Force prediction in ultrasonic vibration-assisted milling

Feng, Yixuan; Hsu, Fu-Chuan; Lu, Yu-Ting; Lin, Yu-Fu; Lin, Chia Hung; Lin, Chiu-Feng; Lu, Yingcheng; Liang, Steven Y.

doi:10.1080/10910344.2020.1815048

Cited by 42 publications

(11 citation statements)

References 28 publications

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“…Unlike FEM, SPH can present precision and stable solutions to problems involving deformable boundaries, especially for large deformation and crack propagation, by approximating the governing equations of particles. SPH is more favorable for a cutting simulation owing to the particle-based algorithm, eliminating the element’s deformation between particles [ 59 ].…”

Section: Simulation Study Of Cmc Abrasive Machiningmentioning

confidence: 99%

Review on Abrasive Machining Technology of SiC Ceramic Composites

Zhang,

Zhao,

et al. 2024

Micromachines

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Ceramic matrix composites have the advantages of low density, high specific strength, high specific die, high-temperature resistance, wear resistance, chemical corrosion resistance, etc., which are widely used in aerospace, energy, transportation, and other fields. CMCs have become an important choice for engine components and other high-temperature component manufacturing. However, ceramic matrix composite is a kind of multi-phase structure, anisotropy, high hardness material, due to the brittleness of the ceramic matrix, the weak bonding force between fiber and matrix, and the anisotropy of composite material. Burr, delamination, tearing, chips, and other surface damage tend to generate in the machining, resulting in surface quality and strength decline. This paper reviewed the latest abrasive machining technology for SiC ceramic composites. The characteristics and research directions of the main abrasive machining technology, including grinding, laser-assisted grinding, ultrasonic-assisted grinding, and abrasive waterjet machining, are introduced first. Then, the commonly used numerical simulation research for modeling and simulating the machining of ceramic matrix composites is briefly summarized. Finally, the processing difficulties and research hotspots of ceramic matrix composites are summarized.

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Section: Simulation Study Of Cmc Abrasive Machiningmentioning

confidence: 99%

Review on Abrasive Machining Technology of SiC Ceramic Composites

Zhang,

Zhao,

et al. 2024

Micromachines

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“…In this article, a chatter vibration model uses a mechanistic approach for macro-scale milling processes considering the regenerative effect on uncut chip thickness and time effectiveness. Researchers may use other models if the models can reflect the regenerative effect of milling dynamics in uncut chip variations and rotational motions with high frequency [25]. In the case of using commercial FEM software, the simulation time may take one day for one condition even without regenerative effects [26].…”

Section: Generation Of Data Sets For Feature Elements Using Time-doma...mentioning

confidence: 99%

Machining Stability Categorization and Prediction Using Process Model Guided Machine Learning

2022

Metals

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The time-domain dynamic process model is used to generate data and guides the stability criteria for machine learning, saving the experimental costs for a number of required data for the metal process. Fourier transformation of vibration data simulated using a dynamic process model generates the feature lists including multiple frequencies and amplitudes at each process condition. The feature lists for milling stability are analyzed for training the machine learning algorithm. The amplitude and frequency distributions may change according to the dynamic pattern of the machining stability. The vibration patterns are grouped into stable, chatter, and boundary conditions by performing data training using support vector machines and gradient tree boosting. In the high-speed milling of Al6061-T6 with 6000 to 18,000 RPM and variations of axial and radial depths of cuts, 2400 data sets of the time domain data were trained and tested. Actual experimental tests are carried out for new process conditions with the range of 9890 to 28,470 RPM and 989 to 2847 mm/min. The experimental stability outcomes are compared with predictions from the algorithms. Stability is accurately predicted over new conditions with around 0.9 prediction accuracy, which means the methodology can be used to predict, categorize, and monitor stability in end milling processes.

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“…Recently, vibration-assisted micro machining has arisen as a promising approach for accurate and flexible surface texturing [ 12 , 13 , 14 ]. Multiple advantages and improvements have been proved, such as reduced cutting forces [ 15 ], extended tool life, minimized burr formation, improved surface quality [ 16 ], and the ability to machine hardened metals and ceramics [ 17 , 18 ]. Vibration-assisted machining was initially designed to enhance the machinability of challenging materials, and later has proven to be adept at surface texturing.…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Experimental Investigation of Surface Textures in Vibration-Assisted Micro Milling

Song,

Zhang,

Jing

et al. 2024

Micromachines

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Vibration-assisted micro milling is a promising technique for fabricating engineered mi-cro-scaled surface textures. This paper presents a novel approach for theoretical modeling of three-dimensional (3D) surface textures produced by vibration-assisted micro milling. The proposed model considers the effects of tool edge geometry, minimum uncut chip thickness (MUCT), and material elastic recovery. The surface texture formation under different machining parameters is simulated and analyzed through mathematical modeling. Two typical surface morphologies can be generated: wave-type and fish scale-type textures, depending on the phase difference between tool paths. A 2-degrees-of-freedom (2-DOF) vibration stage is also developed to provide vibration along the feed and cross-feed directions during micro-milling process. Micro-milling experiments on copper were carried out to verify the ability to fabricate controlled surface textures using the vibration stage. The simulated and experimentally generated surfaces show good agreement in geometry and dimensions. This work provides an accurate analytical model for vibration-assisted micro-milling surface generation and demonstrates its feasibility for efficient, flexible texturing.

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Force prediction in ultrasonic vibration-assisted milling

Cited by 42 publications

References 28 publications

Review on Abrasive Machining Technology of SiC Ceramic Composites

Review on Abrasive Machining Technology of SiC Ceramic Composites

Machining Stability Categorization and Prediction Using Process Model Guided Machine Learning

Theoretical and Experimental Investigation of Surface Textures in Vibration-Assisted Micro Milling

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