VTechWorks Repository :: Browsing by Author "Kline, D. Earl"

Browsing by Author "Kline, D. Earl"

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Activity-based product costing in a hardwood sawmill through the use of discrete-event simulation
Rappold, Patrick M. (Virginia Tech, 2006-06-02)
The purpose of this research was to quantify the impact of the log variables: length, grade, and scaling diameter, on the cost of producing hardwood lumber, using the activity-based costing technique. The usual technique of calculating hardwood lumber product costs is based upon traditional cost accounting, where manufacturing costs are allocated to the products based upon the volume of each product that is produced. With the traditional cost accounting procedure, the variation in the resources used to process the logs is not taken into consideration. As a result, when the cost to manufacture the products is subtracted from the market value of the products, the resulting profit levels of the products may not be truly representative of the actual resources consumed in manufacturing the product. Using discrete-event simulation, two hardwood sawmills were modeled and a series of experiments were conducted which would not have been feasible to conduct on the mill floors. Results from the simulation experiments illustrated that the activity-based and traditional cost accounting techniques allocated different amounts of manufacturing costs to the products. The largest difference between the two cost accounting techniques was found to be the amount of raw material costs allocated to the products. For one of the sawmills modeled, log grade was identified as having the greatest influence on determining product costs and total manufacturing costs. Results from the model of the second sawmill however demonstrated that log diameter had a greater impact on determining product costs and total manufacturing costs. The commonality of the results from the two simulation models was that the differences in the volume of lumber produced, between the logs that were studied, was a critical component in determining which log parameter had the most effect on changing the dynamics of the sawmill system. To enable hardwood managers a more precise method of allocating raw material costs to the lumber products, a methodology was developed that uses the principles of activity-based costing to allocate raw material costs. The proposed methodology, termed the lumber yield method, uses lumber yield values from logs with similar characteristics to allocate raw material costs to the lumber products. Analysis of the output from the simulation models illustrated that with the lumber yield method, the amount of raw material costs allocated to the products was not significantly different than the amount allocated by the activity-based costing method. The calculated raw material costs of the products were however, found to be significantly different between the lumber yield method and the traditional volume costing method.
Adoption of Scanning Technology in the Secondary Wood Products Industry
Cumbo II, Danny Wayne (Virginia Tech, 1999-10-04)
A mail survey of wood cabinet, furniture, dimension, and flooring manufacturers was undertaken across the US to assess the market potential for automated lumber grading technology in the secondary wood products industry. Two hundred and nine usable responses were received providing information related to the identification of adopters of scanning technology, the optimum benefit bundle to increase the marketable success of automated lumber grading technology, and the best methods of promotion to this industry. The results indicate that potential adopters of automated lumber grading technology will most likely be larger companies both in terms of annual sales and number of employees. In addition, adopter companies will be more likely to market their products in international markets. Results show that dimension and flooring manufacturers perceive this technology as more beneficial to their industries than cabinet and furniture manufacturers. Analysis showed that significant differences existed between the four industry sectors on various machine attributes. In addition, dimension and flooring manufacturers rated machine attributes higher than cabinet and furniture manufacturers where significant differences were detected. This indicates that dimension and flooring manufacturers place more importance on various machine attributes than cabinet and furniture manufacturers when considering the adoption of automated lumber grading technology. Optimal benefit bundles were characterized for each industry sector. While these benefit bundles differed among sectors, the differences where slight. Machine accuracy, simplicity of operation, technical support, and reduction in labor costs were important attributes to most sectors. The best methods of promotion to the secondary wood products industry included trade shows, peer discussions, and plant visits. In addition, these three methods were most effective in promotion for the individual industry sectors as well. Advertisements, meetings and symposiums, scientific journals, and unsolicited sales literature were not rated as highly effective methods of promotion to the cabinet, furniture, dimension, and flooring industries.
