H . G . TOLER & SON , continued ...
H . G . TOLER & SON , continued ...
“ BioVision allows us to maximize both volume and value . If it ’ s a higher value piece we can cut for value , but if it ’ s lower value we can cut for volume .”
scan frame or added to an existing transverse scan frame via a bolt-on housing that accommodates the vision sensors . With BioVision , USNR has combined the proven Linear High Grader ( LHG ) classification system developed for planer mills with the high resolution BioLuma 2900 color sensors for transverse scanning of lumber .
Scanned images are fed to the defect classification engine where characteristics are extracted based on visual properties and defect shape data . These characteristics are typeclassified according to proprietary classification rules , then overlaid on the geometric profile model . Optimization software selects the most valuable solution available according to the product parameters , grade rules and prices entered . BioVision benefits include the following .
John Grigsby was pleased with the way the startup progressed . “ It started up well right out of the box . It ’ s probably one of the smoothest electronic start-ups I ’ ve ever been through .” John is also more than pleased with the results he is seeing from the system . “ We ’ re noticing an uplift in the amount of C and D ( grade ) lumber . It really excels when we cut wides , we can cut 70-80 % C and D . That ’ s a real good judge because we cut for grade only ( cut to order ), so the BioVision has to sort out what is grade and what isn ’ t , and when to make wides .” He went on to say , “ In terms of knot size classification it ’ s doing real well . It allows us to cut for specific lengths and specific grades , of specific widths . It can pinpoint exactly what we want to produce . If all we need to make is 1x12 , C & better 16 ’ long , and if we set that as priority it won ’ t cut anything but .”
John explained further , “ Each grade class has a different wane class , so as knot defects drop the piece down in appearance grade it can stand more wane . That is how we gain in volume , by edging for the grade that is in the flitch . We used to saw for a medium grade , and it ended up being over sawn for low grade and under sawn for higher grades . Now we ’ re more on-grade . BioVision allows us to maximize both volume and value . If it ’ s a higher value piece we can cut for value , but if it ’ s lower value we can cut for volume . By producing lumber at the mill that is on-grade , the final grading process is streamlined , requiring less trim . The graders can often simply verify grade instead of having to trim to get it .”
We are particularly appreciative of those processors , like H . G . Toler & Son , who through their confidence and trust helped USNR to take the next evolutionary step forward .
►►Maximize volume for lower grade flitches
►►Maximize value by cutting around defects to produce clearer , higher grade boards
►►Smart reman decisions based on defects and geometric shape
►►Fiber classification based on grade ( combined vision and geometric data ) vs geometry only
►►Confidence algorithms compare solutions with and without grade input
BioVision ’ s user interface features both a camera image of the board as well as a computer-generated image that displays the defects and the optimizer ’ s solution . This feature aids in tuning and troubleshooting , as well as off-line rerun simulation .
14 Millwide INSIDER | ISSUE 3 - 2013