A top performer

THG in Scandinavia

A top performer

AUTOMATED GRADING IS PUT TO THE TEST IN SWEDEN

With such positive results, we are confident that we have a very competitive automated grading system that meets all the needs of our market.

In a recent technology study conducted by two independent Swedish industry groups, our Transverse High Grader (THG) was put to the test alongside other European automated grading systems. Among the 5 participating grading machines, THG performed exceptionally well in all aspects of grading for the Nordic market. These results confirmed that THG is a top performer among automated grading systems available on the global market today.

In July 2017, the Research Institute of Sweden (RISE), in collaboration with the Swedish Wood Technology Forum, conducted a study of automatic grading systems for lumber. The study involved five suppliers of technology for this purpose. Participating companies included RemaSawco, FinScan, USNR / Söderhamn Eriksson, Microtec and Lisker. The results of the project were presented in September at three locations in Sweden. Results were presented to approximately 100 wood processors at these venues.

Setting goals

A previous major study was conducted in 1996, and one significant goal for this recent study was to highlight the advances that technology has affected on the processes in this industry. Another goal was determining the capability of the grading systems to optimize the value of the lumber.

The tests were designed for comparing the European standard for grading (EN-1611) to the Nordic Timber grading rules, to see how the outcome would be affected by using the different sets of rules. Eric Blomstrand, account manager with USNR / Söderhamn Eriksson, explained, “We do not have the same situation in Europe as in North America. In Europe it is up to the seller and the buyer to agree on the grade. The Nordic Timber grade rule book can be seen as a recommendation. Often though, the rules are customized to fit customer demands. If you sell lumber according to the EN-1611 grade rules, then the grade has to correspond to that standard.”

Spruce and pine lumber were tested, both in side board (25 x 125 mm / 1" x 5") and center board or plank (47 x 148 mm / 1.8" x 6") dimensions. Appearance was the primary factor in determining value; lumber strength was not a consideration.

Put to the test

USNR / Söderhamn Eriksson contributed its Transverse High Grader (THG) for the study.

The tests that involved the THG were carried out at the company's facility in Söderhamn, Sweden, already set up to test customers’ lumber for defect recognition and classification.

Our system received high marks in comparison to what we observed with other systems in the survey.

The tests for this study evaluated each system for its performance in recognizing and classifying defects in 300 pieces of lumber. Then experienced manual graders took their turn to assess the pieces based on their established standards.

Though specific results were not publicized outside the participant group, the study disclosed overall error rates for some systems exceeding 20%. With an error rate of less than 5%, the THG showed that it is a top tier performer.

Meeting objectives

Eric Blomstrand commented, "We wanted to participate in the project for two reasons. First we were interested to learn how our THG compares with other systems in this field, and we also wanted the opportunity for our team in Sweden to learn more about board scanning and automated grading. While our teams based in North America have extensive experience in this area, this is technology to which our Swedish team has had more limited exposure.”

Excels in performance

Eric continues, "The test results for the THG have been enlightening, as our system received high marks in comparison to what we observed with other systems in the survey. We feel reassured that our THG excels in its performance for the Scandinavian market.”

"With such positive results, we are confident that we have a very competitive automated grading system that meets all the needs of our market," he concluded.

To learn more about our THG visit: https://www.usnr.com/ en/product/THGLM

Eric Blomstrand presented the results of the THG's performance to wood processors at three venues in Sweden.

SPLITS / SHAKE

Four faces of a Nordic pine board with shake highlighted in pink.

KNOTS

Four faces of a Nordic pine board with knots highlighted in green.

THE SCIENCE INSIDE THG

With more than 110 vision scanning systems operating around the globe, and over 20 years of experience in grade scanning under our belt, USNR is an industry leader in this field.

DataFusion method

DataFusion™ compares scan data from a variety of technologies to achieve the most accurate defect detection and classification. To collect this data, THG utilizes the advanced grade scanning sensor – BioLuma 2900LVG+, that integrates:

• GrainMap™ grain angle measurement

• XHD color vision

• HD laser profiles

• LED illumination

Finding the pith

Pith is key to locating and sizing knots hidden within a piece. THG models the pith to assist it in determining knot displacement, utilizing the following characteristics:

• wane

• surface pith

• surface grain line patterns

• grain angles

• end grain

• knots

An end grain scanner takes a visual snapshot of the end of a piece to model its grain pattern. This grain pattern is then fit into a virtual log to determine the starting pith position in the 3-dimensional board relative to its location within the modeled log. Once the board model is assembled, knot projections are developed to find a common point of intersection.

The resulting information from these clues is integrated to determine the final pith model. Using multiple clues allows THG to track the pith even though it moves through the piece.

Armed with accurate defect data, THG’s decision capabilities let you determine proprietary grades for:

• cut-n-2, cut-n-3, cut-n-4

• sophisticated wane rules

• knot sizes / classification

• shake separation

First the image from the end scanner is processed to find the grain pattern on the end of the board. This pattern is fit to concentric circles of a virtual log, to determine the starting pith position.

Next, once the 3 dimensional board model is assembled, and using the board's surface clues, knot projections are made to find a common point of intersection.

Finally, using multiple clues allows THG to track the pith even though it moves through the piece.