An Application of Lean Thinking to the Furniture Engineering Process
Wang, Chao (Virginia Tech, 2011-03-21)
Efficient engineering processes are critically important for furniture manufacturers. Engineering impacts the production cost, design quality, product lead time, and customer satisfaction. This research presents a systematic approach to analyze a furniture engineering process through a case study. The research was conducted through a case study in a furniture plant located in China, producing American style furniture products. The first stage was to investigate the company's current engineering process, identify non value-added activities, and analyze the engineering performance based on selected Key Performance Indicators (KPIs) such as lead time, document error rate, and engineering throughput. A survey questionnaire was sent out to the engineering group to determine the current engineering efficiency. Results show that "product complexity" and "engineer competency" are the two most influential factors that impact engineering lead time and quality. In the second stage, value stream mapping was used to analyze an upholstery furniture engineering process. The approach encompasses an analysis of the current state of the engineering process and the proposal of a lean future state value stream map (VSM). Results from the current state VSM show, that the value-added ratio of the current engineering process is only 26%. Several engineering steps present deficiency such as the processes of creating drawings, compile mass production documents, check and sign-off engineering documents, create CNC programs, and generate packaging files. Based on current state VSM analysis, the researcher focused on transforming these processes to eliminate waste and to propose the best practices for the future state VSM. From this research, it shows that current processes include a large amount of non-value adding activities such as waiting, extra processing, rework, excess motion, transportation, underutilized people, and inefficient information. These non-value adding activities are interfering with engineers' ability to prepare engineering documents for downstream jobs and affecting the overall manufacturing process. The VSM is effective to provide the visual control over the engineering process for implementing lean transformations.
Assessing sustainability of the continuous improvement process through the identification of enabling and inhibiting factors
Madrigal, Johanna (Virginia Tech, 2012-08-09)
This research presents results of innovation management practices and sustainability of continuous improvement. Innovation is recognized as a growth tool for economies in general however not all economy sectors have innovation as a strategy. This research served as a case study to analyze how innovation is managed within innovative firms to help less innovative sectors, such as the wood products industry, to become profitable. Among the observed innovation management practices, this study was able to identify the use of continuous improvement to support incremental innovation. Although, continuous improvement is well known and accepted, there are still challenges to reach a sustainable state of continuous improvement. This research also addresses the difficulty in sustaining continuous improvement through a longitudinal case study. A literature review was conducted to identify factors influencing the sustainability of the continuous improvement. These factors were gathered within a research framework which functioned as the main source to establish the questionnaire used as the research tool. Utilizing this tool, the study evaluated the hypotheses relating to the effects of time, location and company type on the behavior of the enabling and inhibiting factors, and the relationships among them. Results demonstrated that time has no effect on factors affecting the sustainability of the continuous improvement, although changes affect how the factors are perceived as success factors in sustaining continuous improvement. The study also concluded that type of company and location impact how the inhibiting and enabling factors are perceived as supporters of the sustainability of the continuous improvement. Finally, the study revealed that these factors are correlated among them, thus sustainability is the result of a dynamic multifactor process rather that an unique factor. In addition to this new framework, the study also developed a self-assessment tool to be used for continuous improvement practitioners. With this tool, the new developed framework can be continuously monitored and proper and informed action can be taken by managers to address any observed gap in sustaining continuous improvement. Finally, the study also brings an example of interdisciplinary research which gathers quantitative methods from the statistics field, and qualitative methods from the business and social science fields.
Automated Detection of Surface Defects on Barked Hardwood Logs and Stems Using 3-D Laser Scanned Data
Thomas, Liya (Virginia Tech, 2006-09-08)
This dissertation presents an automated detection algorithm that identifies severe external defects on the surfaces of barked hardwood logs and stems. The defects detected are at least 0.5 inch in height and at least 3 inches in diameter, which are severe, medium to large in size, and have external surface rises. Hundreds of real log defect samples were measured, photographed, and categorized to summarize the main defect features and to build a defect knowledge base. Three-dimensional laser-scanned range data capture the external log shapes and portray bark pattern, defective knobs, and depressions. The log data are extremely noisy, have missing data, and include severe outliers induced by loose bark that dangles from the log trunk. Because the circle model is nonlinear and presents both additive and non-additive errors, a new robust generalized M-estimator has been developed that is different from the ones proposed in the statistical literature for linear regression. Circle fitting is performed by standardizing the residuals via scale estimates calculated by means of projection statistics and incorporated in the Huber objective function to bound the influence of the outliers in the estimates. The projection statistics are based on 2-D radial-vector coordinates instead of the row vectors of the Jacobian matrix as proposed in the statistical literature dealing with linear regression. This approach proves effective in that it makes the GM-estimator to be influence bounded and thereby, robust against outliers. Severe defects are identified through the analysis of 3-D log data using decision rules obtained from analyzing the knowledge base. Contour curves are generated from radial distances, which are determined by robust 2-D circle fitting to the log-data cross sections. The algorithm detected 63 from a total of 68 severe defects. There were 10 non-defective regions falsely identified as defects. When these were calculated as areas, the algorithm locates 97.6% of the defect area, and falsely identifies 1.5% of the total clear area as defective.
