Printer Friendly

Hardwood log bucking and loading efficiency in West Virginia.

Abstract

The efficiency of bucking and loading central Appalachian hardwood logs was investigated by using a knuckleboom loader together with a sawbuck. Bucked tree stems averaged 15.32 inches in butt diameter with lengths ranging from 19.50 to 106.00 feet. The average number of logs bucked per stem was 3.4 with an average volume of 47.29 board feet (BF) Doyle scale per log. The majority of logs bucked were saw and peeler logs (68%), followed by pulpwood and scragg logs (31%). Hourly bucking production was 4.56 thousand BF per productive machine hour (MBF/PMH) with a unit cost of $14.65/MBF. The loader grappled an average of two logs per turn with an average small-end diameter of 10.50 inches and average length of 9.61 feet. The loading productivity was 7.19 MBF/PMH with a unit cost of $9.29/MBF. Results indicated a typical knuckleboom loader with a sawbuck can be employed efficiently in the region with a typical balanced manual harvesting system or a mechanized harvesting system.

Bucking is one of the most important processes in logging operations. No other process, except perhaps felling, has as direct an influence on logging profitability as bucking (Sickler 2004). Workplace organization and layout are important parts of the bucking process. If the bucking station is set up in an organized manner, the time it takes to buck a log can be reduced and the accuracy of the cuts can be increased. By using hydraulic saws and a saw buck with standard log measurements for bucking, greater accuracy can be achieved more consistently. During the last six decades, optimal bucking has been extensively studied, and several programs have been developed by many researchers using computer modeling techniques associated with mathematical programming (Pnevmaticos and Mann 1972, Faaland and Briggs 1984, Nasburg 1985, Sessions 1988, Sessions et al. 1989, Pickens et al. 1992). However, no optimal bucking program has been generally used in field applications, specifically for bucking central Appalachian hardwood species.

A recent log bucking and merchandising study was conducted in West Virginia based upon on-site interviews with 50 timber harvesting company owners/operators (Wang et al. 2007). Bucking logs based on the value (grade) is dominant in West Virginia. This method was used by 70 percent of the logging companies, while 30 percent of the companies buck logs based on volume (production). Fifty percent of the logging companies who were currently bucking for volume indicated that some incentives ranging from $10 to $50/MBF would be needed for them to buck for grade.

Time spent on loading trucks can be also minimized if logs are sorted into designated piles by products during the bucking process, which allows them to be easily accessed while any particular product is being loaded. The time consumption per loading cycle may be described either by empirical time studies or by theoretical models that include machine characteristics, human reaction times, and log sizes (Gullberg 1997).

Several studies have been conducted on loading productivity. Machines evaluated include fork-lift loader, truck-mounted loader, forwarder-mounted loader, and trailer-mounted knuckleboom loader. Hartman (1968) examined loading cycles based on log properties using a tractor equipped with a fork lift. He found that the second order of the moment of inertia most significantly affected the total loading cycle time. The moment of inertia, which was recorded as any opposition of the log to change its state of motion, also significantly affected log collection. A study performed with a forwarder found that average loading times were dependent upon the number of piles and the capacity of the loading arm. The cycle time depends on how many piles can be loaded without moving the forwarder (Ronnqvist et al. 1999). Another loading study involving a forwarder was conducted by Gullberg (1997) and examined variables that may affect loading cycle times of shortwood. He stated that the volume per loading cycle is dependent on several variables including pile characteristics (log length, volume), loading method (multiple pile loading), grapple area, and machine characteristics, such as net lifting force and stability.

Some logging companies in other regions are using trucks mounted with knuckleboom loaders, and thus loading is done by the truck driver (Sickler 2004). This can be a great time saver in the loading process, but when improperly used it can cause serious damage to a grade log (Sickler 2004). This is also true for knuckleboom loaders mounted on a trailer. These loading processes involve picking the logs up, and caution should be paid to prevent damaging some of the valuable outer wood of the logs. The number of logs grappled for each cycle is dependent on size and often by product. The placement of the logs on the truck also plays an integral role in the time spent loading as well as the volume loaded.

