Guoyu Fu

Online tool wear monitoring is critical for ensuring machining quality and improving production efficiency. Existing online monitoring methods mainly rely on indirect signals for condition identification, and they often suffer from difficulties in placing sensing points close to the cutting zone as well as strong susceptibility to interference under complex cutting conditions. To address these issues, a micro-groove grating resistance sensor was fabricated based on micro and nanofabrication technology and integrated onto the tool flank face. In combination with tool life criteria, a tool wear monitoring method was established. This paper describes the fabrication process of the sensor, including micro-groove etching, conductive silver paste filling, high-temperature sintering, surface treatment, packaging and electrical lead-out. The morphology and electrical characteristics of the fabricated sensor were also characterized. Cutting experiments were conducted to investigate the evolution of the sensor's electrical behavior with tool wear during machining, thereby validating the feasibility of the proposed method for graded monitoring of tool wear. The experimental results show that, with the expansion of the flank wear land, the sensor electrical signal exhibits stepwise variation characteristics, which can be used to characterize different wear-state intervals during tool wear evolution and to provide warning of abnormal failure conditions such as tool chipping.

In this study, an innovative modeling approach has been proposed to demonstrate the removal mechanisms of Polymethyl Methacrylate (PMMA) reinforced with randomly distributed carbon nanotubes (CNTs) during nanosectioning. The viscoplastic behavior of the matrix polymer was described using the Mulliken–Boyce model and the distribution of the CNTs in the matrix was modeled using the random sequential adsorption (RSA) method. The effects of cutting thickness and CNT loading on the machinability of the nanocomposites are explored. Subsequent experiments were conducted to validate the modeling. It reveals that the addition of CNT increases the resistance to cutting, compared to the malleable matrix. Although the primary strain distribution for both plain PMMA and PMMA/CNT composites aligns closely, discernible disparities between the two materials emerge. A force augmentation is anticipated whenever a nanotube interacts with the cutting tool, which causes surface protrusions and sub-surface damage. The addition of CNT with a loading lower than 1.0 wt% does not change the mechanisms of chip formation, but the addition of 1.0 wt% CNTs increases cutting force by approximately 32%. This work provides a feasible approach and framework to numerically model the nanosectioning of CNT-reinforced thermoplastics.

This study investigates the influence of joining parameters on the dynamic tensile performance of hybrid bonded-bolted GFRP/Al joints, which are crucial in aerospace and automotive applications due to their high strength and lightweight properties. The motivation lies in addressing challenges related to geometric imperfections and varying assembly conditions that significantly impact joint reliability under dynamic loads. Experiments and numerical simulations were conducted to evaluate the effects of perpendicularity errors, fit clearance, and preload on the mechanical performance and failure modes of these joints. Dynamic tensile tests were performed using controlled loading conditions, and finite element modeling was employed to validate experimental findings and provide additional insights into stress distributions and failure mechanisms. The results demonstrated that perpendicularity errors significantly degrade joint performance. Specifically, joints with a 3° perpendicularity error parallel to the load direction exhibited a 64.40% reduction in energy absorption, whereas errors perpendicular to the load direction resulted in a 31.09% reduction. Excessive fit clearance changed the failure mode from tensile to shear, particularly at lower loading speeds. Increasing the preload effectively delayed adhesive layer delamination, reduced deformation, and enhanced overall joint strength. This research provides novel insights into the effects of geometric errors and assembly conditions on hybrid joint performance.