An automatic method for inspecting plywood shear samples
Avent, R. Richard (Virginia Tech, 1990-06-07)
Plywood is composed of several thin layers of wood bonded together by glue. The adhesive integrity of the glue formulation employed must surpass the structural integrity of the wood species within a given panel of plywood. The American Plywood Association (APA) regularly tests the plywood produced at various plywood manufacturing plants to ensure that this particular performance requirement is consistently met. One of the procedures used by the APA to test this requirement consists of 1) milling a plywood panel to be tested into small rectangular blocks called samples, 2) conditioning these samples with various treatments to simulate natural aging, 3) shearing each sample into two halves, and 4) estimating the percent wood failure (as opposed to glue failure) produced by the shear by visually inspecting these sample halves. A region of solid wood or a region of wood fibers embedded in glue on the shear of a sample half is a region of wood failure while a region of glue is a region of glue failure. If the wood failure of samples from a significant number of panels is too low, the right to use APA trademarks is withdrawn from the plant where the sampling occurred. Since measurements obtained by human visual inspection can contain inaccuracies due to fatigue, boredom, state of mind, etc., an automatic vision system to determine percent wood failure is proposed. The method presented is a refinement of the method developed by McMillin and is divided into three tasks. The first task is to locate the area of shear on a given sample half. The second task is to distinguish the areas of wood from the areas of glue on the shear of a sample half. Solid wood is distinguished from glue based on the difference in gray level intensity that exists between solid wood and glue. Wood fiber is distinguished from glue based on the difference in texture, i.e., edge patterns, that exists between fiber and glue. The third task is to compare the areas of shear on the two sample halves comprising a sample to determine the percent wood failure of the sample.
Benchmarking Performance Measurement and the Implementation of Lean Manufacturing in the Secondary Wood Processing Rough Mill
Cumbo, Dan; Kline, D. Earl; Van Aken, Eileen M.; Smith, Robert L. (Virginia Tech, 2004-09)
It is hypothesized that, while other components of the secondary wood products value stream; e.g., moulding, turning, sanding, etc, are being integrated and “leaned up” so to speak, the rough mill represents a real or perceived barrier to full implementation of lean manufacturing tools, techniques and concepts. This study investigated the implementation of lean manufacturing in the rough mill as well as performance measurement and metrics at both the rough mill and overall business level. Data were collected from a nationwide survey of secondary wood processing facilities.
Breaking down barriers: Market opportunities for Appalachian forest products in Central America
Lyon, Scott (Virginia Tech, 2011-07-08)
The research purpose was to determine strengths and weaknesses of Appalachian wood products sales in Central America. In the future, there may be a greater need for international forest products in Central America due to increasing population size, tourism, and deforestation. Potential market opportunities for Appalachian forest product companies in Central America were evaluated and strategies were developed to increase exports from Appalachian wood product companies. Interviews of Central American wood products wholesalers and government and non-government officials were conducted to determine the current situation of the forest, the demand for local wood production, and potential for future production of wood products. A survey of wood products retailers and manufacturers was conducted to determine drivers and barriers of the sale of Appalachian wood products in Central America. Models were developed to describe relationships between company performance and suppliers and a series of independent variables (e.g, supplier promotion, product attributes). Results suggested that U.S. wood products companies have not put enough effort into marketing forest products in Central America. Central American wood products consumers lack knowledge of Appalachian wood products and their advantages over wood products currently used. Inconsistencies between Appalachian and Central American wood products industries (e.g., dimensions, species terminology) act as a barrier to efficient exchange of wood products. Models suggest that companies may need to focus on barriers to increase company performance. The best market strategies for Appalachian forest products companies to increase sales into Central America are: partner with local wholesalers, offer higher value-added products, maintain similar pricing with competition, and offer sales and product discounts.