According to a previous study in West Virginia, all of the bucking operations were done at the landing using either chain saws or sawbucks. Bucking with a sawbuck by a loader operator is the most common practice in West Virginia and accounted for 84 percent of the bucking operations. Manual bucking with chain saws at the landing accounted for 16 percent (Wang et al. 2007). Knuckleboom loaders accomplished 73 percent of the truck loading. Trucking was done with tractor-trailers (5l%) and short-wood and other types of trucks (49%) (Milauskas and Wang 2006). Most previous studies addressed technique-related bucking problems and production efficiency associated with felling and skidding operations. Log bucking and merchandising generally requires more time for processing each tree stem while loading can be optimized with log sorting. Apparently, there is a lack of information associated with the efficiency and costs of log bucking, merchandising, and loading. As part of a hardwood log merchandising project, the objectives of this paper were to (1) examine bucking and loading production efficiency in West Virginia by using a typical knuckleboom loader with a sawbuck, and (2) statistically analyze how hardwood species, tree stem or log dimension, and log product type affect bucking and loading production and costs.

Methods

The field study was conducted on a 112 acre tract of the West Virginia University Research Forest from November 2005 to February 2006. The harvest was a partial diameter limit cut combined with a crop tree release cut for red oak. It was a mechanized harvesting operation using one Timbco feller-buncher, two grapple skidders, and three tractor-trailers for hauling. Five people worked in the forest for this operation, while three were employed for trucking. The stand was composed of mostly yellow-poplar (Liriodendron tulipfera) (80%), chestnut oak (Quercus prinus) (8%), scarlet oak (Quercus coccinea) (5%), black cherry (Prunus serotina), and other hardwood species (7%). The average diameter at breast height was 17 inches for sawtimber and 9 inches for pulpwood, while the average volume per tree was 122 BF for sawtimber and 1.96 tons for pulpwood, respectively. The equipment used for log bucking and loading on this site was a CTR bucksaw, and a Barko 395ML loader. The operator reported having 14 years of experience running the loader and sawbuck.

Time elements and machine factors were recorded by using a digital video camera equipped with an internal clock. Log data including species, large- and small-end diameters, length, and log type were measured and recorded on paper. A work cycle for each operation consisted of certain elemental functions and factors. The times for each function and the value of each variable were recorded in the field.

Functions of the bucking were defined as: (1) Swing to tree stem--Starts when the loader operator finishes the previous cycle and begins moving the grapple to the next tree stem to be bucked and ends when swing movement has stopped; (2) Grappling Consists of time taken to grapple a tree stem and all the logs associated with it; (3) Swing to saw Begins when grapple swings from tree stem pile or log pile and ends when the tree stem is placed in a sawbuck or the loader is ready for bucking next log from the same tree stem; (4) Buck--Begins when the saw is positioned on the tree stem and ends when a log is completely severed. This process usually consists of several logs; and (5) Swing to log pile--Begins when the grapple moves from the sawbuck and ends when the log is dropped onto a specific pile. Delays were also recorded if they occurred during the bucking process. Bucking variables measured on the landing include butt and top diameters, length, species, and the number of logs bucked from each stem, and large-end, small-end diameters, length, and product type of each log.

Loading elemental time functions were grouped into: (1) Swing to log pile--Begins when the grapple swings to log pile and ends when the grapple reaches the pile and is ready for grappling; (2) Grapple--Begins when grapple starts to gather a load and ends when the grapple is full; (3) Swing to truck--Begins when grapple starts to swing to tractor-trailer with a full grapple of logs and ends when grapple reaches the tractor-trailer; (4) Ungrapple--Begins when loader operator opens grapple and drops logs onto the truck and ends when loader is ready for another load; and (5) Rework--Consists of time taken to rearrange some of the logs grappled in a turn for better placement and a safe and full load. Loading variables collected in the field include the number of logs grappled each turn, and large-end, small-end diameters, length, species, and product type of each log per turn.

Both elemental times and values of operational variables were recorded in a work cycle. A total of 100 cycles for bucking with sawbuck and 180 cycles for loading were collected in the field. Local volume equations were later used to compute the volumes of tree stems and logs (Wiant 1986, Rennie 1996, Avery and Burkhart 2002). Volume of pulpwood that was expressed in BF instead of tons was just for comparisons with other log products in this study. A general linear model (GLM) was used to analyze if significant differences of times and productions of bucking and loading exist among operational variables. Regression techniques were also employed to develop estimation equations for elemental times and hourly productions.

