NON-DESTRUCTIVE TESTING TECHNIQUES ALLOW THE ANALYSIS OF WOOD CHARACTERISTICS WITHOUT ALTERING ITS END-USE CAPABILITIES. WOOD MORPHOLOGY, WOOD DENSITY, MOISTURE CONTENT, AND WOOD DECAY ARE SOME OF THE FEATURES DETECTABLE BY MEANS OF DIFFERENT NON-DESTRUCTIVE METHODS. AMONG THEM, COMPUTED TOMOGRAPHY (CT) AND MAGNETIC RESONANCE IMAGING (MRI) STAND OUT BECAUSE OF THEIR ABILITY TO MEASURE INFORMATION IN A THREE-DIMENSIONAL FASHION. THIS ENABLES ONE TO SCAN VOLUMETRICALLY AN ENTIRE TREE LOG, GIVING MEASUREMENTS OF EACH LOCATION OF THE ANALYZED VOLUME. THE OUTPUT DATA CAN PROVIDE INFORMATION ABOUT INTERNAL STRUCTURES OR PHYSIOLOGICAL FEATURES, WHICH CAN THEN BE USED FOR OPTIMIZING INDUSTRIAL PROCESSING OR FOR RESEARCH PURPOSES. IN THIS CHAPTER, THE AUTHORS DESCRIBE CT AND MRI IN TERMS OF THEIR OPERATIONAL PRINCIPLES, SAMPLING CONDITIONS, DATA OUTPUTS, AND ADVANTAGES AND DISADVANTAGES.

THE SAWING OF HYMENAEA COURBARIL IS COMPLEX DUE TO ITS HIGH DENSITY AND ABRASIVENESS. THESE FACTORS ACCELERATE THE WEAR ON SAW BLADE TEETH, AND AS A CONSEQUENCE, INCREASE THE CUTTING VARIABILITY AND PROCESS COSTS. THE EFFECT OF CUTTING PARAMETERS ON STANDARD DEVIATION OF SAWN-WOOD THICKNESS WAS EVALUATED TO PROPOSE OPTIMAL SAWING CONDITIONS. A LOG CARRIAGE BANDSAW WITH TWO SAW BLADE GEOMETRIES, THREE LOG DIAMETER CLASSES, AND TWO FEED RATES WERE USED TO CARRY OUT THE SAWING TESTS. THE RESULTS SHOWED THAT THE SAWING VARIATION EXPRESSED BY THE TOTAL STANDARD DEVIATION OF BOARD THICKNESS WAS LOWER THAN 1 MM, WHEN LOG DIAMETER WAS LOWER THAN 0.79 M, AND THE LOG CARRIAGE FEED RATE WAS LOWER THAN OR EQUAL TO 10 M MIN-1 FOR BOTH SAW GEOMETRIES. THE SAWING THICKNESS WAS AFFECTED BY LOG DIAMETER AND LOG CARRIAGE FEED RATE, WHILE SAW GEOMETRY WAS NOT STATISTICALLY SIGNIFICANT. HOWEVER, THE GOAL OF THIS INITIATIVE WAS NOT AN ESTIMATION OF THE CHANGES ON SAWMILL PRODUCTIVITY. BEFORE THIS STUDY, ALL LOG CLASSES WERE PROCESSED WITH A LOG CARRIAGE FEED RATE OF NO HIGHER THAN 10 M MIN(-1). CONSEQUENTLY, GIVEN THE ESTIMATED TOTAL STANDARD DEVIATIONS, IT CAN BE SUGGESTED THAT THE LOGS OF CLASS 2 COULD BE SAWN AT A 50 % HIGHER RATE WITHOUT ALTERING THE CUTTING PRECISION, IMPROVING SAWMILL PRODUCTIVITY.

