Predictive Analytical Modeling of Thermo-Mechanical Effects in Orthogonal Machining

Factor relationships in a machining system do not work in pairs. Varying the cutting parameters, materials machined, or volumes produced will influence many machining characteristics. For this reason, we are attempting to better understand the effect of the Johnson-Cook (J-C) law of behavior on cutting temperature prediction. Thus, the objective of the present study is to investigate, experimentally and theoretically, the tool/material interactions and their effects on dust emission during orthogonal cutting. The proposed approach is built on three steps. First, we established an experimental design to analyze, experimentally, the cutting conditions effects on the cutting temperature under dry condition. The empirical model which is based on the response surface methodology was used to generate a large amount of data depending on the machining conditions. Through this step, we were able to analyze the sensitivity of the cutting temperature to different cutting parameters. It was found that cutting speed, tool tip radius, rake angle, and the interaction between the cutting speed and the rake angle explain more than 84.66% of the cutting temperature variation. The cutting temperature will be considered as a reference to validate the analytical model. Hence, a temperature prediction model is important as a second step. The modeling of orthogonal machining using the J-C plasticity model showed a good correlation between the predicted cutting temperature and that obtained by the proposed empirical model. The calculated deviations for the different cutting conditions tested are relatively acceptable (with a less than 10% error). Finally, the established analytical model was then applied to the machining processes in order to optimize the cutting parameters and, at the same time, minimize the generated dust. The evaluation of the dust generation revealed that the dust emission is closely related to the variation of the cutting temperature. We also noticed that the dust generation can indicate different phenomena of fine and ultrafine particles generation during the cutting process, related to the heat source or temperature during orthogonal machining. Finally, the effective strategy to limit dust emissions at the source is to avoid the critical temperature zone. For this purpose, the two-sided values can be seen as combinations to limit dust emissions at the source.

A numerical model for tool–chip friction in intermittent orthogonal machining

This article presents a novel model to study the influence of surface textured cutting tools in near-micromachining conditions. The model utilizes the Challen and Oxley’s asperity deformation model (Van Luttervelt et al., CIRP Ann Manuf Technol, 1998, vol. 47, pp. 587–626; Arrazola et al., CIRP Ann Manuf Technol, 2013, vol. 62, pp. 695–718) paired with an approach to a priori estimate of the interfacial film formation at the tool–chip interface. The procedure considers the chemical effect of the environment, along with the mechanical aspects of the surface texture of the cutting tool’s rake surface. Model performance, in terms of predicting machining forces and coefficient of friction, was validated with existing experimental data (Anand et al., Proceedings of the international conference on advancements and futuristic trends in mechanical and materials engineering, 5–7 October 2012, pp. 661–666). The outcome trend of the proposed model approximately matches with the experimental results. Further, the model tries to explain the impact of cutting tool’s surface roughness on overall tool–chip friction while performing intermittent cutting in the near-micromachining regime.

Cutting to the Point: Directly Machined Metal Molds for Directional Gecko-Inspired Adhesives

Fabrication techniques for gecko-inspired adhesives generally target mold durability, adhesive performance, and process efficiency and simplicity. With these goals in mind, we present a micromachining process for creating reusable aluminum molds used to fabricate directional dry adhesives. The molds require deep, narrow and overhanging grooves to create sharp and angled adhesive features. This geometry precludes most traditional machining and lithographic material removal processes. The presented process is a hybrid of indenting and orthogonal machining, using a diamond-coated microtome blade as the tool. An FEA analysis reveals the local extent of work hardening as each groove is created, and helps to define a trajectory that reduces the effects of tool deflection and chip build up. The results of a series of experiments agree with predictions from the analysis and reveal a range of blade approach angles and a lower bound on groove spacing to achieve the desired geometry. This range is narrower than for molds machined from wax in previous work. Nonetheless, adhesive samples cast from the new metal molds achieve comparable performance to those previously cast from wax.

