Optimization and Yield of Low Quality and Small Sized Diameter Oak (Quercus robur L.) Logs in Production of Rough Elements

Autor: Josip Ištvanić, Juraj Jovanović, Murco Obucina, Selver Smajić
Rok vydání: 2021
Předmět:
Zdroj: New Technologies, Development and Application IV ISBN: 9783030752743
Popis: It is not usual practice but sometimes without previous agreement, to sawmills sometimes are delivered logs which do not fit regulations for standard saw logs. Often those logs are below standard quality or dimensions. Namely, sawmills compensate the lack of standard saw logs, in aspiration to fully use own capacities, by processing round wood with smaller dimensions called thin round wood. Research aim of this paper was to determine volume yield, lumber value yield and log value yield of Oak (Quercus roburL.) logs with smaller diameter and quality during their processing dimension stock and flooring components. The object of research were Oak logs divided into three groups with mid diameter ranging from 18 to 20, 21 to 23 and 24 to 26 cm. Primary sawing of logs was performed by using live sawing technique on long band saw. All obtained sawn boards were sawn up into dimension stock and flooring components by cross – rip sawing method. The best log volume yield in the form of dimension stock and flooring components showed logs with mid diameter ranging from 24 to 26 cm, followed by logs with diameter from 21 to 23 cm, and logs with diameter from 18 to 20 cm, with mutual insignificant difference. Results show that the best quality dimension stock and flooring components were sawn from logs with mid diameter ranging from 21 to 23 cm, followed by logs with diameter from 24 to 26 cm, and logs with diameter from 18 to 20 cm. The best log value yield results showed logs with mid diameter ranging from 24 to 26 cm, followed by logs with diameter from 21 to 23 cm, and logs with diameter from 18 to 20 cm. In this paper the usage of three very confined diameter groups was compared. It was determined that there is slight but insignificant mutual difference.
Databáze: OpenAIRE