the trailers at the roadsides. For the cut-to-length method, the harvester-processors fell and pro- cess trees into short logs at the stump. Then forwarders could extract the logs to the roadside. Forwarders or front-end grapple loaders can be then used to load the logs into trailers. A case study was conducted using the whole- tree harvesting method in an 11-year-old plantation of Eucalyptus globules (blue gum) at Clear Hills in Western Australia. The average tree volume was 0.2 m’. According to the results of the time study, the average productivity of a Cat 320C excavator-based grapple loader was 86.2 m*/PMH, (Figure 1). The work delay (mainly operational type due to waiting for the timber trucks) was 8.1% of the total working time (Ghaffariyan et al. 2012b). Another case study was conducted in Southern Tasmania within pine plantations (Pinus radiata). The tree size averaged 2.6 m* and the mean log volume was 0.7 m’. The harvesting system consisted of a tracked feller-buncher, processor, forwarder and loader. The loader model was Komatsu PC300 with a Randalls grab, which was used to load the short logs on the mini B-double truck. The average productivity of the 84 Mohammad Reza Ghaffariyan / Silva Balcanica 22(2): 81-90 (2021) Figure I. A front-end loader working in eucalypt plantations (Western Australia, photo by Rick Mitchell) Figure 2. Manual loading in Turkey (Guelci and Erdas, 2018) loader was 100.8 m*/PMH.,. Based on the results of Ghaffariyan et al. (2012c), 2.9% of the total time was spent for waiting for the timber trucks to move during loading, while 97.1% of the total time represented the actual loading time). Europe Akay et al. (2004) have reported that there are various types of loading from manual to highly mechanised ones. One of the powerful types is the hydraulic front-end loader that can handle short and long logs. According to Akay et al. (2004), the Predicting productivity of timber loading operations: a literature review 85 number of pieces per each truck is a significant variable impacting the loading time (used by Schneider (1978) as an independent variable). The study area in Kahramanmaras (Turkey) was covered by cedar, pine and fir with average tree volume of 0.7 m? and average slope of 31%. A Cat 322-B loader was applied to load the logs into the timber trucks where logs were produced at the landing using bucking the long logs skidded to the landing with a tracked-skid- der. The average productivity in this case study was 45.3 m°*/PMH,. An- other Turkish loading productivity study was conducted by Guelci and Erdas (2018) in stands of Brutian pine (Pinus brutia T.) with average ground slope of 33% and average log volume of 0.14 m* to 0.29 m’. The study included two loading methods: manual loading (Figure 2) and electric loading (Figure 3). Using an electric power winch increased the productivity by 25%. The average productivity was recorded at 3.40 m*/PMH, for the manual loading, while the pro- ductivity reached up to 4.25 m*/PMH, for the electric power loader. The higher pro- ductivity of the electric power loader was due to the higher load capacity. Load vol- ume per each truck was the significant variable impacting the productivity based on a linear regression analysis. Glueci et al. 2018 studied the productivity of Cat 428-E front-end loader in the Osmanniye area of Turkey. The mean volume per load was 0.45 m’ which resulted in an average productivity of 2.40 m*/PMH, (detailed informa- tion was not provided in the source of Glueci et al. 2018). Akay et al. 2020 studied the Liebherr L 514 Stereo front-end loader in Turkey. The study area was flat and covered by eastern spruce (Picea orientalis) and eastern beech (Fagus orientalis) located near Ordu in Turkey. The processed short logs were previously extracted to the roadside (landings) and were then loaded to the timber trucks. Two people worked in loading, including a loader operator and a worker guiding the operator to stack the logs on the truck. The average log size was 0.38 m’. An average productivity of 34.3 m*/PMH, was reported. Akay et al. (2020) found that the log volume and diameter were significant variables impacting the productivity, as demonstrated by the linear type regression model in their study. Work elements such as moving to the truck (31% of the total time) and moving to the log pile (31%) consumed the largest share of loading time. The working delays (including mechanical and personal ones) were recorded to ac- count for 25% of the total work time. Figure 3. Loading with an electric winch loader in Turkey (Guelci and Erdas, 2018) 86 Mohammad Reza Ghaffariyan / Silva Balcanica 22(2): 81-90 (2021) America In 1978, a study was conducted by the United States Department of Agriculture in In- termountain Region, Idaho (USA). The study included four types of loaders: cable load- ers with tongs, cable loader with grapple, self-propelled hydraulic loaders and truck mounted hydraulic loaders. The delay-free working time per each cycle was significantly impacted by the number of pieces per each truck based on a linear model (Schneider, 1978). Cass et al. (2009) conducted short time studies for a period of two to four days on five loader operators in Georgia and South Carolina (the machine model was not reported). The operations included the first thinning and clear-cuts. The harvesting sys- tem included feller-buncher, skidder, knuckleboom loader with a pull-trough delimber and a hydraulic ground saw. Log diameter ranged from 7.5 cm to 20 cm. The log length ranged from 3.8 m to 8.8 m. Loading productivity did not vary for different product, but it varied for different drivers from 69.4 ton/PMH, to 135 ton/PMH, (note the values in m?° had not been reported). The operators who performed delimbing and topping func- tions during loading took longer time and that resulted in a lower productivity. A case study was conducted by Soman (2019) in central Maine at a site consisting of mixed hardwood and softwood, including eastern hemlock (Tsuga canadensis (L.) Carr.) and yellow birch (Betula alleghaniensis Britt.) and other species. The slope angle was usually lower than 9%. Partial harvest and clear-cut methods were applied in the region. Trees were felled by feller-bunchers then extracted to the roadside by the grapple skidders to be processed at the landing. Loading with a Serco 300 grapple loader included elements such as swing empty, grapple, cutting, swing loaded and sorting. Sorting with loader was significantly impacted by the number of logs per turn. The average productivity was 168.9 m*/PMH, for both study treatments (partial harvest and clear-cut) as the log piles were combined to facilitate sorting similar market products. The log volume was not reported in this case study. Soman (2019) carried out another study in Maine to com- pare the tree length with the whole- tree harvesting method. The slope was gentle, less than 15%. The stands were mixed and included various species, mainly balsam fir (Abies balsamea (L.) Mill.), red maple (Acer rubrum L.), red spruce (Picea rubens Sarg.), black spruce (Picea mariana Mill.), eastern white pine (Pinus strobus L.), quaking (Populus tremuloides Michx.) and big-tooth aspen (Populus grandidentata Michx.). Harvesting machines included a feller-buncher, grapple skidder, processor, loader and a truck. The loader type was Sterco 300 and loaded the pulpwoods and sawlogs. Work cycles in- cluded swing empty, grappling, swing loaded, loading into the timber trucks. For some cycles there was a bucking element to cut the logs to market dimensions after the swing was loaded. Stem density varied from 1071 to 1149 trees per ha and total basal area ranged from 24.0 m*/ha to 27.2 m*/ha. Loading productivity averaged at 95 m’/PMH,, which was the same for both study treatments (Soman, 2019). Another study by Harril and Hun (2020) investigated the cost and productivity of integrated biomass harvesting in private forestlands in northern California. The stands consisted of tanoak, madrone (Arbutus menziesii) and young growth Douglas-fir (Pseudotsuga menziesii). The slope varied from 0 to 45%, while DBH ranged from 23.8 cm to 28.5 cm in the study units. The average tree volume was 0.66 m’. A mechanised system was applied to clear-cut the Predicting productivity of timber loading operations: a literature review 87 area using a combination of a feller-buncher, two Komatsu PC300 loaders (to swing/ shovel the bunches of whole trees to the roadside), loaders to load the bunches onto two timber trucks to deliver the woods to a centralised processing site. The average produc- tivity of loading whole trees was 138.4 m*/PMH, (note this value was transformed using a tree weight of 0.35 Bone Dry Tonnes (BDT) as cited in Harril and Hun (2020)). The slope, number of grapples per turn, loaded swing degrees, number of compaction and the travel distance were significant variables in the regression model (as linear type) to predict the delay-free loading time per cycle (Harril and Hunt, 2020). A Cat 322C loader was studied by Han and Han (2020) in northern California, USA. The stand was a mixed conifer forest, including white fir (Abies concolor), Douglas-fir (Pseudotsuga menziesii), ponderosa pine (Pinus ponderosa), incense-cedar (Calocedrus decurrens) and sugar pine (Pinus lambertiana). Cable