Analysis of Micro-Milling
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Analysis Of Micro Milling Of Hardened H13 Steel
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Analysis of Micro-Milling
- 1. Analysis of micro-milling of hardened H13 steel Hongtao Ding, Ph.D. Mechanical Engineering, Purdue University https://engineering.purdue.edu/CLM/
- 3. Micro-milling Experiments of Hardened H13 Tool Steel Table 3.1 Test conditions of micro-milling of hardened H13 steel Fig. 3.1 Micro-milling experimental configurations 14
- 4. Real-Time Monitoring of Cutting Process with an AE Sensor 15 Fig. 3.2 Acoustic emission sensor monitoring of micro-milling To avoid tool chattering, a slow feed rate of 35 mm/min was used when entering and exiting the workpiece. The AE sensor was primarily used as a monitoring tool for the micro milling experiments. The AE RMS signals remained about constant within one cutting pass before the tool was severely worn.
- 5. Dimension Control in Micro-milling Fig. 3.3 Work geometry produced after about 3 minutes side cutting (15 passes) Table 3.2 Measurement and error of machined workpiece geometry Fig. 3.4 Typical 3D surface profile produced by side cutting 16
- 6. Surface Defects in Micro-milling 17 Fig. 3.5 Surface integrity in micro side cutting As the tool had severely worn, lots of prows could be observed on the machined surface
- 7. Tool Wear Progression in Micro-milling 18 Fig. 3.6 Tool wear progress in side cutting The tool nose wear and flank wear developed at a steady rate prior to tool catastrophic failure.
- 9. ALE applied on the top section A with a fine mesh
- 10. Mesh-to-mesh solution mapping technique is developed between two continuous explicit steps for remeshing the distorted workpiece mesh and solution mappingStrain gradient constitutive model (Liu and Melkote, 2007; Lai, et al., 2008)
- 11. Thermal Analysis of Micro-milling Fig. 3.8Heat transfer analysis of slotting Fig. 3.9Workpiece temperature histories 20
- 12. Chip Formation in Micro-milling 21 Fig. 3.10Chip formation and flow stress simulations during one side cutting cycle
- 13. Size Effect and BUE Formation in Micro-milling 22 Fig. 3.11 Workpiece material velocity field during side cutting with different tool edge radii
- 14. Summary on Micro-milling of Hardened H13 Steel A precise dimension control of the machined part was achieved with an accumulated error of about 1%. A gradual tool wear progression in both the tool nose and flank face was observed in the wear tests for multiple tools. As the tool wore and ploughing became dominant, larger and more prows were observed on the machined surface, and large BUE was observed on the tool nose. Novel 2D FE models with a strain gradient plasticity model were developed to simulate the continuous chip formation using ALE technique for a complete micro-milling cycle with varying chip thickness. The heat transfer analysis of multi milling cycles showed that the steady-state workpiece temperature reaches about 300 °C as the flute approaches and drops to about 90 °C as the flute leaves in micro slotting at a cutting speed of 85 m/min, while the workpiece temperature increases to 75 °C in the cutting phase but drops to the ambient temperature in the cooling phase in micro side cutting at a cutting speed of 19 m/min. The specific cutting force was predicted to increase from about 15 to about 100 GPa as λ decreased from 2 to 0.2. Ploughing and no chip formation were simulated with the FE model as the ratio λ decreased to about 0.2. The model simulations showed that a large triangle zone of workpiece material was stagnant in front of the tool nose for side cutting with a large tool edge radius, which indicated a built-up edge would form more often as the tool wore. 23
Editor's Notes
- The slotting experiments were conducted for hardened H13 steel with an average hardness of 45 HRC using 900 µm diameter micro endmills by Aramcharoen and Mativenga (Aramcharoen and Mativenga, 2009), while the side cutting tests were conducted for hardened H13 steel with an average hardness of 42 HRC using 100 µm diameter micro endmills by the authors.
- To avoid tool chattering, a slow feed rate of 35 mm/min was used when entering and exiting the workpiece.The Acoustic emission sensor was primarily used as a monitoring tool for the micro milling experiments. The AE RMS signals remained about constant within one cutting pass before the tool was severely worn.
- Clean step geometry with burrs largely remaining on the top surface was observed along the whole machined section. Machining marks can be observed on the end surface and the small steps on the machined end surface were caused by the change of surface contacts after loading and unloading the workpiece or toolA precise dimension control with an accumulated error of about 1% was achieved in the micro side cutting testThe surface roughness of the machined side surface was measured with a non-contact interferometric surface profiler. The surface roughness on the machined side surface was found to be constantly around 0.5 µm in multiple-pass side cuttingorkpiece.
- A cleaner cut surface was generated after 3-minute side cutting, while as the tool wore more severely after 12-minute cutting, more material tearing can be observed on the machined surface.
- The tool nose wear and flank wear developed at a steady rate prior to tool catastrophic failure.
- Fully coupled thermo–mechanical Abaqus/Explicit analysis ALE applied on the top section A with a fine mesh Mesh-to-mesh solution mapping technique is developed between two continuous explicit steps for remeshing the distorted workpiece mesh and solution mappingthe JC modeled flow stress is non-dimensional and independent of the length scale in the FE simulation and hence the models are not suitable for describing the significant size effect in micro cutting.In strain gradient plasticity, a length scale is introduced through the coefficients of spatial gradients of strain components and can be used to model the size effect in micro milling. The length L used in the simulation was chosen to be the maximum uncut chip thickness. Simulations with the Johnson-Cook model was not able to simulate the extreme high specific cutting force occurring in micro cutting for ratio λ less than 0.5. Micro-milling simulation with the strain gradient plasticity model shows a significant size effect in the specific cutting force in micro-milling and matches well with the experimental data for various λ ratios. The simulation results thus validated the efficacy of the FE model with the strain gradient plasticity model for simulating micro-milling
- The FE chip formation simulation was limited to one micro-milling cycle of both micro slotting and side cutting configurations, because coupled thermo-mechanical analysis is too expensive in computation using any commercial finite element software. To correctly model the steady-state cutting temperature only achieved after many milling cycles, a pure heat transfer analysis was performed on the bulk workpiece after the chip formation analysis for further milling cycles at a low computation cost.In every milling cycle of micro slotting and side cutting configurations, the workpiece material is heated locally by heat generation due to plastic deformation and friction at the tool-chip and tool-workpiece interfaces as the tool flute approaches, while it cools down due to heat conduction to the bulk material and heat convection to the air as the flute leaves. If the local heat generation is not dissipated completely to the bulk material by heat conduction and to the environment by heat convection, the temperature of the workpiece will get an increasein the following milling cycle due to the remaining heat. A time-dependent nodal heat flux subroutine was created for the heat transfer analysis of multi cycles, in which the heat flux was used as periodic heat input along the milling paths.
- Continuous chip formation within a complete side cutting cycle for one flute rotation from 26° to 0° with a 0.5 µm edge radius micro tool is shown
- Material removal mechanism transition from cutting to ploughing was investigated by the FE model. Cutting was the main material removal mechanism when the ratio λ was greater than 1. Ploughing played a more important role as λ decreased to below 1. No chip would foVelocity fields simulated with various cutting ratios show a large triangle zone of stagnant workpiece material for side cutting with a small λ less than 1, which indicated a built-up edge would form more often as tool wore rmas λ decreased to below 0.2.