Tool wear and spring back analysis in orthogonal machining unidirectional CFRP with respect to tool geometry and fibre orientation

Machining abrasive carbon fibre reinforced polymers (CFRP) is characterised by extensive mechanical wear. In consequence, the cutting edge micro-geometry and thus the tool/material contact situation are continuously changing, which affects process forces and machining quality. As a conclusion, a fundamental understanding of the tool wear behaviour and its influencing factors is crucial in order to improve performance and lifetime of cutting tools. This paper focuses on a fundamental tool wear analysis of uncoated tungsten carbide cutting inserts with different combinations of fibre cutting angles and tool geometries. For this purpose, orthogonal machining experiments with unidirectional CFRP material are conducted, where the wear progression of the micro-geometry is investigated by means of five wear parameters lα, lγ, γ*, α*, and bc. For detecting the actual contact zone of the cutting edge and to measure the elastic spring back of the material, the flank face is marked via short pulsed laser processing. Furthermore, the process forces and the wear rate are measured. It is shown that the material loss due to wear clearly varies along the tool’s contact region and is highly dependent on the clearance angle and the fibre cutting angle Φ, while the influence of the tested rake angles is mostly negligible. Especially in machining Φ=30° and Φ=60°, a strong elastic spring back is identified, which is more intense for smaller clearance angles. For all tested configurations, the material’s elastic spring back increases in intensity as wear progresses which, in combination with the decreasing clearance angle, is the main reason for high thrust forces.

FE analysis of the effects of process representations on the prediction of residual stresses and chip morphology in the down-milling of Ti6Al4V

Part I of these two-part papers will investigate the effect of three FEM representations of the milling process on the prediction of chip morphology and residual stresses (RS), when down-milling small uncut chips with thickness in the micrometer range and finite cutting edge radius. They are: i) orthogonal cutting with the mean uncut chip thickness t, obtained by averaging the uncut chip thickness over the cutting length, ii) orthogonal cutting with variable t, which characterizes the down-milling process and which is imposed on a flat surface of the final workpiece, and iii) modelling the true kinematics of the down milling process. The appropriate constitutive model is identified through 2D FEM investigation of the effects of selected constitutive equations and failure models on the prediction of RS and chip morphology in the dry orthogonal machining of Ti6Al4V and comparison to experimental measurements. The chip morphology and RS prediction capability of these representations is assessed using the available set of experimental data. Models featuring variable chip thickness have revealed the transition from continuous chip formation to the rubbing mode and have improved the predictions of residual stresses. The use of sequential cuts is necessary to converge toward experimental data.

Finite element modelling for orthogonal machining of AA2024-T351 alloy with an advanced fracture criterion

Numerical modelling of the plastic deformation and fracture during the high speed machining is highly challengeable. Consequently, there is a need for an advanced constitutive model and fracture criterion to make the numerical models more reliable. The aim of the present study is to extend the recent advanced static Lou-Yoon-Huh (LYH) ductile fracture creation to high strain rate and temperature applications such as machining. In the present work, the LYH static fracture creation was extended to machining conditions by introducing strain rate and temperature dependency terms. This extended LYH fracture criterion was calibrated over the wide range of stress triaxialities and different temperatures. Modified Khan- Huang-Liang (KHL) constitutive model along with the variable friction model was employed to predict the flow behaviour of work material during the machining simulation. Damage evolution method was coupled to identify the element deletion point during the machining simulation. Orthogonal machining experiments were carried out for an aerospace grade AA2024-T351 at cutting speeds varying between 100 and 400m/min with the feed rates varying between 0.1 and 0.3mm/rev. To assess the prediction capabilities of extended LYH fracture criterion numerical simulations were also carried out using Johnson-Cook (JC) fracture criterion under all experimental conditions. Specific cutting energy, chip morphology and compression ratio predictions were compared with the experimental data. Numerical predictions with coupled extended LYH criterion showed good agreement with experimental results compared to coupled JC fracture criterion.

Waspaloy orthogonal hard machining simulation, a comparison among different rheological models

Nickel based superalloys, such as Waspaloy, are extensively used to manufacture components that operate under high temperature cyclic loads, because of their superior chemical and thermo-mechanical properties. In particular, these artifacts are mainly produced by shaping and/or finishing machining operations. Despite of their huge properties, these alloys show an extremely poor workability, that makes them part of the group of the so called difficult-to-cut materials. Therefore, the proper selection of the machining conditions is always challenging for the designers. In this context, predictive models represent an extremely useful tool to numerically simulate the machining process, guaranteeing a good knowledge of the material behavior under machining conditions, and avoiding expansive and time consuming experimental campaigns. Besides, the proper selection of the material rheological model is of fundamental importance in order to obtain precise and affordable results from the numerical model. In this work a Johnson-Cook based viscoplastic flow behavior model was proposed. The model was obtained from Artificial Neural Network (ANN) based interpolation techniques and validated using orthogonal machining experimental tests. Moreover, the proposed model was compared with other rheological models available from literature to benchmark their affordability and assessing their performances.