Characterization of Wood Features Using Color, Shape, and Density Parameters
Bond, Brian H. (Virginia Tech, 1998-02-09)
Automated defect detection methods allow the forest products industry to better utilize its resources by improving yield, reducing labor costs, and allowing minimum lumber grades to be utilized more intelligently. While many methods have been proposed on what sensors and processing methods should be used to detect and classify wood features, there exists a lack of understanding of what parameters are best used to differentiate wood features. The goal of this research is to demonstrate that by having an in depth knowledge of how wood features are represented by color, shape, and density parameters, more accurate classification methods can be developed. This goal was achieved through describing wood features using parameters derived from color and x-ray images and characterizing the variability and interrelationships of these parameters, determining the effect of resolution and species on these relationships, and determining the importance and contribution of each parameter for differentiating between wood features using a statistical prediction model relating feature types to the parameters. Knots, bark pockets, stain and mineral streak, and clearwood were selected as features from red oak, (Quercus rubra), hard maple, (Acer saccharum), and Eastern white pine (Pinus stobus). Color (RGB and HSI), shape (eccentricity and roundness), and density (gray-scale values) parameters were measured. Parameters were measured for each wood feature from images and parameter differences between feature types were tested using analysis of variance techniques (ANOVA) and Tukey's pairwise comparisons with a=0.05. Discriminant classifiers were then developed to demonstrate that an in-depth knowledge of how parameters relate between feature types could be used to develop the best possible classification methods. Classifiers developed using the knowledge of parameter relationships were found to provide higher classification accuracies for all features and species than those which used all parameters and where variable selection procedures had been used< It was determined that differences exist between all feature types and can be characterized and classified based on two color means, one color standard deviation, the mean density, and a shape parameter. A reduction in image resolution was determined not to affect the relationship of parameters. For different species, the intensity of features was to be related to the intensity of clearwood. The ability to explain classification errors using the knowledge gained about feature parameters was demonstrated. This knowledge could be used to reduce future classification errors. It was determined that combining parameters collected using multiple sensors increases classification accuracy of wood features. Shape and density were found not to provide good classification variables for features when used separately, but were found to contribute to classification of features when used with other parameters. The ability to differentiate between the feature types examined in this research was found be equal when using the RGB or HSI colorspace.
Comparison of the Economic Feasibility between Conventional and Vacuum Drying for 4/4 Red Oak
Brenes-Angulo, Oxana; Bond, Brian H.; Kline, D. Earl; Quesada, Henry Jose (Forest Products Society, 2017-01-01)
Vacuum drying of wood is a method to reduce drying time and inventory; however, there is limited information regarding the economic feasibility for vacuum drying 4/4 red oak compared with traditional drying methods. The benefits of this technology, mainly dramatically reduced drying times and higher flexibility, must be weighed against the higher initial capital investment. The goal of this project was to compare the economic feasibility, using capital budgeting techniques, of conventional drying and vacuum drying for 4/4 red oak lumber. The analysis was conducted for two actual flooring manufacturers. Conventional drying for this analysis was considered to be air-drying plus kiln drying, which is commonly done with red oak. The vacuum technology considered used hot platens for heating the wood. Species, thickness, drying methods, and lumber demand compared, both drying methods (conventional and vacuum drying) were determined to be economically feasible. However, vacuum drying had a slightly higher net present value, cost–benefit ratio, and sensitivity analysis than conventional drying, making it a slightly better investment for drying 4/4 red oak. The initial tied-up inventory and its respective cost in the conventional drying scenario represents an opportunity cost that can be recovered using vacuum drying. This recovered cost can result in freed capital that can be invested elsewhere to increase competitiveness.
Computer simulation of hourly dry-bulb temperatures
Kline, D. Earl; Reid, John F.; Woeste, Frank E. (Virginia Agricultural Experiment Station, 1982)
A computer model of hourly dry-bulb temperatures was developed for Blacksburg, Virgi nia, from a 9-year sample of hourly dry-bulb temperature data. The periodic variations over the course of a year were estimated by least-square approximation. A first order Markov chain model was used to simulate the stochastic nature of temperature. These two models were combined to simulate years of hourly dry-bulb temperatures.
