Gear Hobbing Cutting Process Simulation and Tool Wear Prediction Models

2001 ◽  
Vol 124 (1) ◽  
pp. 42-51 ◽  
Author(s):  
K.-D. Bouzakis ◽  
S. Kombogiannis ◽  
A. Antoniadis ◽  
N. Vidakis
Keyword(s):  
Tool Wear ◽  
High Speed ◽  
Prediction Models ◽  
Numerical Models ◽  
High Speed Steel ◽  
Cutting Process ◽  
Wear Prediction ◽  
Tool Wear Prediction ◽  
Gear Hobbing ◽  
The Individual

Gear hobbing is an efficient method to manufacture high quality and performance toothed wheels, although it is associated with complicated process kinematics, chip formation and tool wear mechanisms. The variant cutting contribution of each hob tooth to the gear gaps formation might lead to an uneven wear distribution on the successive cutting teeth and to an overall poor tool utilization. To study quantitatively the tool wear progress in gear hobbing, experimental-analytical methods have been established. Gear hobbing experiments and sophisticated numerical models are used to simulate the cutting process and to correlate the undeformed chip geometry and other process parameters to the expected tool wear. Herewith the wear development on the individual hob teeth can be predicted and the cutting process optimized, among others, through appropriate tool tangential shifts, in order to obtain a uniform wear distribution on the hob teeth. To determine the constants of the equations used in the tool wear calculations, fly hobbing experiments were conducted. Hereby, it was necessary to modify the fly hobbing kinematics, applying instead of a continuous tangential feed, a continuous axial one. The experimental data with uncoated and coated high speed steel (HSS) tools were evaluated, and correlated to analytical ones, elaborated with the aid of the numerical simulation of gear hobbing. By means of the procedures described in this paper, tool wear prediction as well as the optimization of various magnitudes, as the hob tangential shift parameters can be carried out.

Modeling of Gear Hobbing: Part I — Cutting Simulation and Tool Wear Prediction Models

1999 ◽  
Author(s):  
Konstantinos D. Bouzakis ◽  
Spiros Kombogiannis ◽  
Aristomenis Antoniadis ◽  
Nectarios Vidakis
Keyword(s):  
Tool Wear ◽  
Cutting Tool ◽  
Prediction Models ◽  
Cutting Parameters ◽  
Tool Wear Prediction ◽  
Gear Hobbing ◽  
Uneven Wear ◽  
And Performance ◽  
The Individual ◽  
Chip Geometry

Abstract Gear hobbing is the most common method to manufacture high quality and performance toothed wheels. The gear hobbing kinematics induces complicated chip formation and is characterized by convoluted wear mechanisms of the cutting tool. The variant cutting contribution of each cutting tooth is responsible for the uneven wear distribution on the successive hob teeth and the poor utilization of the entire cutting tool. Moreover, the gear width influences the chip geometry in the tool entry and exit regions into the workpiece, and sets a mathematical wear description even more complicated. To study quantitatively the tool wear progress in gear hobbing, experimental-analytical methods have been established. Gear hobbing experiments and advanced mathematical models are hired to correlate the undeformed chip geometry and other cutting parameters with the anticipated wear. With the aid of such procedures and of appropriate constants, essential for the description of the wear development in the individual gear gaps generating positions, an optimization of the hobbing process can be achieved. Hence, among others, appropriate tangential shifts of the hobbing tool may be predicted.

Modeling of Gear Hobbing: Part II — A Computer Supported Experimental-Analytical Determination of the Wear Progress to Optimize the Tool Life Time

1999 ◽  
Author(s):  
Konstantinos D. Bouzakis ◽  
Spiros Kombogiannis ◽  
Aristomenis Antoniadis ◽  
Nectarios Vidakis
Keyword(s):  
Tool Wear ◽  
Prediction Models ◽  
Digital Simulation ◽  
Life Time ◽  
Analytical Determination ◽  
Tool Wear Prediction ◽  
Gear Hobbing ◽  
User Friendly ◽  
Continuous Enrichment

Abstract Tool wear prediction models for gear hobbing were presented in the first part of this paper. To determine the constants of the equations used in these models, fly hobbing experiments with uncoated and coated HSS tools were conducted. Hereby, it was necessary to modify the fly hobbing kinematics from continuous tangential feed to continuous axial feed. The experimental data were evaluated, and correlated to the analytical ones, elaborated through the described digital simulation of the cutting process. The determined constants of the wear laws for the investigated tools were used in a further developed user friendly software, enabling the prediction of the tool wear accomplishment in gear hobbing. On that account the wear development can be precisely foreseen and the tangential shift of the tool is optimized. The open and modular structure of the developed code enables the continuous enrichment of its database with other type of coating and workpiece materials. With the aid of the aforementioned techniques, the superiority of coated HSS tools in comparison to uncoated ones is also quantitatively exhibited.

