A PREDICTIVE MODEL FOR THE CUTTING FORCE IN WOOD MACHINING DEVELOPED USING MECHANICAL PROPERTIES

• Main Authors: Andrew Naylor, Phil Hackney, Noel Perera, Emil Clahr
• Format: Article
• Language: English
• Published: North Carolina State University 2012-05-01
• Series: BioResources
• Subjects: Wood Machining; Mechanical Testing; Regression Modeling
• Online Access: http://ojs.cnr.ncsu.edu/index.php/BioRes/article/view/BioRes_07_3_2883_Naylor_HPC_Predictive_Model_Wood_Machining/1562

In this study a number of work-piece variations were evaluated whilst limiting the cutting conditions. Eight wood species controlled at four moisture levels were machined along and across the wood grain. The tool used during cutting was designed to resemble a rip saw tooth with zero rake angle and narrow edge width. Each work-piece variation machined in the cutting tests was subjected to mechanical tests that evaluated bending properties across the grain and shear properties along the grain. The regression model establishes a relationship between the bending properties for cutting forces across the grain, as well as shear properties for cutting forces along the grain. F and R² values show that the elastic properties of the wood in bending and shear have less influence on the cutting forces when compared to the strength and toughness. Additionally, density is seen to have less influence on the cutting force along the grain. This is explained by the tool passing through an unquantifiable proportion of early and latewood fibers from the annual growth rings. Cutting across the grain, the tool is forced to machine through approximately the same proportion of earlywood and latewood fibres.