Correlation of the Elastic Properties of Stretch Film on Unit Load Containment
Bisha, James Victor (Virginia Tech, 2012-05-24)
The purpose of this research was to correlate the applied material properties of stretch film with its elastic properties measured in a laboratory setting. There are currently no tools available for a packaging engineer to make a scientific decision on how one stretch film performs against another without applying the film. The system for stretch wrap comparison is mostly based on trial and error which can lead to a significant loss of product when testing a new film or shipping a new product for the first time. If the properties of applied stretch film could be predicted using a tensile test method, many different films could be compared at once without actually applying the film, saving time and money and reducing risk. The current method for evaluating the tensile properties of stretch film advises the user apply a hysteresis test to a standard sample size and calculate several standard engineering values. This test does not represent how the material is actually used. Therefore, a new tensile testing method was developed that considers the film gauge (thickness) and its prestretch. The results of this testing method allowed for the calculation of the material stiffness (Bisha Stiffness) and were used to predict its performance in unit load containment. Applied stretch film is currently compared measuring containment force, which current standards define as the amount of force required to pull out a 15.2cm diameter plate, 10.1cm out, located 25.4cm down from the top and 45.7cm over from the side of a standard 121.9cm width unit load. Given this definition, increasing the amount of force required to pull the plate out can be achieved by manipulating two different stretch film properties, either increasing the stiffness of the film or increasing the tension of the film across the face of the unit load during the application process. Therefore, for this research, the traditional definition of containment force has been broken down into two components. Applied film stiffness was defined as the amount of force required to pull the film a given distance off the unit load. Containment force was defined as the amount of force that an applied film exerts on the corner of the unit load. The applied stretch film was evaluated using two different methods. The first method used the standard 10.1cm pull plate (same plate as ASTM D 4649) to measure the force required to pull the film out at different increments from the center on the face of the unit load. This measurement force was transformed into a material stiffness and film tension (which were subsequently resolved into containment force). The second, newly developed, method involved wrapping a bar under the film, on the corner of the unit load, and pulling out on the bar with a tensile testing machine. This method allowed for the direct measurement of the containment force and material stiffness. The results indicated that while some statistically significant differences were found for certain films, the material stiffness and containment were relatively consistent and comparable using either method.The use of the Bisha Stiffness to predict the applied stiffness and containment force yielded a statistically significant correlation but with a very low coefficient of determination. These results suggest that while film thickness and prestretch are key variables that can predict applied stiffness and containment force, more research should be conducted to study other variables that may allow for a better. High variability of the predictions observed were caused by the differences in film morphology between the different method of elongation (tensile vs application). This study was the first that attempted to define and correlate the tensile properties of stretch film and the applied properties of stretch film. From this research many, terms have been clarified, myths have been dispelled, formulas have been properly derived and applied to the data collected and a clear path forward had been laid out for future researchers to be able to predict applied stiffness and containment force from the elastic properties of stretch film.
A Design Methodology for Creating Programmable Logic-based Real-time Image Processing Hardware
Drayer, Thomas Hudson (Virginia Tech, 1997-01-24)
A new design methodology that produces hardware solutions for performing real-time image processing is presented here. This design methodology provides significant advantages over traditional hardware design approaches by translating real-time image processing tasks into the gate-level resources of programmable logic-based hardware architectures. The use of programmable logic allows high-performance solutions to be realized with very efficient utilization of available logic and interconnection resources. These implementations provide comparable performance at a lower cost than other available programmable logic-based hardware architectures. This new design methodology is based on two components: a programmable logic-based destination hardware architecture and a suite of development system software. The destination hardware architecture is a Custom Computing Machine (CCM) that contains multiple Field Programmable Gate Array (FPGA) chips. FPGA chips provide gate-level programmability for the hardware architecture. Sophisticated software development tools, called the TRAVERSE development system software, are created to overcome the significant amount of time and expertise required to manually utilize this gate-level programmability. The new hardware architecture and development system software combine to establish a unique design methodology. There are several distinct contributions provided by this dissertation. The new flexible MORRPH hardware architecture provides a more efficient solution for creating real-time image processing computing machines than current commercial hardware architectures. The TRAVERSE development system software is the first integrated development system specifically for creating real-time image processing designs with multiple FPGA-based CCMs. New standards and design conventions are defined specifically for creating solutions to low-level image processing tasks, using the MORRPH architecture for verification. The circuit partitioning and global routing programs of the TRAVERSE development system software enable automated translation of image processing designs into the resources of multiple FPGA chips in the hardware architecture. In a broad sense, the individual contributions of this dissertation combine to create a new design methodology that will change the way hardware solutions are created for real-time image processing in the future.