yarding was applied using the whole tree and tree length methods to reduce fuel in thinning operations. The study area was steep as ground slope varied from 37% to 68%. The tree size was small and averaged at 0.03 m*. Trees were felled with a chain saw then yarded to the roadside using a cable yarder. A processor was used at the roadside to process whole trees then a Cat 322C loader was applied to load the whole trees into timber trucks from a cold deck. The study results showed that there was no significant difference between average loading times between the two harvest- ing methods. The number of logs per turn was the only significant variable impacting the loading time based on a linear type regression. The loading productivity for the tree length method averaged at 59.4 m’/PMH,, while the whole- tree method yielded an average productivity of 60.5 m*/PMH, (Han and Han, 2020). Grapple loaders are also used in Brazilian forest operations. A case study was car- ried out by Arcego et al. (2019) in pine stands (Pinus taeda) in Otacilio Costa, Brazil. Trees were felled with a feller-buncher then skidded to the roadside with a grapple skidder to be processed to logs using a mechanical processor. Then a tracked based Komatsu PC200 (Figure 4) was used to load the short logs into the B-double timber trucks with the gross weight of 57 t. Log length varied from 2.4 m to 7.0 m. The log Figure 4. Komatsu PC200 loader working in Brazil (Arcego et al. 2019) 88 Mohammad Reza Ghaffariyan / Silva Balcanica 22(2): 81-90 (2021) bundles were equipped with four to eight safety straps. The results showed that aver- age loading productivity for 2.4 m logs (using six straps) was 105.8 ton/PMH.. For 3.4 m logs with using four or eight straps the productivity increased to 151.2 ton/PMH,. The highest productivity at 177 ton/ PMH, was achieved by loading 7.0 m logs using four straps (note the values in m* were not reported). The mean productivity for all study treatments was 144.7 ton/PMH, (Arcego et al. 2019). Table |. Summary of loading productivity studies see Independent Productivit Continent | Country | volume P Machine model A Y' | Reference (mn2} variables (m*/PMH,) Indonesia Iran Log volume Log volume Caterpillar 966 F Type and WL 980 Cin IUPHHK PD Volvo BM4500 Kewilaa and Tehupeiory (2015) Ghaffariyan et al. 2012a Australia Oceania n/a n/a Cat 320C Komatsu PC300 Ghaffariyan et al. 2012b Ghaffariyan et al. 2012c Number of pieces per truck Load volume Load volume Cat 322-B Manual Electric winch loader Akay et al. (2004) Guelci and Erdas (2018) Akay et al. Logvolimeé Liebherr L 514 Stereo (2020) ae Nig Sterco 300 re bis Number of logs 0.66 ear aa ted 138.4 Harril and ns 2 Sia Komatsu P300 Hun (2020) loaded swing degrees, number of compaction ; and travel America : distance Number of logs Lee pound Cat 322C 59.4-60.5 Han and 0.03 number of straps Han (2020) per bundle Brazil N/A Komatsu PC200 144.7 (t/ Arcego et al. PMH.) 2019 Predicting productivity of timber loading operations: a literature review 89 Conclusions Log volume is one of the important factors impacting the loading productivity. Larger log volumes can result in higher productivity due to increase work efficiency in han- dling larger pieces (Ghaffariyan et al. 2012; Arcego et al. 2019). Thus, the size of logs can be an important consideration when choosing suitable size/ type of the load- er (and the size of the timber trucks) in order to eliminate any potential deficiency in loading (and haulage) operations. Also, all logs need to be carefully processed to match with loader (and truck) specifications. When landings are well planned/ main- tained and when the timber loads are well stacked at the landings, the loaders may operate more effectively. Ghaffariyan et al. 2012c suggested applying a better machine management to reduce the downtimes of loaders when waiting for the timber trucks. Loading should be in harmony with the other components of the harvesting system (e.g. felling, extraction, etc.) in order to ensure achieving an effective production for the whole supply chain (Akay et al., 2020). Han and Han (2020) mentioned that the loading productivity for logs produced using two harvesting methods (including whole tree and tree lengths) were not significantly different but the number of logs per turn was a key variable impacting loading time per cycle. If the number of safety straps per each bundle of logs is reduced it can increase the efficiency of the loading operation (Arcego, 2019). Regarding manual loading, Guelci and Erdas (2018) and Akay et al. (2020) mentioned that this type of loading in Turkish forestry may face some challenges, such as lack of labour in the regions, and might not be productive due to long time requirement to load a unit volume of load compared with the mecha- nised loaders. References Akay, A.E., Bilici, E., Tas, I., H.E. Findik. 