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

TWO GROUPS OF SUGAR MAPLE (ACER SACCHARUM MARSH) LOGS WERE SCANNED USING AN X-RAY SCANNER TO IDENTIFY AND LOCATE THEIR MAIN INTERNAL CHARACTERISTICS. IN THE DESIGN OF THIS EXPLORATORY STUDY, FIVE LOGS PRODUCED FROM A FRESHLY CUT TREE (GROUP 1) AND THREE LOGS (GROUP 2) SAMPLED FROM A SAWMILL YARD, WERE SCANNED TO IDENTIFY THE VARIOUS WOOD TYPES PRESENT: ROT; KNOTS; COLORED HEARTWOOD; AND SAPWOOD. BASED ON THESE COMPUTED TOMOGRAPHY (CT) IMAGES, FOUR OR FIVE DISKS (20 MM THICK) WERE CUT FROM EACH LOG. BLOCKS OF 10 X 10 X 10 MM WERE THEN CUT FROM EACH DISK REPRESENTING AREAS OF EACH TYPE OF WOOD. THE GREEN DENSITY, BASIC DENSITY, AND MOISTURE CONTENT OF EACH BLOCK WERE MEASURED TO ASSESS WITHIN-TREE VARIATIONS BETWEEN LOGS AND WITHIN WOOD TYPE. CT GREY LEVELS IN THE CT IMAGES WERE THEN MEASURED FOR INDIVIDUAL BLOCKS TO ASSESS THE FEASIBILITY OF IDENTIFYING WOOD TYPES.

THIS STUDY AIMS TO IDENTIFY THE DEFECTIVE CORE ON COMPUTED TOMOGRAPHY IMAGES (CT) OF PRUNED RADIATA PINE LOGS, USING AN ALGORITHM OF SUPERVISED CLASSIFICATION. THE CLASSIFICATION PROCESS WAS REQUIRED TO IDENTIFY AND SEPARATE THE DEFECTIVE CORE FROM THE FREE DEFECT PART AND KNOTS. TEN PRUNED RADIATA PINE LOGS WERE SCANNED INTO A MEDICAL X-RAY MULTI-SLICE PHILIPS SCANNER AND THE RESULTING CT IMAGES AT 5 MM. WERE OBTAINED. A TOTAL AMOUNT OF 270 CT IMAGES WERE CLASSIFIED UNDER WITH THE MAXIMUM LIKELIHOOD CLASSIFIER AND THE RESULTING THEMATIC MAPS WERE FILTERED WITH A MEDIAN FILTER OF 7 X 7. THEN, 90 THEMATIC MAPS WERE SELECTED AND USED TO ASSESS THE ACCURACY OF THE CLASSIFICATION PROCESS.

SUGAR MAPLE LOGS (ACER SACCHARUM MARSH.) WERE SCANNED USING X-RAY MEDICAL SCANNER IN ORDER TO DEVELOP A CLASSIFICATION PROCEDURE FOR THIS TYPE OF IMAGERY (CT IMAGES). THE CLASSIFICATION PROCEDURE WAS REQUIRED IN ORDER TO SEPARATE SAPWOOD FROM COLORED HEARTWOOD, KNOTS, ROT AND BARK. FIVE LOGS COMING FROM A FRESHLY CUT TREE (GROUP 1) AND THREE LOGS SAMPLED FROM A SAWMILL YARD (GROUP 2) WERE CHOSEN FOR THIS PURPOSE. TWO PARAMETRIC SUPERVISED CLASSIFICATION ALGORITHMS, A MINIMUM DISTANCE (MDC) AND MAXIMUM LIKELIHOOD (MLC) ONES, WERE QUALITATIVELY AND QUANTITATIVELY TESTED AND THE RESULTING THEMATIC MAPS WERE FILTERED BY A 5×5 MEDIAN FILTER.