The generic GLM model for analyzing bucking is expressed as:

B[T.sub.ijkl] = [mu] + [D.sub.i] + [L.sub.j] + [S.sub.k] + [D.sub.i] x [L.sub.j] + [D.sub.i] x [S.sub.k] + [L.sub.j] x [s.sub.k] + [[epsilon].sub.ijkl]

i = 1, 2, 3 j = 1, 2, 3, 4 k = 1, 2, ..., 5 l = 1, 2, ..., n [1]

Where B[T.sub.ijkl] represents the lth observation of elemental times, cycle time, or hourly production: [mu] is the mean of each response variable: [D.sub.i] is the effect of the ith butt diameter of a tree stem: [L.sub.j] is the effect of the jth length of a tree stem: [S.sub.k] is the effect of the kth species: [[epsilon].sub.ijkl] is an error component that represents uncontrolled variability: and l is the number of observations within each treatment. Interactions among butt diameter, length of tree stem, and species were also considered in the model.

The model for loading is expressed as:

L[T.sub.ijklm] = [mu] + A[D.sub.i] + A[L.sub.j] + N[L.sub.k] + P[T.sub.i] x A[D.sub.i] + A[L.sub.j] x [[epsilon].sub.ijkl]

i = 1, 2, 3 j = 1, 2, 3 k = 1, 2, 3 l = 1, 2, 3 m = 1, 2, ..., n [2]

Where L[T.sub.ijklm] represents the mth observation of elemental times, cycle time, or hourly production; [mu] is the mean of each response variable: A[D.sub.i] is the effect of the [i.sup.th] average small-end diameter of logs grappled per turn; A[L.sub.j] is the effect of the jth average length of logs grappled per turn; N[L.sub.k] is the effect of the kth number of logs grappled per turn; P[T.sub.l] is the effect of lth log product type: [[epsilon].sub.ijklm] is an error component that represents uncontrolled variability; and m is the number of observations within each treatment. Interaction among average small-end diameter of logs, and average length of logs was also considered in the model.

Results

Bucking operations

The butt diameter of the tree stems averaged 15.32 inches ranging from 9.30 to 24.60 inches while their length varied from 19.50 to 106.00 feet, with an average length of 53.74 feet (Table 1). The number of logs bucked per tree stem was between 1 and 7 and averaged 3 logs. The scaling diameter (small-end diameter) of these logs ranged from 2.70 to 22.80 inches with an average of 10.52 inches. The bucked log length averaged 13.57 feet, ranging from 6.00 to 25.00 feet. The log volume averaged 49.08 BF. Sixty-eight percent of these bucked logs were peeler or sawlogs. Pulpwood and scragg accounted for 31 percent, and cull was only 1 percent.

Swing to tree stem.--Swing to tree stem time was primarily affected by the boom reach and the relative location of tree-stem pile. It averaged 0.28 minutes (Table 1) and was not significantly different among species (F = 0.50: df = 4,90; p = 0.7339), among butt diameter class (F = 2.63; df = 2,90: p = 0.0797), and among stem lengths (F = 0.30: df = 3,90: p = 0.8222) (Table 2). Two numbers separated by a comma were used to express the degree of freedom of each class variable in the GLM model. The first number represents the degree of freedom of a class variable and the second number is the degree of freedom for the corrected total in the model.

Swing to saw.--Swing to saw time was solely related to the relative distance between sawbuck and log pile. The swing to saw time averaged 0.34 minutes (Table 1). It was not significantly different among species but differed significantly among butt diameter class and among stem lengths (Table 2).

Grapple.--Grapple time was between 0.12 and 2.67 minutes with an average of 0.81 minutes (Table 1). There was no significant difference in grapple time among species (Table 2). It differed significantly among butt diameter class (F = 14.27; df = 2,99; p = 0.0001) and among stem lengths (F = 8.10; df = 3,99; p = 0.0001). The interaction between species and stem length also significantly affected the grapple time (F = 2.37; df = 6,99; p = 0.0377). A regression model was developed to estimate grapple time (Table 3), which is a function of butt diameter and the number of logs bucked per stem.

Buck.--Buck time ranged from 0.03 to 1.10 minutes per stem with an average of 0.26 minutes (Table 1). The buck time was not significantly affected by species. However, it did significantly differ among butt diameter class (F = 2.78; df = 2,99; p = 0.0001) and among stem lengths (F = 0.54; df = 3,99; p = 0.0430) (Table 2). A regression model developed to estimate buck time was sensitive to butt diameter and the number of logs bucked per stem (Table 3).

Swing to pile.--Swing to pile time averaged 0.59 minutes per stem (Table 1). There was no significant difference in swing to pile time ranging from 0.36 to 0.62 minutes among species. Both butt diameter (F = 14.99; df = 2,99;p = 0.0001) and stem length (F = 28.91; df = 3,99; p = 0.0001) affected swing to pile time significantly (Table 2).

