@article{saloni_buehlmann_lemaster_2011, title={Tool Wear When Cutting Wood Fiber-Plastic Composite Materials}, volume={61}, ISSN={["0015-7473"]}, DOI={10.13073/0015-7473-61.2.149}, abstractNote={Wood fiber–plastic composite materials, a relatively new material, are finding applications mainly in the US residential and commercial construction markets. Thus, the volume of material produced and used is steadily increasing while the range of applications keeps expanding. So far, attention has been paid mainly to primary production processes of wood fiber–plastic materials, while secondary manufacturing processes have attracted less attention. However, with the broadening applications of such materials and their increasing use, secondary manufacturing processes for wood fiber–plastic materials are gaining importance. This study investigated the performance of five commercially available wood fiber–plastic composite materials and solid wood (eastern white pine) with respect to tool wear and resulting material surface roughness. Large performance differences between different wood fiber–plastic composite materials and between solid wood and wood fiber–plastic composite materials with respect to tool wea...}, number={2}, journal={FOREST PRODUCTS JOURNAL}, author={Saloni, Daniel and Buehlmann, Urs and Lemaster, Richard L.}, year={2011}, pages={149–154} }
 @article{buehlmann_saloni_lemaster_2009, title={Performance of woodfiber-plastic composites subjected to abrasive machining}, volume={59}, number={6}, journal={Forest Products Journal}, author={Buehlmann, U. and Saloni, D. and Lemaster, R. L.}, year={2009}, pages={61–64} }
 @article{buehlmann_zuo_2008, title={Investigating the influence of lumber sample subsets on simulated rough mill part yields}, volume={58}, number={10}, journal={Forest Products Journal}, author={Buehlmann, U. and Zuo, X. Q.}, year={2008}, pages={84–90} }
 @article{buehlmann_zuo_thomas_2008, title={Performance evaluation of the least-cost lumber grade-mix solver}, volume={40}, number={3}, journal={Wood and Fiber Science}, author={Buehlmann, U. and Zuo, X. G. and Thomas, R. E.}, year={2008}, pages={427–435} }
 @article{bumgardner_buehlmann_schuler_wisdom_2005, title={Approaches to, and perceived benefits of, training in the secondary wood industry}, volume={37}, number={3}, journal={Wood and Fiber Science}, author={Bumgardner, M. S. and Buehlmann, U. and Schuler, A. T. and Wisdom, B. B.}, year={2005}, pages={384–393} }
 @article{bumgardner_buehlmann_schuler_christianson_2004, title={Domestic competitiveness in secondary wood industries}, volume={54}, number={10}, journal={Forest Products Journal}, author={Bumgardner, M. and Buehlmann, U. and Schuler, A. and Christianson, R.}, year={2004}, pages={21–28} }
 @article{zuo_buehlmann_thomas_2004, title={Investigating the linearity assumption between lumber grade mix and yield using design of experiments (DOE)}, volume={36}, number={4}, journal={Wood and Fiber Science}, author={Zuo, X. Q. and Buehlmann, U. and Thomas, R. E.}, year={2004}, pages={547–559} }
 @article{buehlmann_zuo_thomas_2004, title={Linear programming and optimizing lumber quality composition in secondary hardwood dimension mills}, volume={218}, ISSN={["0954-4054"]}, DOI={10.1243/095440504772830291}, abstractNote={ Linear programming has been widely applied in the secondary hardwood dimension manufacturing industries to solve the least-cost lumber grade mix problem, which refers to the search for minimal raw material costs. Most existing models are based on the assumption of a simple linear relationship between lumber grade mix and yield. However, this crucial assumption has never been verified.  In this study, the results from a five-factor mixture design statistically proved that none of the cutting bills tested has a simple linear relationship between yield and different lumber grade mixes. It was observed that cutting bill characteristics and lumber quality affect the relationship between yield and lumber grades. Cutting bills that require wider and/or longer parts tend to behave non-linearly. In addition, the more dissimilar lumber grade qualities that are processed, the more likely is the occurrence of a non-linear response.  The inability to predict the relationship between yield and lumber grades, coupled with the high percentage of non-simple linear relationships observed in this study, brings into question the validity of the linearity assumption applied in previous linear programming models. Further efforts are needed to construct a new least-cost lumber grade mix model that does not rely on the assumption of a simple linear relationship between lumber grade mix and yield. }, number={1}, journal={PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE}, author={Buehlmann, U and Zuo, X and Thomas, RE}, year={2004}, month={Jan}, pages={143–147} }
 @article{buehlmann_wiedenbeck_kline_2003, title={Effect of cutting bill requirements on lumber yield in a rip-first rough mill}, volume={35}, number={2}, journal={Wood and Fiber Science}, author={Buehlmann, U. and Wiedenbeck, J. K. and Kline, D. E.}, year={2003}, pages={187–200} }
 @article{thomas_buehlmann_2003, title={Performance review of the ROMI-RIP rough mill simulator}, volume={53}, number={3}, journal={Forest Products Journal}, author={Thomas, E. and Buehlmann, U.}, year={2003}, pages={80–85} }
 @article{buehlmann_thomas_2002, title={Impact of human error on lumber yield in rough mills}, volume={18}, ISSN={["1879-2537"]}, DOI={10.1016/S0736-5845(02)00010-8}, abstractNote={Rough sawn, kiln-dried lumber contains characteristics such as knots and bark pockets that are considered by most people to be defects. When using boards to produce furniture components, these defects are removed to produce clear, defect-free parts. Currently, human operators identify and locate the unusable board areas containing defects. Errors in determining a defect and its location, known as operator error, lead to lower lumber yield and increased product cost. Technology exists that would alleviate these problems and is a viable option to avoid wasting lumber because of human error. This study was performed in a rough mill collecting data on the errors made by humans when marking defects. Computer-based simulation tools were used to assess the significance of these errors. It was found that three-quarters of the decisions made by human operators are erroneous in some way resulting in an absolute yield loss of approximately 16.1%. Thus, automated defect detection systems that perform more accurately than do humans could have a payback period of 1 year or less.}, number={3-4}, journal={ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING}, author={Buehlmann, U and Thomas, RE}, year={2002}, pages={197–203} }
 @article{thomas_buehlmann_2002, title={Validation of the ROMI-RIP rough mill simulator}, volume={52}, number={2}, journal={Forest Products Journal}, author={Thomas, E. R. and Buehlmann, U.}, year={2002}, pages={23–29} }
 @article{buehlmann_thomas_2001, title={Lumber yield optimization software validation and performance review}, volume={17}, number={1-2}, journal={Robotics and Computer-Integrated Manufacturing}, author={Buehlmann, U. and Thomas, R. E.}, year={2001}, pages={27–32} }
 @article{buehlmann_ragsdale_gfeller_2000, title={A spreadsheet-based decision support system for wood panel manufacturing}, volume={29}, ISSN={["0167-9236"]}, DOI={10.1016/S0167-9236(00)00072-5}, abstractNote={Wood paneling manufacturers face a number of complex decisions when trying to allocate production resources and combine various raw materials to meet production goals. While various linear programming formulations for this problem have been proposed, these models are often difficult to use and maintain for real-time decision making in a dynamic shop floor environment. This paper describes an MS Excel-based decision support system for wood panel manufacturing. The system is easy to use and maintain yet gives shop floor personnel access to powerful optimization capabilities useful for fine-tuning production processes in the face of changing supply and price situations.}, number={3}, journal={DECISION SUPPORT SYSTEMS}, author={Buehlmann, U and Ragsdale, CT and Gfeller, B}, year={2000}, month={Oct}, pages={207–227} }