Mesh node rigid moving algorithm for the uncoated milling cutter tool wear prediction considering periodic process variables

2016 ◽  
Vol 231 (19) ◽  
pp. 3635-3648 ◽  
Author(s):  
H-B Liu ◽  
Y-Q Wang ◽  
D Wu ◽  
B Hou
Keyword(s):  
Tool Wear ◽  
Fem Simulation ◽  
High Speed Steel ◽  
Periodic Process ◽  
Process Variables ◽  
Wear Prediction ◽  
Milling Cutter ◽  
Tool Wear Prediction ◽  
Cutting Model ◽  
Mesh Node

Milling is a typical intermittent cutting process. As a result, tool wear is generated cyclically due to periodic process variables. However, the traditional tool wear prediction strategy based on continuous cutting model is no longer applicable. In this paper, a novel geometric approach through mesh node rigid moving for the milling cutter tool wear prediction has been developed. Firstly, a unified tool wear predictive model is established through bridging the two wear configurations before and after worn. A coupled abrasive–diffusive model is employed to calculate the tool wear volume of each point on tool face. Further, a novel iterative algorithm for tool wear prediction through mesh node rigid moving layer-by-layer and process variables redistribution is designed in discrete-time domain, which is generally decomposed into two phases according to cutting heat equilibrium state, FEM simulation and offline calculation. Last, a series of numerical and saw-milling experiments for flank wear prediction were implemented to verify the developed approach. The AISI304 and the high vanadium high-speed steel tool without coating were adopted. By comparison, the predicted results were consistent with the experimental overall. It has been proved that the proposed approach is more effective than pure FEM simulation and is suitable for long-term milling tool wear prediction.

2D FEM Estimate of Tool Wear in Hard Cutting Operation: Extractive of Interrelated Parameters and Tool Wear Simulation Result

2009 ◽  
Vol 69-70 ◽  
pp. 316-321 ◽  
Author(s):  
Cai Xu Yue ◽  
Xian Li Liu ◽  
Hong Min Pen ◽  
Jing Shu Hu ◽  
Xing Fa Zhao
Keyword(s):  
Tool Wear ◽  
Cutting Temperature ◽  
Cutting Process ◽  
Wear Loss ◽  
Cutting Condition ◽  
Machined Surface ◽  
Wear Prediction ◽  
Tool Wear Prediction ◽  
Cutting Model ◽  
Hard Cutting

Tool wear plays an important part during cutting process, and wear loss has a close relationship with cutting condition, which affects machined surface mostly. In order to accomplish tool wear prediction in way of FEM, based on founding of cutting model under steady state, interrelated parameters needed for tool wear prediction, such as cutting temperature, contact pressure and raletive sliding velocity are extracted. By compiling Python subprogram and using Abaqus tool in hard cutting process PCBN tool wear is predicted, which provide foundation for optimizing cutting condition.

Fatigue Fracture Investigation of Cemented Carbide Tools in Gear Hobbing, Part 1: FEM Modeling of Fly Hobbing and Computational Interpretation of Experimental Results

2002 ◽  
Vol 124 (4) ◽  
pp. 784-791 ◽  
Author(s):  
A. Antoniadis ◽  
N. Vidakis ◽  
N. Bilalis
Keyword(s):  
High Speed ◽  
Cutting Tool ◽  
Complex Geometry ◽  
High Speed Steel ◽  
Cutting Performance ◽  
Cutting Process ◽  
Cemented Carbide ◽  
Fem Modeling ◽  
Gear Hobbing ◽  
Cemented Carbide Tools

Gear hobbing is a highly utilized flexible manufacturing process for massive production of external gears. However, the complex geometry of cutting hobs is responsible for the almost exclusive utilization of high-speed steel (HSS) as cutting tool material. The limited cutting performance of HSS, even coated HSS, restricts the application of high cutting speeds and restricts the full exploitation of modern CNC hobbing machine tools. The application of cemented carbide tools was considered as a potential alternative to modern production requirements. In former investigations an experimental variation of gear hobbing, the so-called fly hobbing was applied, in order to specify the cutting performance of cemented carbide tools in gear production. These thorough experiments indicated that cracks, which were not expected, might occur in specific cutting cases, leading to the early failure of the entire cutting tool. In order to interpret computationally the reasons for these failures, an FEM simulation of the cutting process was developed, supported by advanced software tools able to determine the chip formation and the cutting forces during gear hobbing. The computational results explain sufficiently the failure mechanisms and they are quite in line with the experimental findings. The first part of this paper applies the verified parametric FEM model for various cutting cases, indicating the most risky cutting teeth with respect to their fatigue danger. In a step forward, the second part of the paper illustrates the effect of various technological and geometric parameters to the expected tool life. Therefore, the optimization of the cutting process is enabled, through the proper selection of cutting parameters, which can eliminate the failure danger of cemented carbide cutting tools, thus achieving satisfactory cost effectiveness.

scholarly journals Multi-Scale Convolutional Gated Recurrent Unit Networks for Tool Wear Prediction in Smart Manufacturing

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Weixin Xu ◽  
Huihui Miao ◽  
Zhibin Zhao ◽  
Jinxin Liu ◽  
Chuang Sun ◽  
...  
Keyword(s):  
Tool Wear ◽  
Information Technologies ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Wear Prediction ◽  
Multi Scale ◽  
Tool Wear Prediction ◽  
Machine Health Monitoring ◽  
Gated Recurrent Unit ◽  
Unit Network

AbstractAs an integrated application of modern information technologies and artificial intelligence, Prognostic and Health Management (PHM) is important for machine health monitoring. Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry. In this paper, a multi-scale Convolutional Gated Recurrent Unit network (MCGRU) is proposed to address raw sensory data for tool wear prediction. At the bottom of MCGRU, six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network, which augments the adaptability to features of different time scales. These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations. At the top of the MCGRU, a fully connected layer and a regression layer are built for cutting tool wear prediction. Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.

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