Bucking delay.--Only six delays were observed during bucking operations. Delay was usually due to maintenance of sawbuck and included replacing the dull chain and tightening the chain. Some delay also occurred because of hydraulic failure and communication between the loader operator and the trucker. The delay ranged from 0.25 to 60.50 minutes with an average of 10.45 minutes.

Cycle time.--Bucking cycle time averaged 2.28 minutes ranging from 0.80 to 5.74 minutes without delays (Table 1). Cycle time was significantly affected by butt diameter and stem length (Table 2). A multilinear regression model was developed to estimate bucking cycle time. It was best described by butt diameter, stem length, and the number of logs bucked from a tree stem (Table 3).

Bucking productivity.--Hourly bucking production with a sawbuck ranged from 0.29 to 16.47 MBF Doyle scale per productive machine hour (PMH) with an average of 4.56 MBF/PMH (Table 1). Bucking productivity was between 0.93 and 6.21 MBF/PMH and was different among species (F = 3.10; df = 4,89; p = 0.0212) (Table 2). The bucking productivity generally increases with butt diameter and length of tree stem. There was significant difference in bucking productivity among butt diameter class (F = 4.44; df = 2,89; p = 0.0155) and among stem lengths (F = 0.69; df = 3,89; p = 0.0493). The interaction between species and butt diameter class also significantly affected bucking productivity. Butt diameter of tree stem was the only significant factor that was included in the regression model for estimating bucking productivity (Table 3).

Loading Operations

The loader grappled two logs per turn with an average volume of 54.64 BF (Table 4). The range of average small-end diameter of loaded logs per turn was between 3.50 and 20.30 inches, while average log length varied from 6.00 to 18.00 feet.

Swing to pile.--Swing to pile time averaged 0.12 minutes ranging from 0.02 to 0.66 minutes (Table 4). The average log length grappled per turn was the only factor that affected swing to pile time significantly (F = 4.09; df = 2,140; p = 0.0190) (Table 5).

Grapple.--Grapple time was between 0.02 and 0.65 minutes with an average of 0.05 minutes (Table 4). It changed slightly and was not significantly affected by small-end diameter class of logs grappled per turn, average length of logs per turn, the number of logs per turn, or product types (Table 5).

Swing to truck.--Swing to truck time averaged 0.17 minutes (Table 4). It varied from 0.15 to 0.18 minutes among average small-end diameter of logs, the number of logs per turn, and product types (Table 5). It differed significantly among the average lengths of logs grappled per turn (F = 1.99; df = 2,140; p = 0.0128).

Ungrapple.--Ungrapple time ranged from 0.01 to 0.31 minutes with an average of 0.08 minutes (Table 4). There was no significant difference in ungrappling time among average small-end diameter class, the number of logs grappled per turn, and among product types (Table 5). It was significantly affected by the average length of logs grappled per turn (F = 4.26; df = 2,140;p = 0.0162).

Rework.--Rework occurred when the loader operator relocated some logs on the truck for a safer and higher payload.

It averaged 0.29 minutes (Table 4) and no class variables significantly affected the rework time (Table 5).

Cycle time.--Loading cycle time was between 0.18 and 1.53 minutes with an average of 0.52 minutes (Table 4). It changed from 0.43 to 0.55 minutes and was significantly different among average small-end diameter of logs grappled per turn (F = 3.18; df = 2,140; p = 0.0449).

Loading productivity.--Loading productivity averaged 7.19 MBF/PMH ranging from 0.00 to 57.76 MBF/PMH (Table 4). The productivity generally increased with increasing average small-end diameter class of logs, average length of logs per turn, and the number of logs grappled per turn (Table 5). It varied from 3.40 MBF/PMH for loading pulp logs, to 7.56 MBF/PMH for peeler logs, and to 12.24 MBF/PMH for sawlogs. The loading productivity was significantly different among the above four class variables (Table 5). The multilinear regression models were developed to estimate the loading productivity for three types of log products (Table 6). These models were best described by average small-end diameter of logs grappled per turn, average length of logs per turn, and the number of logs grappled per turn.