Developing a flexible range sensing system for industrial inspection applications
Hou, Yoshen (Virginia Tech, 1993-06-15)
This thesis describes the development of a range sensing system. The goal was to create a range sensor that is robust and flexible so that a number of applications within the forest products manufacturing environment can be addressed. Features of the system include: the capability of producing spatially registered image pairs of range and intensity, the ability to generate both range and intensity very quickly, the applicability to a wide variety of industrial applications, the ability to handle large depth-of-field range sensing problems, the ability to do real-time data processing, and the capability to do extensive system diagnostics under complete software control. A triangulation based plane-of-light optical method is employed to extract range information. The research shows that this method suits range sensing applications where conveyor belts are involved. An in-depth study of the triangulation method is included. In the study it shows that this method also supports large depth-of-field range sensing. A dedicated signal processing hardware, built on the Micro Channel interface, performs pipelined image processing and generates range and intensity images in a spatially registered form. The hardware is designed to support several modes of operation, for the purpose of facilitating optical adjustments and calibrations. The hardware self-diagnostic facility is also included in the design. A memory management scheme is provided that facilitates real-time data processing of the range and intensity images. The experiments show that this scheme provides a real-time environment for software processing. This thesis also contains a theory exploring the limitations of the measurement accuracy of the range detection algorithm employed in the prototype system. The maximum data generation rate of the prototype system is 380 range/intensity lines per second at 128 range/intensity pixels per line. Several proposals toward future work are included that aim at improving the speed as well as the measurement accuracy of the prototype system.
Development of root observation method by image analysis system
Kim, Giyoung (Virginia Tech, 1995-12-05)
Knowledge of plant roots is important for determining plant-soil relationships, managing soil effectively, studying nutrient and water extraction, and creating a soil quality index. Plant root research is limited by the large amount of time and labor required to wash the roots from the soil and measure the viable roots. A root measurement method based on image analysis was proposed to reduce the time and labor requirement. A thinning algorithm-based image analysis method was used to measure corn root length at the planar faces cut from a core sample. The roots were exposed by careful handling and contrasted from the soil by causing autofluorescence using long-wave ultraviolet light. The contrast-enhanced images were stored on the camcorder video tape and digitized by frame grabber. A binary root image was acquired from the digitized gray scale image by a thresholding operation. The binary root image was thinned until the roots were reduced to their basic structure. Root length was calculated from the number of pixels of the root's basic structure. This root length was divided by the removed soil volume of the profile of the core sample to estimate the root length density (RLD, cm root cm⁻³ soil). This estimated RLD was regressed on RLD, measured from washed roots in the same soil core sample, and a linear relationship (R² = 0.96) was obtained. This study indicated that the image analysis root measurement method can determine the length of corn root systems up to 2.5 times faster than by using the conventional method which incorporates a root washing procedure.
Dynamic modeling of branches and knot formation in loblolly pine (Pinus taeda L.) trees
Trincado, Guillermo (Virginia Tech, 2006-06-15)
A stochastic framework to simulate the process of initiation, diameter growth, death and self-pruning of branches in loblolly pine (Pinus taeda L.) trees was developed. A data set was obtained from a destructive sampling of whorl sections from 34 trees growing under different initial spacing. Data from dissected branches were used to develop a model for representing knot shape, which assumed that the live portion of a knot can be modeled by a one-parameter equation and the dead portion by assuming a cylindrical shape. For the developed knot model analytical expressions were derived for estimating the volume of knots (live/dead portions) for three types of branch conditions on simulated trees: (i) live branches, (ii) non-occluded dead branches, and (iii) occluded dead branches. This model was intended to recover information on knots shape and volume during the simulation process of branch dynamics. Three different components were modeled and hierarchically connected: whorl, branches and knots. For each new growing season, whorls and branches are assigned stochastically along and around the stem. Thereafter, branch diameter growth is predicted as function of relative location within the live crown and stem growth. Using a taper equation, the spatial location (X,Y,Z) of both live and dead portion of simulated knots is maintained in order to create a 3D representation of the internal stem structure. At the end of the projection period information on (i) vertical trend of branch diameter and location along and around the stem, (ii) volume of knots, and (iii) spatial location, size and type (live and dead) of knots can be obtained. The proposed branch model was linked to the individual-tree growth and yield model PTAEDA3.1 to evaluate the effect of initial spacing and thinning intensity on branch growth in sawtimber trees. The use of the dynamic branch model permitted generation of additional information on sawlog quality under different management regimes. The arithmetic mean diameter of the largest four branches, one from each radial quadrant of the log (i.e. Branch Index, BI) and the number of whorls per log were considered as indicators of sawlog quality. The developed framework makes it possible to include additional wood properties in the simulation system, allowing linkage with industrial conversion processes (e.g. sawing simulation). This integrated modeling system should promote further research to obtain necessary data on crown and branch dynamics to validate the overall performance of the proposed branch model and to improve its components.
