The sound absorption coefficient is a commonly used parameter to characterize the acoustic properties of materials. The fire performance of construction products has to be evaluated on the basis of their reaction to fire performance. The evaluation of the reaction to fire performance for the flammable construction materials which are in Class E reaction to fire is based on the ignitability test and the thermal test using the radiant heat source. For this study, nine types of STERED^® products, which were made from the recycled automotive technical textiles, were chosen in order to evaluate their ability for sound absorption and the reaction to fire. The fire performance was evaluated on the basis of the relative mass loss in the radiant heat source test; the ignitability in accordance with ISO 11925-2, the possible appearance of flame, duration of flame, and the glowing during the single flame source test. The sound absorption of nine products was rated on the basis of the sound absorption coefficient and the noise reduction coefficient. The measurement was performed using the transfer function method in accordance with ISO 10534-2. From the nine tested types of STERED^® products, the product Senizol AT XX2 TL 60 had the lowest mass loss at thermal loads up to 700 °C and it fulfilled the conditions for Class E reaction to fire. This product had the highest noise reduction coefficient of 0.81 and a high absorption coefficient for frequencies ranging between 500 Hz and 2000 Hz. The STERED^® product Senizol AT XX2 TL 60, as well as Senizol AT 22 TL 50, Senizol AT 40 TL 25, Senizol AT XX4 TL 50 and Senizol AT XX4 TL 10 with a sound absorption coefficient α of between 0.80 to 0.95 and corresponding NRCs from 0.66 to 0.81, these STERED^® products can be classified according to ISO 11654 into the sound absorption classes A and B.

The issue of the change in tool temperature as a result of the machining process is presented in this paper. The aim of the paper is to put forward a proposal and subsequently to verify the methodology of temperature monitoring in the process of computer numerical control (CNC) machining in real time. Subsequently, the data can be used in the process of adaptive machine-tool control. Experiments were used to determine whether the research method is appropriate. Oak, beech and spruce wood turning blanks with the thickness of 20 mm were machined using a 5-axis CNC machining centre. A temperature change observation resulting from the changes in parameters of the removed layer was used to test whether the research method is relevant. Parameters of the removed layer were affected by the changes in feed rate in the range from 1 ÷ 5 m·min⁻¹ in the removed layer (1–5 mm) or in wood species used in the experiment. As emerges from the proposed methodology, it is possible to monitor the changes in tool temperature responding to minimal changes in technological parameters on a relatively small size of a milled surface quite accurately. Sensitivity to given changes in technological parameters as well as the importance of the methodology was proven.

The potential of tree bark, a by-product of the woodworking industry, has been studied for more than seven decades. Bark, as a sustainable raw material, can replace wood or other resources in numerous applications in construction. In this study, the acoustic properties of bark-based panels were analyzed. The roles of the particle size (4–11 mm and 10–30 mm), particle orientation (parallel and perpendicular) and density (350–700 kg/m³) of samples with 30 mm and 60 mm thicknesses were studied at frequencies ranging from 50 to 6400 Hz. Bark-based boards with fine-grained particles have been shown to be better in terms of sound absorption coefficient values compared with coarse-grained particles. Bark composites mixed with popcorn bonded with UF did not return the expected results, and it is not possible to recommend this solution. The best density of bark boards to obtain the best sound absorption coefficients is about 350 kg/m³. These lightweight panels achieved better sound-absorbing properties (especially at lower frequencies) at higher thicknesses. The noise reduction coefficient of 0.5 obtained a sample with fine particles with a parallel orientation and a density of around 360 kg/m³.

For the sustainability of an important renewable resource, such as wood, it is important to significantly increase the efficiency of its processing. A large part of this raw material ends up in the wood processing industry, where it is used for the production of pulp, paper, construction and furniture timber, floors and others. Therefore, it is very important to gain the knowledge needed for optimal valuation of raw wood material, through quality detection and classification into quality classes. There are many defectoscopic methods working on different physical principles. The most familiar of these methods are semi-destructive and non-destructive, as they do not cause damage to the tree or wood during assessment. The aim of this article is to describe, assess and compare known semi-destructive and non-destructive methods for the assessment of wood properties. This article describes basic visual inspection, basic semi-destructive methods (Pilodyn, Resistograph) and advanced semi-destructive methods (SilviScan®, DiscBot®) as well. Non-destructive methods use mostly acoustic wave motion (acoustic, ultrasonic), high-frequency waves (using georadar, microwave) and methods based on visual evaluation (image, laser). At last, there are X–ray methods with the latest technology using three-dimensional (3D) computed tomography (CT). The implementation of modern non-destructive methods is of great importance for the application of principles of Industry 4.0, where these methods provide collecting of data on the material properties, in its entire production flow of log processing.

Heterogeneity in the tree trunks’ shapes and quality is not often reached fully using raw material potential in grading processes of tree and stand and the following sawmill processing. Therefore, optimization of given processes is a current topic of research and is part of the operational practice. In the contribution we submit a survey of solving the given problems in the European and Slovak conditions. A significant impulse for solving problem at a new level is a significant progress in the field of industrial computed tomography. New and fast CT scanners have been developed and they enable to increase valuation by 15% in coniferous trees and by 24% in broadleaf trees. In the contribution we analyze period of returns of CT scanner’s implementation into the sawmill process within Slovak context for small, medium-sized and big sawmills. Results show that period of returns for big sawmills is approximately for years, for medium-sized sawmills is eight years when processing coniferous softwood or three to eight years in case of broadleaved processing. In the final synthesis we present a concept of interlinking the 3D scanner and technologies of laser woodcutting with the outcomes allowing to optimize stand grading and maximize profit of the given raw wood in the sawmill processing.

The qualitative evaluation of harvested raw logs and sawlogs is mainly based on the quantitative and qualitative evaluation of the visible macroscopic features of the wood. Modern methods allow for the analysis of whole logs by means of computed tomography. These devices can analyze the internal qualitative features of wood that are not visible on the external structures of the logs. The aim of this work was to evaluate the detection accuracy of a CT-scanning device intended for scanning logs on the internal qualitative features of wood using model trunks. Two logs of beech and oak with a length of 4 m were selected for the analysis, based on availability. Qualitative features were identified through computed tomography scanning, visually identified on cut sections, and then manually measured in accordance with applicable legislation. Relatively good agreement was demonstrated for the detected features in terms of identifying their location (dimension in millimeters from the end of the log). For this parameter, the average differences were 0.90% on the beech log and only 1.21% on the oak log. Relatively high accuracy was shown via CT detection of qualitative features in the beech section (with average differences in dimensions of only 3.5%). In the case of the oak log, the dimensions of the quality features were significantly overestimated. These results indicate that CT scanning technology may have a problem with some hardwood species. It was primarily developed for coniferous tree species, and software algorithms are, therefore, not yet fully adapted to the precise detection of the dimensions of individual quality features. Despite the detected differences, it was confirmed that the CT technology of scanning harvested wood can have a fundamental impact on optimization procedures in the recovery and processing of wood. Renting a scanning line for a certain capacity of wood volume appears to be a deployment option for forestry operations and smaller wood processing operations. Thus, this technology can become an important factor in improving the economic evaluation of the final production of wood.