Explore the vast range of titles available.

This paper presents an original method to inversely identify the Johnson–Cook model constants (J-C constants) of ultra-fine-grained titanium (UFG Ti) based on a chip formation model and an iterative gradient search method using Kalman filter algorithm. UFG Ti is increasingly finding usefulness in lightweight engineering applications and medical implant filed because of its sufficient mechanical strength, high manufacturability, and high biocompatibility. Johnson–Cook model is one of the constitutive models widely used in analytical modeling of machining force, temperature, and residual stress because it is effective, simple, and easy to use. Currently, the J-C constants of UFG Ti are unavailable and yet an effective identification methodology based upon machining data is not readily available. In this work, multiple cutting tests were conducted under different cutting conditions, in which machining forces were experimentally measured using a piezoelectric dynamometer. The machining forces were also predicted using the chip formation model with inputs of cutting conditions, workpiece material properties, and a set of given model constants. An iterative gradient search method was enforced to find the J-C constants when the difference between predicted forces and experimental forces reached an acceptable low value. To validate the identified J-C constants, machining forces were predicted using the identified J-C constants under different cutting conditions and then compared to the corresponding experimental forces. Close agreements were observed between predicted forces and experimental forces. Considering the simple orthogonal cutting tests, reliable and easily measurable machining forces, and efficient iterative gradient search method, the proposed method has less experimental complexity and high computational efficiency.

This paper presents an improved inverse identification method for Johnson-Cook model constants (J-C constants) using force and temperature data. Nowadays, J-C constants are identified by either experimental approaches with the complex and costly system, numerical approaches with high computational cost, or analytical approaches with available material properties. The previous model is developed based on a modified chip formation model and an exhaustive search method using temperature and force measurements. The current model is improved by replacing the exhaustive search method with an iterative gradient search method based on the Kalman filter algorithm. The modified chip formation model is used to predict machining forces. The iterative gradient search method is used to determine the J-C constants when the difference between predicted forces and experimental forces reached an acceptable low value. AISI 1045 steel and Al6082-T6 aluminum are chosen to test the proposed methodology. The determined J-C constants are validated by comparing to the documented values in the literature, which were obtained from Split-Hopkinson Pressure Bar tests and validated in published works. Good agreements are observed between identified J-C constants and documented values with an improved computational efficiency. The cutting temperatures are used as inputs in the modified chip formation model. Therefore, the workpiece material properties are not required to predict temperatures and forces, and thus are not required for determining J-C constants. Considering the modified chip formation model using temperatures as inputs, and the effective iterative gradient search method, this method has advantages of less mathematical complexity and high computational efficiency.

Ti40 burn-resistant titanium alloy is one kind of beta-phase titanium alloy. There exists complex cutting deformation, high cutting temperature, high cutting force and fluctuations, and serious tool wear and damage in the process of cutting Ti40 alloy. In this paper, the chip formation characteristics, chip formation mechanisms, and their relationships with dynamic fluctuation force of Ti40 beta titanium alloy are analyzed. It is shown that a large number of shear bands are formed inside the deformation of each beta phase grain, its chip thickness varies irregularly, and there exist many micro-serrated teeth and micro-cracks on the serrated chips. The chip formation mechanism of Ti40 alloy involves both adiabatic shear and crack initiation theories. With cutting speed increasing, the formation frequency of adiabatic shear bands is lifted, notable serrated teeth are formed, and the sub-grains are formed more obvious and fine among adiabatic shear bands. At peaks of milling force, notable fluctuation is shown, and the fluctuation times and amplitudes corresponded to the number of irregular cutting chip thickness variations or the irregular instant cutting volume and not a formation of every shear band. The fluctuation of milling force is caused by adiabatic shear and cutting direction change due to vibration. Meanwhile, the effect of chip formation on tool wear/damage is analyzed and compared with Ti6Al4V alloy.

