Investigation into the effects of machining parameters on the edge quality of particleboards - Modelling and Optimization

Abstract

Abstract It is challenging to model and optimize the variables affecting particleboard's (PB) machining edges. The lack of thorough investigation of these models presents further difficulties. However, they can directly improve the cutting-edge profile's quality and reduce production costs. Statistical and mathematical modelling tools, such as the Response Surface Methodology (RSM) are valuable tools for understanding how both qualitative and quantitative variables affect the quality performance of a process or product, which means understanding how these variables respond to the factors involved in the model. The Box-Behnken experimental design model was initially used to plan experiments in this study. By employing this technique, fewer tests are necessary to examine the predefined factors. The model's suitability and the accuracy of the results were verified using a variance analysis (ANOVA). That allowed a comparison of the variation caused by the factors with the interference caused by random errors in the generated responses. Subsequently, a mathematical-statistical model was then generated from experimental data using polynomial functions to use RSM as an optimization method. From this examination, the optimal values for each response variable were obtained. In conclusion, this study demonstrates that both experimental and prediction results show a good correlation and highlight that the use of RSM to optimize the delamination criteria (Tw), the specific cutting energy (Es), and feed per tooth (fz) as response variables when influenced by the factors feed speed (Vf) and frequency (N), is appropriate for the edge quality analysis of the specific type of PB considered in this study. Extended author information available on the last page of the article Published online: xx XXXXXXX 2024