Work

Prediction Models for the Milling of Heat-Treated Beech Wood Based on the Consumption of Energy

Year: 2024

Type: article

Abstract: The article is focused mainly on verifying the suitability of data from experimental milling heat-treated beech wood and on investigation of the effect of technical and technological parameters of milling on the energy consumption of this process. The independent parameters of machining process are cutting speed, feed speed, rake angle, and hydrothermal modification of experimental wood material. Based on analysis of variance it can be argued that the greatest statistically significant effect on energy consumption have cutting speed and rake angle of the tool while the feed speed had the least influence. The measured data of cutting power during milling were used to build a regression model and validate it, while the most suitable type of model with correlation of 87 % is Classification and Regression Tree followed by model created by Random Forests method.

Source: Applied Sciences

DOI: 10.3390/app14209539

Authors: Peter Koleda, Peter Koleda, Tomáš Čuchor, Pavol Koleda, Pavol Koleda, Ľubomír Rajko

Institution: Technická univerzita vo Zvolene

Language: English

Topic: Advanced machining processes and optimization

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,728

Funder: Agentúra na Podporu Výskumu a Vývoja