Evaluation of a direct processing system for converting no. 3 grade red oak logs into rough dimension parts
Lin, Wenjie (Virginia Tech, 1993)
The primary objective of this study was to assess the economic feasibility and profitability of the direct processing system for converting No.3 grade red oak logs into rough dimension parts. In the first part of this study, the cutting yields of green dimension parts and dollar value recovery from No.3 grade red oak logs by the direct processing system were estimated. A combination method of actual log sawing and simulated cutting was used to obtain the dimension yields. Two sawing patterns (live-sawing and five-part-sawing) and two cutting sequences (rip-first and crosscut-first) were tested for their effects on dimension yields, cutting lengths, and dollar value recovery. It was found that live-sawing resulted in significantly higher dimension yield than five-part-sawing. If followed by rip-first, live-sawing also resulted in higher dollar value recovery than five-part-sawing. Rip-first and crosscut-first has no significant differences in dimension yield, however, rip-first can recover more dollar value than crosscut-first if longer cuttings have higher value. The results of this study indicated that the combination of live-sawing and rip-first has the highest dimension yield and dollar value recovery if longer cuttings have higher value. In the second part of this study, the mill designs of the direct processing system for the various sawing patterns and cutting sequences were developed. The computer simulation/animation models for these designs were built using SIMAN IV/CINEMA. These models were used to predict the dynamic performances and production rates of the various mill designs. Based on simulation results, the direct processing system with one headrig saw can process from 17.8 to 20.5 MBF No.3 grade red oak logs and turn out 11 to 14.3 MBF Clear-two-face, 4/4 random width green dimension parts per shift. In the third part of this study, a financial analysis using discounted cash flow methods was conducted over a ten year planning horizon to determine the economic feasibility of the direct processing system that processes No.3 grade red oak logs directly into rough dimension parts. Under the assumptions of this study, measured by both Net Present Value (NPV) and Internal Rate of Return (IRR), all of the six designs evaluated are economically acceptable. With the highest NPV of $4,193,700 and the highest IRR of 29.6 percent, the design that uses live-sawing and rip-first with manual chop saws was found to be the most economically attractive selection. The profitability of the direct processing system, measured in ROS (Return on Sales), was estimated and compared with the reported profitability for the hardwood dimension and flooring industry. The results indicated that the direct processing system are more profitable than the conventional processing system for making dimension parts. The sensitivities of NPV and ROS to the changes in dimension part price, log price, labor cost, overhead cost, capital investment, weighting factor for part lengths, green cutting yield and drying and remanufacturing loss were analyzed. Dimension part price, green cutting yield and drying and remanufacturing loss were found to be the most important factors that affect the economic feasibility and profitability of the direct processing system.
Evaluation of color-based machine vision for lumber processing in furniture rough mills
Widoyoko, Agus (Virginia Tech, 1996)
This research study examined the potential application of a color-based machine vision system under development at Virginia Tech for lumber processing in the furniture rough mill. The evaluation was done by conducting a yield study using 134 red oak boards. ROMI-RIP, a rip-first simulation program by Thomas (1995), was used to simulate yields for both the manually digitized lumber data and the machine vision scanned lumber data. The color-based machine vision system was evaluated by comparing the optimum yield obtainable when using lumber data derived from the automatic scanning system to: (1) observed yield from an existing state-of-the-art rip-first rough mill and (2) the optimum yield from manually digitized lumber data. Overall, the color-based machine vision system resulted in about 17 percent lower yield than was measured in the rough mill and 20 percent lower than the optimum, based on manually digitized lumber data. An analysis of the yield percentage point difference between the machine vision-based yields and optimal yields indicates: (1) approximately 11.5 yield points were lost due to errors in defect detection accuracy, (2) 7.3 yield points were lost due to errors in the machine vision material handling system, and (3) 1.3 yield points were lost due to data digitization and truncation errors. Since material handling, data digitization, and truncation problems are solvable with current technologies, future research should focus on developing systems that can improve the accuracy of feature recognition in lumber.