Cost analysis

Estimated hourly cost for the knuckleboom loader was calculated using the machine rate method (Miyata 1980). Labor was $17.00 per scheduled machine hour (SMH) plus additional labor-related costs totaling 40 percent of hourly wages. Interest, insurance, and tax were assumed as 20 percent. Maintenance and repair was 90 percent of the machine's depreciation. Mechanical availability of the loader/sawbuck was 80 percent with 2000 SMH per year.

The price of the sawbuck was $15,000. A new saw bar costs $280.00 while a chain is $85.00. The sawbuck required 2.5 gallons of oil per day. Chains were generally changed at least once daily depending upon tree species bucked. The loader was purchased for $108,000 in 2005 and the estimated salvage price after 5 years is $100,000. The fuel consumption of the loader was 25 gallons per day. The reported oil consumption was 0.5 gallons per 250 hours of work, while the price of the motor oil was $399.00 per 55 gallons.

Fixed costs and variable costs were estimated at $26.14/PMH and $10.92/PMH. Labor cost was $29.75/PMH. Total hourly costs of the loader amounted to $66.80/PMH. When combined with the hourly production estimates of 4.56 MBF/PMH for bucking and 7.19 MBF/PMH for loading, the unit costs averaged $14.65/MBF for bucking and $9.29/MBF for loading, respectively. The unit cost of bucking generally decreased with an increase in butt diameter of tree stein (Fig. 1). Bucking unit cost decreased 85 percent from $69.90/MBF to $10.43/MBF when the butt diameter of tree stein changed from 10 to 18 inches. It decreased 57 percent from $10.43/MBF to $4.47/MBF as the butt diameter increased from 16 to 26 inches. Loading unit costs also generally decreased with an increase of the average small-end diameter of logs grappled per turn (Fig. 2). The loading unit costs decreased from $19.63/MBF, $22.72/MBF, and $15.12/MBF to $2.67/MBF, $2.33/MBF, and $3.74/MBF for loading sawlogs, peeler logs, and pulp logs, respectively, as the average small-end diameter changed from 9 to 20 inches. When the small-end diameter of logs grappled was less than 13 inches, loading sawlogs was 5 percent and 16 percent more expensive than loading peeler logs and pulp logs, respectively. However, if the small-end diameter of loaded logs was larger than 13 inches, loading pulpwood logs was 14 percent and 31 percent more expensive than loading sawlogs and peeler logs, respectively.

Conclusions and discussion

Hardwood species did not affect the bucking elemental times significantly. However, there were significant differences in elemental times and bucking productivity among butt diameters and lengths of tree stems. Swing to saw and swing to pile times were a major component in a cycle and accounted for 41 percent of a total cycle time because log merchandising was carried out in these two elemental functions. Bucking cycle time and hourly production can be best modeled by butt diameter, stem length, and the number of logs bucked per stein. This study also indicated that the utilization rate of tree stems was high, with 99 percent for sawlogs, peelers, pulpwood, and scragg. There was only 1 percent of cull left on the landing.

There were two grapple skidders running on this operation, which kept the landing full of tree-length stems. The bucking was never slowed down because of lack of trees. Bucking and loading efficiency can be improved through better maintenance and appropriate operations of the loader. During the bucking operations several major mechanical delays due to hydraulic system failure, such as hydraulic hoses breaking, were observed, The hoses were pinched by excess wood that was cut and placed inside of the sawbuck. Hoses rub together while they are in use and this causes holes to form, which in turn causes leaks and can amount to a substantial delay. Also having the sawbuck on a secure position can save time and produce more consistent cuts. When the sawbuck is not leveled it moves in each cycle, which can also cause some uneven cut log ends. Repositioning the sawbuck takes time.

All class variables including average small-end diameter of logs grappled per turn, average length of logs, the number of logs grappled per turn, and product type did not significantly affect most of the loading elemental times. However, the loading productivity was significantly different among these variables. Rework was the most time consuming elemental function during loading, and it accounted for 58 percent of a total cycle time. This is because the loader operator always tried to make a safe, legal and full truck payload. Loading productivity varied increasingly from pulpwood logs, to peeler logs, and to sawlogs because of different sizes of these products. The turn volume of logs loaded changed from 22.86 BF for pulp logs, to 62.00 BF for peeler logs, and to 85.75 BF for sawlogs. The loading productivity can be best described in a model by average small-end diameter of logs grappled per turn, average length of logs and the number of logs per turn.

