МОДЕЛЮВАННЯ ІНТЕНСИВНОСТІ ПИЛОУТВОРЕННЯ ПІД ЧАС МЕХАНІЧНОГО ОБРОБЛЕННЯ ДЕРЕВИНИ

Галина Сомар; Олександр Сень

doi:10.36930/42265214

Authors

G.V. Somar Ukrainian National Forestry University https://orcid.org/0000-0003-4107-0112
O.Ya. Sen Ukrainian National Forestry University https://orcid.org/0009-0002-1870-9950

DOI:

https://doi.org/10.36930/42265214

Keywords:

mathematical modeling; wood machining; wood dust generation; cutting speed; cutting tool wear; environmental protection technologies; occupational safety; woodworking industry; regression analysis; process optimization

Abstract

The article presents the results of an experimental study and mathematical modeling of wood dust generation during mechanical wood machining. The relevance of the study is determined by the need to improve the environmental safety of woodworking production, advance environmental protection technologies, and enhance occupational safety by reducing dust generation directly in the cutting zone. The aim of the research was to determine the influence of cutting speed and cutting tool wear on wood dust generation intensity and to develop a mathematical model for predicting this process. The investigated factors were the cutting speed ranging from 40 to 80 m/s and the cutting-edge radius ranging from 10 to 50 μm, which characterizes the degree of tool wear. The experimental program was carried out using a second-order Box experimental design, while the obtained data were processed by regression analysis. The adequacy of the developed mathematical model was confirmed using Cochran’s, Student’s, and Fisher’s statistical criteria. The obtained results demonstrated that wood dust generation intensity increases with both cutting speed and cutting tool wear. The minimum dust generation intensity was 13.802 g/min at a cutting speed of 40 m/s and a cutting-edge radius of 10 μm, whereas the maximum value reached 49.782 g/min at 80 m/s and 50 μm, respectively. The developed quadratic regression model provides reliable prediction of dust generation intensity, determines rational machining conditions, and evaluates the influence of tool wear on the environmental performance of the machining process. The proposed model can be applied for optimizing cutting parameters, scheduling timely tool re-sharpening, improving dust extraction systems, reducing particulate emissions, and supporting the implementation of digital manufacturing technologies in modern woodworking enterprises. The obtained results contribute to improving production efficiency, environmental sustainability, and occupational safety in woodworking industries

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