Optimization of CNC cutting parameters using design of experiment (DOE) and desirability function

Abstract

In this study, 2⁵ (five factors at two-level factorial design) design of experiment was applied to investigate a set of optimal machining parameters to achieve a minimum surface roughness value for Abies nordmanniana. Wood specimens were prepared using different values of spindle speed, feed rate, depth of cut, tool radius, and cutting directions. Average surface roughness $ \left( {R_{z} } \right) $ values were applied using a stylus. The objectives were to: (1) obtain the effective variables of wood surface roughness; (2) analyze which of these factors had an impact on variability in the CNC machining process; (3) evaluate the optimal cutting values within the range of different cutting levels of machining parameters. The results indicate that the design of experiment (DOE) based on the desirability function approach determined the optimal machining parameters successfully, leading to minimum R _a compared to the observed value. Minimum surface roughness values of tangential and radial cutting directions were 3.58 and 3.21 µm, respectively.

Keywords

Wood surface roughness / Optimization / CNC / Desirability function / Pareto analysis

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