Loading was efficient for the most part, and no delay was observed during the field studies. While performing bucking, the loader occasionally loaded logs on the back end of the trailer at the same time. The designation of log piles by products is important for improving loading productivity. Having a sufficient number of logs to load onto a truck is always a key factor to reduce loading downtime. Rearranging logs on the trailer enables the operator to safely produce a full load of logs. More field experience gained from work or training can help a loader operator make a safe, full, and legal truck payload. For example, placing logs with sweep on outer edges of a load can provide more space for logs and contribute to a more stable load than placing them in the middle of the load.

The hourly production of bucking and loading proved that a typical knuckleboom loader with a sawbuck can be employed in a typical balanced manual harvesting system with two chain saws for felling (2.36 MBF/PMH) and two cable skidders for extraction (1.78 MBF/PMH) or in a typical mechanized system with one feller-buncher for felling (7.81 MBF/PMH) and two grapple skidders for extraction (3.16 MBF/PMH) (Wang et al. 2004a and 2004b). The findings from this study could be useful for logging managers to select an appropriate harvesting system and to aid logging management decisions. The results can be also used by researchers to simulate harvesting system configurations, productivity and cost estimations, and to conduct logging business management training for loggers in the region.

Literature cited

Avery, T.E. and H.E. Burkhart. 2002. Forest Measurements. 5th Ed. McGraw-Hill, New York. 456 pp.

Faaland, B. and D. Briggs. 1984. Log bucking and lumber manufacturing using dynamic programming. Manage. Sci. 30(2):245-257.

Gullberg, T. 1997. A deductive time consumption mode[ for loading shortwood. J. of Forest Engineering 8(1):35-44.

Hartman, R.L. 1968. Analysis of some log properties and their effect on the loading cycle. Master's thesis. Div. of Forestry, West Virginia Univ., Morgantown, West Virginia. 89 pp.

Milauskas, S. and J. Wang. 2006. West Virginia logger characteristics. Forest Prod. J. 56(2): 19-24.

Miyata, E.S. 1980. Determining fixed and operating costs of logging equipment. Gen. Tech. Rept. NC-55. USDA Forest Serv., St. Patti, Minnesota.

Nasburg, M. 1985. Mathematical programming models for optimal log bucking. Diss. No. 132. Linkoping Univ. Linkoping, Sweden.

Pickens, J., A. Lee, and G. Lyon. 1992. Optimal bucking of northern hardwoods. Northern J. of Applied Forestry 9(4): 149-152.

Pnevmaticos, S. and S. Mann. 1972. Dynamic programming in tree bucking. Forest Prod. J. 22(2):26-30.

Rennie, J.C. 1996. Formulas for Mesavage's cubic-foot volume table. Northern J. of Applied Forestry 13(3): 147-148.

Ronnqvist, M., A. Westerlund, and D. Carlsson. 1999. Extraction of logs in forestry using operations research and geographical information systems. In: Proc. of the 32nd Hawaii Inter. Conf. on System Sci. Maui, Hawaii.

Sessions, J. 1988. Making better tree-bucking decisions in the woods. J. of For. 10:43-45.

--, E. Olsen, and J. Garland. 1989. Tree bucking for optimal stand value with log allocation constraints. Forest Sci. 35(1):271-276. Sickler, R. 2004. Increasing the competitiveness of Missouri's Hardwood Producers: An introduction to lean enterprise principles for loggers. Missouri Enterprise Business Assistance Center. Rolla, Missouri. 35 pp.

Wang, J., C. Long, and J.F. McNeel. 2004b. Production and cost analysis of a feller-buncher and grapple skidder in central Appalachian hardwood forests. Forest Prod. J. 54(12):159-167.

--, --, J.F. McNeel, and J. Baumgras. 2004a. Productivity and cost of manual felling and cable skidding in central Appalachian hardwood forests. Forest Prod. J. 54(12):45-51.

--, S.T. Grushecky, Y. Li, and J.F. McNeel. 2007. Hardwood log merchandising and bucking practices in West Virginia. Forest Prod. J. 57(3):71-75.

Wiant, H.V., Jr. 1986. Formulas for Mesavage and Girard's volume tables. Northern J. of Applied Forestry 3:124.

The author is Associate Professor, West Virginia Univ, Division of Forestry and Natural Resources, Morgantown, West Virginia. (jxwang@wvu.edu). The author would like to thank Mr. Tony Goff, Mr. Jingang Liu, Mr. Tom Crickenberger, and Mr. Bob Driscole for their help during the field studies. This manuscript is published with the approval of the Director of West Virginia Agricultural and Forestry Experimental Station as Scientific Article No. 2975. This paper was received for publication in June 2006. Article No. 10223.