An Examination of Appalachian Forest Products Exports
Parsons, Brigitte A. (Virginia Tech, 2003-04-17)
The primary goal of this study was to identify value added export opportunities for the hardwood products manufacturing industry. By studying current industry practices and trends, we can better understand the opportunities hardwood lumber businesses have exploited in the past and could do so today. The study found that opportunities exist for businesses with the right initial mindset preparing them for exporting, the proper equipment, and the appropriate educational experience. Surveys of hardwood lumber manufacturers in 1989 and 2002 addressed similar objectives and helped better understand export participation of hardwood lumber manufacturers in the Appalachian Region. The objectives of this research project included determining current export experience, access and use of export development programs, key export markets, and mill production, marketing, equipment, personnel and other attributes of the region's hardwood lumber industry. Other objectives included determining if any significant changes in the region's hardwood industry had occurred, and in particular, what was mill export market experience in the past 15 years. The key was to identify key factors that lead to export marketing participation. This study showed that export market participation is growing as forest sector businesses consolidated during this period. Businesses were found to seek assistance from multiple government agencies, trade associations, and most importantly from their customers. While the largest export market continues to be Canada, little information is available on other businesses purchasing Appalachian hardwood lumber, indicating the need for more research on markets and their size. Important species for exporting are red oak, yellow-poplar, white oak, and maple, and higher grades of hardwood lumber continue to be the top three. Owning a kiln is essential to exporting, and having an above average size marketing staff was found to be helpful. The most important attribute of exporters is an open-minded management that sees the benefits of exporting.
A feasibility study on using CT image analysis for hardwood log inspection
Zhu, Dongping (Virginia Tech, 1993)
To fully optimize the value of material produced from a log requires information about the log's internal defects prior to log breakdown. Studies have shown that a 7 to 21 percent improvement in log value recovery can be achieved if the location and identity of internal defects are known. Recent developments in advanced nondestructive testing methods such as CT and MRI offer, for the first time, the possibility of finding internal defects in logs prior to breakdown. Our ability to detect and recognize defects using this data depends Critically on our understanding of wood structure and our ability to devise reliable method for automated image interpretation. While a lot of work has gone into demonstrating that certain types of defects manifest themselves in such sensor imagery, there has not been a systematic approach toward making the automatic inspection of logs a practical reality. This dissertation describes work aimed at creating a viable automated technology for locating and identifying log defects. The imaging modality used in this dissertation is CT. An important first step is to establish a data base of imagery and the ground truth information to determine how the various defects manifest themselves in this imagery. The second step is to study defect characterization and determine exactly which defects are detectable. The final step is to develop a basic method of approach to automated image analysis. A data base has been created from two hardwood species. It is representative of hardwood logs in the sense that it contains almost all the major defects. Visual inspection and analysis of these CT images have shown that most defects manifest themselves in CT imagery. These defects can be detected by features such as intensity, 3-d shape, and texture. As a means of automated image analysis, a knowledge-based vision system has been developed. It consists of three components: a data acquisition unit, an image segmentation module, and scene analysis module. A 3-d adaptive LS filter has been developed in the segmentation module that is efficient in removing annual rings while preserving other needed high frequency detail. Images are segmented using a multiple threshold scheme and regions are grouped using a 3-d connected volume growing algorithm. To represent the 3-d nature of wood defects, a set of basic features have been defined and used to design a set of hypothesis tests. These features seem to be adequate for defect recognition. To cope with imprecision and ambiguity the Dempster-Shaffer model for knowledge representation is used in the vision system. As a viable alternative to Bayesian-based theory, the Dempster's method of evidential reasoning is employed that uses previously unavailable information such as the amount of ignorance and ambiguity a hypothesis exhibits. As such, the proposed vision system seems to be able to recognize a number of hardwood defects. This dissertation also explores wood texture as an additional feature in defect recognition, and contributes the first application of robust Spatial AutoRegressive modeling to wood texture analysis. Based on a correlation measure, two simple but efficient texture discrimination schemes are proposed. Incorporating a texture test in the scene analysis should improve the vision system's recognition power. As a pilot research, this dissertation has explored a number of important issues in creating a vision system for automated log inspection. Clearly, more work is needed to make the system more robust with additional species. Nevertheless, preliminary results seem to indicate that a machine vision system for automated hardwood log inspection can be developed.

Browsing by Author "Kline, D. Earl"

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