Saw-tooth chip generated from hard turning is one of the most distinguishing features with conventional turning process. The presented work aims to contribute an extensive understanding the formation mechanism and main parameters of saw-tooth chips in oblique hard turning of 90CrSi hardened tool steel (60–62 HRC). The effects of dry, Al2O3 nanofluid MQL, Al2O3/MoS2 hybrid nanofluid MQL conditions on the serrated chip formation were experimentally investigated in terms of chip morphology, chip color, segment spacing, serrated segmentation frequency, and shear angle. The obtained experimental results indicated that, due to the better cooling and lubricating performance of nanofluid and hybrid nanofluid, the shear angles ϕ increase about 91.73% and 94.88% respectively when compared to dry cutting, which makes the formation of saw-tooth chip more favorable. Moreover, the analysis of microstructure image of the back side of chip proves the better lubrication from ball roller and tribo-film formation of Al2O3 and MoS2 nanoparticles. Based on the chip morphology analysis, the shear angle ϕ, the degree of chip segmentation on the top side in the chip’s transverse section K2, and the chip deformation coefficient in the transverse section K3 should be used as the additional criterions to evaluate the frictional improvement in cutting zone.

In this work, the machining of ultra-fine-grained pure titanium (UFG Ti) in an integrated manufacturing process combining severe plastic deformation (SPD) process and machining process is investigated through analytical modeling with experimental validation. UFG Ti is increasing finding usefulness in lightweight engineering applications and biomedical applications because of its sufficient mechanical strength, manufacturability, and biocompatibility. The UFG Ti is prepared by a SPD process, namely equal channel angular extrusion (ECAE) from commercial pure grade 4 titanium. However, the machining process in the integrated manufacturing process has not been fully understood in the context of machining forces and temperatures. The machining forces are predicted in this work using extended chip formation model. In this model, the average temperature at the primary shear zone is calculated based on the equilibrium between generated heat and plastic work. Orthogonal cutting tests were conducted under various cutting conditions with experimental force measurements using a piezoelectric dynamometer. Good agreements are observed between predicted forces and experimental forces. In addition, sensitivity analyses were performed to investigate the influence of input J-C constants and cutting condition parameters on the accuracy of the predicted machining forces. The predicted machining forces were compared to machining forces of Ti-6Al-4V alloy under various cutting conditions, which are widely used in engineering and biomedical applications. This work extends the applicability of analytical models in machining to a broader class of materials. It will promote the use of UFG Ti and the integrated manufacturing process in engineering and biomedical applications.

Based on the software ABAQUS/Explicit, a finite element (FE) model for orthogonal cutting was established. The FE model was validated by comparing the cutting forces and serrated degree of chips obtained by orthogonal cutting experiments under the cutting speeds 40, 80, 120, and 160 m/min. Based on the developed FE model, the influence of thermal conductivity on the degree of chip segmentation and the adiabatic shear localization were investigated. Furthermore, the plot contours on undeformed shape of cutting simulation was used to investigate the temperature distribution, and the high temperature zone was identified, which can help enhance the understanding of the serrated chip formation. Finally, cracks located in the adjacent segments of chips were observed. The results show that with the increase in thermal conductivity, the degree of adiabatic shear decreases. It can be concluded that the poor thermal conduction performance should be primarily responsible for the formation of serrated chips during machining Ti-6Al-4V alloy. Due to the high temperature at contact surface between cutting tool and workpiece, the increasing of cutting speed facilitates the formation of serrated chips during machining.

