Cutting mechanism characterisation and performance prediction in end-grain milling of laminated bamboo lumber

This is the authors' abstract. We don't add key points for this paper.

Laminated bamboo lumber (LBL) is strong and sustainable, yet its anisotropic nature can trigger cutting-force fluctuations and fibre damage during end-grain milling, reducing efficiency and surface quality. This study investigated the effects and mechanisms of key milling parameters and developed predictive models for the active force (Fa) and mean roughness parameter (Ra). A Box-Behnken design within the response surface methodology (RSM) framework was employed to model Fa and Ra. ANOVA showed that feed per revolution (Frev) and milling depth (ae) were the dominant factors. Increasing Frev raised undeformed chip thickness, intensifying fibre fracture and tearing, while increasing ae enlarged the tool-fibre engagement area, increasing mechanical loading and friction. Higher cutting speed (vc) reduced Fa by lowering chip thickness per tooth and shortening contact time; however, at constant Frev, it increased the feed rate and could aggravate fibre compression/tearing, increasing Ra. The significant Frev×ae interaction further amplified both responses, indicating greater instability under high chip loads. RSM achieved the best accuracy for Fa (R2=0.98) and Ra (R2=0.91); GPR was competitive for Fa but weaker for Ra. These results support parameter selection and model choice for efficient, high-quality LBL machining.