Evaluation of Yield Improvements in Machine vs. Visual Strength Grading for Softwood Species

Abstract

The current national standard for strength grading in Spain is based on a visual classification, which, for softwood species with small cross-sections (with a thickness equa tol or less than 70 mm), establishes two different visual grades (ME-1 and ME-2). These grades are assigned to the strength classes C24 and C18, respectively, for maritime and radiata pines, and C27 and C18 for Scots pine, according to the European standard EN-1912:2012. The production of engineered wood products, such as glulam or cross-laminated timber is increasing worldwide. The machine grading of wood using non-destructive testing provides the industry with a more reliable, fast, and consistent method for grading. With this background in mind, this study presents the yield comparison of machine grading vs. visual grading for those three pine species from Spain. The machine settings were obtained according to the standard EN 14081-2:2019, providing several possible strength grade combinations. Results allow new possibilities for the industry and improve the structural yield of the studied timber, thus increasing the material optimization.

Machine Grading of High-Density Hardwoods (Southern Blue Gum) from Tensile Testing

“…Table 5 shows the strength class combinations and the performance for every strength class, as well as the percentage of rejection per combination. In comparison with the strength classes obtained from machine grading in softwood species (Maritime pine, Radiata pine and Scots pine) from Spain [16], Southern blue gum showed better performance in terms of higher strength class. A lower percentage of rejection was also observed for all the strength class combinations (varying between 1% and 14%), but Southern blue gum showed a lower number of strength classes.…”

“…The settings to be implemented in the machine grading with the aim of assigning the strength classes to each IP value were derived from EN 14081-2 [21]. The methodology for the determination of the optimum grading, size matrix, elementary cost matrix and global cost matrix is described in Moltini et al [16] and summarised in Figure 3.…”

“…Nowadays, the EN 338 [15] does not provide strength classes for hardwood species tested for tension in Europe. Even though visual grading is the most widely used method in Spain and Portugal for declaring the physical and mechanical properties of wood species, it becomes less efficient in terms of structural performance, material optimisation and grading time than machine grading [16][17][18][19]. Nevertheless, there is no European standard providing machine graded species by country and their corresponding strength classes, as is the case for visual grading (EN 1912-[13]).…”

“…Despite some studies focusing on the machine grading of hardwood species tested in tension, Southern blue gum from Spain and Portugal was the first and only hardwood species whose machine grading from tensile tests was approved by CEN. This paper presents the results from the testing of the report approved by CEN/TC124/WG2/TG1 [28], and whose results database has already been shared with CEN/TC124/WG2/TG2, contributing to the revision of EN 338 [15].…”

Visual and machine strength gradings of Scots and red pine structural timber pieces from Türkiye

“…However, the IP obtained by machine grading is a more accurate predictor of wood quality than those obtained by visual grading. The machine grading process is much faster, possible human errors are minimized, and the potential to obtain a higher strength class brings machine grading to the fore (Nocetti et al 2010;Brunetti et al 2016;Nocetti et al 2016;Ravenshorst and Kuilen 2016;Ridley-Ellis et al 2016;Kovryga et al 2017;Krzosek et al 2020;Krzosek and Burawska 2022;Moltini et al 2022).…”