THE FEASIBILITY OF IDENTIFYING KNOTTY CORE IN IMAGES OF X-RAY COMPUTED TOMOGRAPHY (CT) OF PRUNED RADIATA PINE LOGS (PINUS RADIATA D. DON), WAS EVALUATED USING A SUPERVISED CLASSIFICATION METHOD BASED ON ARTIFICIAL NEURAL NETWORKS (ANN). THE CLASSIFICATION PROCESS ALSO CONSIDERS THE IDENTIFICATION OF THE CLEAR WOOD AND KNOTS. THIRTY PRUNED RADIATA PINE LOGS WERE SCANNED IN A MULTI-SLICE SCANNER MEDICAL X-RAY, WHERE THE RESULTING CT IMAGES WERE OBTAINED EVERY 5 MM. A TOTAL OF 270 CT IMAGES WERE CLASSIFIED USING THE ANN, AND THE RESULTING THEMATIC MAPS WERE FILTERED WITH A MEDIAN FILTER OF 7 X 7. THE ACCURACY OF THE CLASSIFICATION PROCESS OF THE CT IMAGES WAS OBTAINED FROM A CONFUSION MATRIX AND KAPPA STATISTICS. THE RESULTS INDICATED THAT THE KNOTTY CORE CAN BE IDENTIFIED AND SEPARATED WITH AN ACCURACY OF 92.7%, WHILE FOR THE OVERALL ACCURACY WAS OBTAINED A VALUE OF 85.0%. AFTER FILTERING THEMATIC MAPS, THE PRECISION VALUES INCREASED TO 96.3% AND 92.3% FOR THE DEFECTIVE CORE AND OVERALL ACCURACY, RESPECTIVELY. KAPPA VALUES WERE 0.607 AND 0.764 FOR THEMATIC MAPS AND THEMATIC MAPS FILTERED, RESPECTIVELY. THESE VALUES INDICATE THAT THERE IS A STRONG DEGREE OF AGREEMENT BETWEEN REFERENCE DATA AND CLASSIFICATION PROCESS. THE RESULTS SUGGEST THAT IT IS FEASIBLE TO APPLY ARTIFICIAL NEURAL NETWORKS AS CLASSIFICATION PROCEDURE TO IDENTIFY THE KNOTTY CORE IN CT IMAGES OF PRUNED RADIATA PINE LOGS.

THE FEASIBILITY OF IDENTIFYING KNOTTY CORE IN IMAGES OF X-RAY COMPUTED TOMOGRAPHY (CT) OF PRUNED RADIATA PINE LOGS (PINUS RADIATA D. DON), WAS EVALUATED USING A SUPERVISED CLASSIFICATION METHOD BASED ON ARTIFICIAL NEURAL NETWORKS (ANN). THE CLASSIFICATION PROCESS ALSO CONSIDERS THE IDENTIFICATION OF THE CLEAR WOOD AND KNOTS. THIRTY PRUNED RADIATA PINE LOGS WERE SCANNED IN A MULTI-SLICE SCANNER MEDICAL X-RAY, WHERE THE RESULTING CT IMAGES WERE OBTAINED EVERY 5 MM. A TOTAL OF 270 CT IMAGES WERE CLASSIFIED USING THE ANN, AND THE RESULTING THEMATIC MAPS WERE FILTERED WITH A MEDIAN FILTER OF 7 X 7. THE ACCURACY OF THE CLASSIFICATION PROCESS OF THE CT IMAGES WAS OBTAINED FROM A CONFUSION MATRIX AND KAPPA STATISTICS. THE RESULTS INDICATED THAT THE KNOTTY CORE CAN BE IDENTIFIED AND SEPARATED WITH AN ACCURACY OF 92.7%, WHILE FOR THE OVERALL ACCURACY WAS OBTAINED A VALUE OF 85.0%. AFTER FILTERING THEMATIC MAPS, THE PRECISION VALUES INCREASED TO 96.3% AND 92.3% FOR THE DEFECTIVE CORE AND OVERALL ACCURACY, RESPECTIVELY. KAPPA VALUES WERE 0.607 AND 0.764 FOR THEMATIC MAPS AND THEMATIC MAPS FILTERED, RESPECTIVELY. THESE VALUES INDICATE THAT THERE IS A STRONG DEGREE OF AGREEMENT BETWEEN REFERENCE DATA AND CLASSIFICATION PROCESS. THE RESULTS SUGGEST THAT IT IS FEASIBLE TO APPLY ARTIFICIAL NEURAL NETWORKS AS CLASSIFICATION PROCEDURE TO IDENTIFY THE KNOTTY CORE IN CT IMAGES OF PRUNED RADIATA PINE LOGS.