2020. Productivity analysis of front-end loader in timber harvesting. - European Journal of Forest Engineering, 6(1), 7-13. Akay, A., Erdas, O., J. Sessions. 2004. Determining productivity of mechanized harvesting ma- chines. — Journal of Applied Sciences, 4(1), 100-105. Arcego, H., Robert, R.C.G, R.O. Brown. 2019. Effect of log length on forestry loading and un- loading. Floresta e Ambiente, 26(2): e20170269. DOI 10.1590/2179-8087.026917 Conway, S. 1982. Logging practices: principles of timber harvesting systems. Miller Freeman Publications, San Francisco. 432 pp. Han, S-K., H-S Han. 2020. Productivity and cost of whole-tree and tree-length harvesting in fuel reduction thinning treatments using cable yarding systems. - Forest Science and Technology, 16(1), 41-48. Ghaffariyan, M.R. 2008. Harvesting planning using heuristic for skidding operations. - Aus- trian Journal of Forest Science, 4, 251-266. Ghaffariyan, M.R. 2019. Short review on overview of forest biomass harvesting case studies in Australia. — Silva Balcanica, 20 (1), 89-96. 90 Mohammad Reza Ghaffariyan / Silva Balcanica 22(2): 81-90 (2021) Ghaffariyan, M.R., Naghdi. R., Ghajar, I., M. Nikooy. 2012(a). Time prediction models and cost evaluation of cut-to-length (CTL) harvesting method in a mountainous forest. Small- scale Forestry. DOI 10.1007/s11842-012-9204-4. Ghaffariyan, M.R., Acuna, M., L. Kellogg. 2012(b). Productivity of roadside processing system in Western Australia. — Silva Balcanica, 13(1), 49-60. Ghaffariyan, M.R., Sessions, J., M. Brown. 2012(c). Machine productivity and residual harvest- ing residues associated with a cut-to-length harvest system in southern Tasmania. South- ern Forests, 74(4), 229-235. Ghaffariyan, M.R., H. Sobhani. 2008. Study of optimum road spacing of ground-based skid- ding operations. —- Caspian Journal of Environmental Sciences, 6(2), 105-112. Griliches, Z. 1998. Productivity: measurement problems. In the New Palgrave. A Dictionary of Economics., J. Eatwell, M. Milgate, and P. Newman, Editors. Palgrave: New York. Vol. 3, K to P: 1010-1013 pp. Guelci, N., O. Erdas. 2018. Comparison of timber loading productivity between manual sys- tem and electric powered winch system. - European Journal of Forest Engineering, 4(1), 1-6. Guelci, N., Erdas, O., Guelci, S., AE. AkayE. 2018. Productivity of a loader in mechanized loading operation in Osmaniye, Turkey. PEFOSS 2018 International Symposium “Man — Forest — Science’, Sarejevo, Bosnia and Herzegovina. October 10-12 (Abstract down- loaded from Research Gate). Han, S-K, H-S Han. 2020. Productivity and cost of whole-tree and tree-length harvesting in fuel reduction thinning treatments using cable yarding systems. - Forest Science and Technology, 16 (1), 41-48. Harrill, H., H-S Han. 2020. Productivity and cost of integrated harvesting of wood chips and sawlogs in stand conversion operations. - International Journal of Forestry Research (12), Article ID 893079, 10 pp. DOI:10.1155/2012/893079 Heinimann, H.R. 2021. Operational productivity studies in forestry with an emphasis on the de- velopment of statistical models. A tutorial. ETH Forest Engineering Research Paper. 56 pp. http://www.fao.org/3/t0579e/t0579e07.htm Lambert, J. 2006. Growth in blue gum forest harvesting and haulage requirements in the Green Triangle 2007-2020. CRC Forestry report. 119 pp. Magagnotti, N., Spinelli, R., Acuna, M., Bigot, M., Guerra, S., Hartsough, B., Kanzian, C., Karha, K., Lindroos, O., Roux, S., Talbot, B., Tolosana, E., FE Zormaier. 2012. Good practice guidelines for biomass production studies, COST Action FP-0902, WG 2 Op- erations research and measurement methodologies. Fiorentino (FI), Italy: CNR IVALSA- ISBN 9788890166044- 52 pp. Murphy, G. 2005. Determining sample size for harvesting cost estimation. - New Zealand Journal of Forestry Science, 35(2/3), 166-169. Russell, F, D. Mortimer. 2005. A review of small-scale harvesting systems in use worldwide and their potential application in Irish forestry. COFORD, Dublin. 48 pp. Scneider, E.W. 1978. A log truck loading study in the intermountain region: production and costs. Department of Forest Engineering, College of Forestry, Oregon State University, Corvallis, Oregon, USA, 70 pp. Soman, H. 2019. Productivity, costs, and best management practices for major timber harvest- ing frameworks in Maine. University of Maine. 82 pp. Electronic Theses and Dissertations. https://digitalcommons.library.umaine.edu/etd/2960