In this paper, an original approach was presented to identify the Johnson-Cook material constants (J-C constants). The Johnson-Cook model is one of the simplest models to describe the material behavior in machining. The five J-C constants are related to strain hardening effect, stain rate hardening effect, and thermal softening effect. The approach was developed based on a chip formation model in orthogonal cutting and Johnson-Cook model. This paper used process variables including the temperature at the primary shear zone, the temperature of the chip, cutting conditions, and the estimations of the material constants as inputs. The machining forces were calculated with the chip formation model using all estimated material constants that were being changed within intervals of 50% of the references. The five J-C constants were determined by searching minimum differences between the calculated forces and measured forces under each cutting condition. The workpiece material properties such as thermal conductivity, specific heat, and melting temperature were not required because of the measurements of the temperatures. The proposed approach has advantages of low experimental cost, low time cost, less experimental complexity, and less mathematical complexity. The determined J-C constants of AISI 1045 steel and 42CrMo4 alloy were compared to their J-C constants from Split-Hopkinson Pressure Bar (SHPB) tests respectively. Close agreements were found for both materials.

In this paper, a finite element (FE) cutting model for particle-reinforced metal matrix composites (PRMMCs) considering material damage was developed to predict SiC particle failure, cutting forces, and machined surface topography in SiC p /Al composite machining, and to analyze the dynamic mechanisms of chip formation and particle failure evolution. The validity of the simulation model was verified by comparing the simulation results with the cutting forces and surface topography obtained from the milling machining experiments. It was found that complex stress-strain fields exist in SiC p /Al composites with mesoscopic non-homogeneous structures, and alternating reticulation of tensile and compressive stress between particles was observed; particle failure due to tool-workpiece interaction exists in both direct and indirect ways; particle failure and local chip deformation during machining affect surface topography and chip shaping, resulting in serrated chips, pitting on the machined surface, and residual particle fragments.

Elevated temperature in the machining process is detrimental to the cutting tool due to a thermal softening effect. The increased material diffusion deteriorates the quality of the machined part. Experimental techniques and finite element method-based numerical models in temperature investigation are limited by the restricted accessibility and high computational cost respectively. Physic-based analytical models are developed to overcome those issues. This study investigated three analytical models, namely a modified chip formation model, Komanduri-Hou two heat sources model, and Ning-Liang material flow stress model, in the prediction of machining temperatures in orthogonal cutting. The evaluation and comparison between three models aim to promote the use of the analytical models in real applications, in which real-time prediction is highly appreciated. Temperatures in machining AISI 1045 steel were predicted under various cutting conditions. Acceptable agreements were observed between predictions and documented values in the literature. In the modified chip formation model, machining temperatures and forces were solved iteratively with complex mathematical equations, which reduced computational efficiency, and thus prevented a real-time temperature prediction. The heat partition factors were empirically determined, which resulted in unoptimized prediction accuracy. In Komanduri-Hou model, the input lengths of two shear zones and shear angle cannot be easily obtained from experiments due to the restricted accessibility. With the benefits of high prediction accuracy, high computational efficiency, and low experimental complexity of model inputs, Ning-Liang model was favored in the real-time prediction of machining temperatures.

Wood fiber/polyethylene composite (WFPEC) is composed of a natural wood fiber and a recyclable polyethylene plastic, which is normally used as an environmental protection composite material. However, better knowledge of chip formation and surface damage mechanism of WFPEC is essential to improve its machinability for extending exterior and interior applications. In this article, machinability of WFPEC was investigated by analyzing the disparity between cutting efficiency and surface quality through a group of orthogonal cutting experiments with change of cutting depth. The chip formation process was recorded by a high-speed camera system with 5000 frames per second. Surface topography was observed by a scanning electron microscope. The results showed that the chip morphology changed from continuous cutting governed by a continuous shearing process under the shallow cutting depth, to a discontinuous cutting governed by plastic fracture under the deep cutting depth ahead of the tool tip. Flattened matrix was the main form of surface topography caused by shallow cutting depth, while matrix-fiber tearing was caused by deep cutting depth. Pullout/fracture and debonding of fibers were related to the fiber orientation angle and the diameter of fiber bundles, but not to the cutting depth. Taken together, the toughness of the workpiece material in the cutting region decreased with the increase in cutting depth. To avoid matrix-fiber tearing, shallow cutting depth should be used during finishing to maintain surface quality. In contrast, pre-cutting can be performed with a deep cutting depth in order to improve the cutting efficiency.