INTRODUCTION: WHEN SAWING LOGS WITHOUT DIAMETER SORTING, THE CUTTING PROGRAM GENERATES DECISIONS AND ROUTES DEPENDING ON THE LOG?S APPEARANCE AND MACHINE LOAD. OBJECTIVE: TO OPTIMIZE THE PRODUCTION FLOW OF A CUSTOM-CUT PINUS RADIATA D. DON SAWMILL, THROUGH DETECTION AND ANALYSIS OF CRITICAL MACHINES, USING DISCRETE EVENT SIMULATION AND EXPERIMENTAL DESIGN. MATERIALS AND METHODS: TWO SIMULATION MODELS WERE DEVELOPED FOR SAWING LOGS WITH LENGTHS OF 2.5 AND 5.0 M, AND DIAMETERS BETWEEN 34 AND 44 CM TO PRODUCE SAWNWOOD WITH A THICKNESS OF 5/4? WITH VARIABLE WIDTH. THE NUMBER OF LOGS PROCESSED PER SHIFT WAS THE RESPONSE VARIABLE OF THE MODEL. HEAVILY-USED MACHINES AND TRANSPORTS WITH LONG QUEUES WERE CANDIDATES FOR CRITICAL MACHINES. THE IMPACT ON PRODUCTION WAS DETERMINED BY MEANS OF EXPERIMENTAL DESIGN, WHERE THE FACTORS ASSESSED WERE: (A) DELIVERY FROM BANDSAW CARRIAGE 1 TO BAND SAW 3, (B) INCREASED DEBARKER CAPACITY, (C) FAILURES ELIMINATED FROM BANDSAW 1 AND 2, AND (D) DIRECT DELIVERY FROM BANDSAW 2 TO EDGER 2. RESULTS AND DISCUSSION: MODIFICATIONS TO THE PRODUCTION FLOW WERE PROPOSED BECAUSE FACTORS B, C AND D SIGNIFICANTLY INCREASED (P = 0.1) THE PRODUCTION LEVEL (LOGS PER SHIFT); THE INCREASES OVER THE SAWMILL?S INITIAL CONDITION WERE 13 AND 18 % FOR LENGTHS OF 2.5 AND 5.0 M, RESPECTIVELY. CONCLUSION: SIMULATION AND EXPERIMENTAL DESIGN CAN BE APPLIED IN SMALL AND MEDIUM-SIZED SAWMILLS TO IMPROVE PRODUCTION WHEN PROCESSING LOGS WITHOUT DIAMETER SORTING.

THE OBJECTIVE OF THIS RESEARCH WAS TO DEVELOP MODELS FOR ESTIMATION OF THE BASIC DENSITY OF WOOD AT FULL TREE LEVEL AND AT DIFFERENT HEIGHTS OF PINUS RADIATA STANDING TREES, MEASURED FROM THE WOOD RESISTANCE USING THE RESISTOGRAPHY AT DBH LEVEL. A SAMPLE OF 29 TREES OF 15 YEARS OLD WAS USED FOR THE EXPERIMENT. THE TREES WERE SELECTED IN A CLONAL FIELD TEST ESTABLISHED IN THE BÍO-BÍO REGION, CHILE. FOR EACH TREE, 174 MEASUREMENTS WERE MADE WITH THE RESISTOGRAPH AND WOOD DISKS WERE OBTAINED TO DETERMINE THE WOOD RESISTANCE AND THE BASIC DENSITY AT SIX DIFFERENT RELATIVE HEIGHTS OF THE STEM. AS A RESULT, A SIGNIFICANT DECREASE OF THE BASIC DENSITY AND RESISTANCE OF THE WOOD WAS OBSERVED, FROM THE BASE TO THE APEX OF THE TREES, WITH VALUES OF 16,8% AND 38,5% OF DECREASE, RESPECTIVELY FOR EACH VARIABLE. THE AVERAGE FOR THE RESISTANCE VALUES DETERMINED AT DBH VARIED BETWEEN 11% AND 19% AMONG THE MEASURED TREES. A PREDICTION MODEL WAS GENERATED TO ESTIMATE THE BASIC DENSITY AT THE TREE LEVEL USING THE AVERAGE RESISTANCE OF THE WOOD MEASURED TO THE DBH. THE ADJUSTMENT PARAMETERS OF THE MODEL WAS A ROOT MEAN SQUARE ERROR VALUE OF 11,9 KG/M3, WHICH DID NOT DECREASE WHEN OTHER VARIABLES OF TREE (DBH OR TOTAL HEIGHT) WERE INCORPORATED. AS A MAIN CONCLUSION, A NEW METHOD TO ESTIMATE THE WOOD BASIC DENSITY AT DIFFERENT SECTIONS OF THE TREE WAS GENERATED USING THE ADJUSTED MODEL.