* Forest Products Society Member.

[c]Forest Products Society 2007.

Forest Prod. J. 57(5):84-90.
Table 1.--Statistics of log bucking during time and motion studies.

 Mean SD Minimum Maximum

Tree stems
 Butt diameter (in) 15.32 3.93 9.30 24.60
 Top diameter (in) 6.56 2.67 2.70 17.80
 Tree-length (ft) 53.74 17.33 19.50 106.00
 No. of logs bucked per stem 3.40 1.18 1.00 7.00

Bucked logs
 Small-end diameter (in) 10.52 4.09 2.70 22.80
 Large-end diameter (in) 12.68 4.06 5.30 24.60
 Log length (ft) 13.57 4.65 4.00 25.00
 Long volume (BF) 49.08 59.32 0.00 397.62

Bucked log types (%)
 Peeler and sawlogs 68 29 0 100
 Pulpwood and scragg 31 29 0 100
 Cull 1 4 0 32

Elemental times (min.)
 Swing to tree stem 0.28 0.23 0.01 0.98
 Swing to saw 0.34 0.24 0.07 1.51
 Grapple 0.81 0.45 0.12 2.67
 Buck 0.26 0.20 0.03 1.10
 Swing to pile 0.59 0.27 0.23 1.79
 Cycle time (a) 2.28 1.00 0.80 5.74
Production estimate
 Productivity (MBF/PMH) 4.56 3.78 0.29 16.47

Table 2.--Means and significance levels of statistics for bucking
operations. (a)

 Elemental tunes (min.)

 Swing to Swing to
 tree stem saw Grapple Buck

Species

 Black cherry 0.43 A 0.18 A 0.63 A 0.28 A
 Chestnut oak 0.30 A 0.35 A 0.76 A 0.28 A
 Red oak 0.22 A 0.33 A 0.77 A 0.28 A
 Scarlet oak 0.28 A 0.31 A 0.50 A 0.07 A
 Yellow poplar 0.29 A 0.35 A 0.86 A 0.25 A

Butt diameter of tree stem (in)

 16 0.26 A 0.32 AB 0.67 B 0.18 B
 20 0.34 A 0.40 A 1.04 A 0.37 A

Stem length (ft)

 40 0.31 A 0.24 B 0.64 B 0.27 BC
 60 0.25 A 0.33 B 0.66 B 0.19 C
 80 0.33 A 0.40 B 1.12 A 0.33 AB
 100 0.23 A 0.58 A 1.30 A 0.43 A

 Elemental tunes
 (min.)

 Swing to Cycle Productivity
 pile time (b) (MBF/PMH)

Species

 Black cherry 0.39 A 1.92 A 4.83 AB
 Chestnut oak 0.62 A 2.35 A 2.04 BC
 Red oak 0.59 A 2.19 A 3.16 ABC
 Scarlet oak 0.36 A 1.52 A 0.93 C
 Yellow poplar 0.60 A 2.33 A 6.21 C

Butt diameter of tree stem (in)

 16 0.57 B 1.98 B 3.06 B
 20 0.69 A 2.85 A 7.62 A

Stem length (ft)

 40 0.42 B 1.84 B 3.35 B
 60 0.51 B 1.92 B 3.90 B
 80 0.86 A 3.03 A 6.07 A
 100 0.80 A 3.47 A 7.70 A

(a) Means with the same letter in a column of the same group are not
significantly different at the 5 percent level with Duncan's
Multiple-Range test.

(b) Cycle time does not include delays.

Table 3.--Models to estimate times and productivity of sawbuck
bucking.

 Models (a)

Grapple time (min.) -0.0962 + 0.0011[D.sup.2] + 0.1916NL
Buck time (min.) 0.6201 - 0.0897D + 0.0034[D.sup.2] + 0.0499NL
Cycle time (c) (min.) 0.4918 + 0.00004[D.sup.2] x L + 0.3727NL
Productivity (MBF/PMH) -1.4744 + 0.0243[D.sup.2]

 [r.sup.2] MSE (b) F-value p-value

Grapple time (min.) 0.49 0.1112 42.06 0.0001
Buck time (min.) 0.45 0.0189 23.76 0.0001
Cycle time (c) (min.) 0.56 0.4532 54.43 0.0001
Productivity (MBF/PMH) 0.65 5.05 163.73 0.0001

(a) D = butt diameter of tree stem (in); NL = the number of logs
bucked per stem; L = stem length (ft).

(b) MSE = mean square error.

(c) Cycle time does not include delay.

Table 4.--Statistics of operational variables of loading operations.

 Mean SD Minimum Maximum

Logs grappled per turn
 Average small-end
 diameter (in) 10.50 3.61 3.50 20.30
 Average large-end
 diameter (in) 11.82 3.73 4.50 21.40
 Average log length (ft) 9.61 1.96 6.00 18.00
 No. of logs 2.00 0.95 1.00 4.00
 Volume of logs (BF) 54.64 47.66 0 316.41

Elemental times (min.)
 Swing to pile 0.12 0.08 0.02 0.66
 Grapple 0.05 0.07 0.02 0.65
 Swing to truck 0.17 0.08 0.07 0.75
 Ungrapple 0.08 0.06 0.01 0.31
 Rework 0.29 0.18 0.07 0.95
 Cycle time (a) 0.52 0.24 0.18 1.53
 Production estimate
 Productivity (MBF/PMH) 7.20 7.49 0.06 57.76

(a) Cycle time does not include delays.

Table 5.--Means and significance levels of statistics for loading
operations (a).

 Elemental times (min.)

 Swing to Swing to
 pile Grapple truck Ungrapple

Average small-end diameter of logs grappled per turn (in)

 8 0.12 A 0.03 A 0.16 A 0.06 A
 12 0.13 A 0.05 A 0.16 A 0.08 A
 16 0.13 A 0.04 A 0.18 A 0.07 A

Average length of logs grappled per turn (ft)

 8 0.11 B 0.05 A 0.14 B 0.08 AB
 12 0.12 B 0.04 A 0.17 AB 0.06 B
 16 0.19 A 0.05 A 0.20 A 0.11 A

Number of logs grappled per turn

 1 0.13 A 0.04 A 0.15 A 0.07 A
 2 0.13 A 0.05 A 0.18 A 0.07 A
 3 0.12 A 0.04 A 0.16 A 0.09 A

Product type
 Sawlogs 0.13 A 0.05 A 0.18 A 0.06 A
 Peeler logs 0.12 A 0.05 A 0.16 A 0.08 A
 Pulp logs 0.12 A 0.03 A 0.15 A 0.07 A

 Elemental times
 (min.)

 Cycle Productivity
 Rework time (b) (MBF/PMH)

Average small-end diameter of logs grappled per turn (in)

 8 0.23 A 0.43 B 1.65 A
 12 0.30 A 0.55 A 5.86 B
 16 0.26 A 0.48 AB 14.95 C

Average length of logs grappled per turn (ft)

 8 0.28 A 0.47 A 6.03 B
 12 0.29 A 0.50 A 7.71 B
 16 0.17 A 0.61 A 15.19 A

Number of logs grappled per turn

 1 0.26 A 0.49 A 9.38 A
 2 0.29 A 0.52 A 6.08 B
 3 0.28 A 0.56 A 8.74 AB

Product type
 Sawlogs 0.28 A 0.51 A 12.24 A
 Peeler logs 0.28 A 0.54 A 7.56 B
 Pulp logs 0.28 A 0.46 A 3.40 C

(a) Means with the same letter in a column of the same group are not
significantly different at the 5 percent level with Duncan's
Multiple-Range test.

(b) Cycle time does not include delays.

Table 6.--Models to estimate loading productivity by product type
(a).

Product
type Model (b) [r.sup.2] MSE (c)

Sawlogs -2.0967 + 0.0679[D.sup.2] 0.48 47.5480
Peeler logs 73.0558 - 7.48D - 9.2923 L + 0.68 13.0515
 0.9814D x L + 1.2626NL
Pulp logs -10.1442 + 1.2238D + 1.7058NL 0.69 3.5469

Product
type F-value p-value

Sawlogs 49.83 0.0001
Peeler logs 28.59 0.0001
Pulp logs 72.53 0.0001

(a) Productivity = MBF per productive machine hour.

(b) D = average small-end diameter of logs grappled per turn (in);
NL = the member of logs grappled per turn;

L = average log length (ft).

(c) MSE = mean square error.
COPYRIGHT 2007 Forest Products Society
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2007 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Wang, Jingxin
Publication:Forest Products Journal
Geographic Code:1U5VA
Date:May 1, 2007
Words:6413
Previous Article:Monitoring of abrasive loading for optimal belt cleaning or replacement.
Next Article:Coming events.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |