Dry Hobbing Research Articles

A temperature-sensitive points selection method for machine tool based on rough set and multi-objective adaptive hybrid evolutionary algorithm

Reasonable deployment of temperature sensors is the key to accurately monitoring the temperature field of machine tools and improving the accuracy of thermal error prediction and compensation models. To determine the optimal deployment location of sensors, this paper proposes a temperature-sensitive points selection method tightly coupled with rough set and multi-objective optimization. Firstly, the importance of each temperature measurement point to the thermal error is calculated based on the rough set, and information entropy is introduced to amplify the importance difference among adjacent measurement points at the same heat source. Then, with the temperature measurement points groups as the variables, the number of temperature measurement points in the group, and the information importance of the group as the objectives, a multi-objective attribute reduction model is established, which transforms the temperature-sensitive points selection problem into a discrete multi-objective optimization problem. Finally, a multi-objective adaptive hybrid evolutionary algorithm is proposed, which designs a population initialization method based on mutual information and interval probability, and dynamic adaptive evolutionary parameters to achieve optimal temperature-sensitive points selection. Experiments on the high-speed dry hobbing machine verify the superiority and effectiveness of the proposed method.

Prediction of the Modal Parameters of The Spindle System in High-speed Dry Hobbing Machine with Thermal Effects

High-speed dry hobbing is an advanced green machining technology for gears. However, thermal issues in the machine tools become serious under the high cutting speed and dry cutting conditions, which result in a nonlinear evolution of the machine tool dynamics, and finally affect the hobbing stability. In view of this, introducing the hob spindle system as the object, this paper intends to investigate the influence of time-varying temperatures on the modal parameters based on the modal tests. Then, a temperature-dependent modal parameters prediction model based on the multi-output Gaussian process regression (MOGPR) is proposed. The experimental results indicated that the modal parameters of the spindle system vary obviously with changing thermal states. The natural frequencies for the first and third modes increased with the temperature rise, while the variation of the natural frequency for the second mode was insignificant. The damping ratios for the first three modes showed a decreasing trend with the temperature rise. The constructed MOGPR model has the capability to effectively predict the modal parameters with the time-varying thermal effects, which can provide a support to build the temperature-dependent hobbing stability boundaries.

Spatial distribution model of thermal load for high-speed dry hobbing tool based on probability density function

High-speed dry hobbing is a clean and environmental-friendly gear machining process, but thermal dissipation inefficiency accelerates tool wear and shorten tool life which is difficult to be effectively inhibited due to its complex distribution characteristics. This paper proposes a thermal load distribution model based on probability density function, describing the spatial distribution of thermal load on tool and providing theoretical support for predicting the distribution of thermal load. Firstly, conducting a finite element simulation analysis based on a mathematical model of high-speed dry gear hobbing process; Secondly, the influence of various parameters on the constructed model is analyzed, and the Bayesian optimization algorithm is utilized to optimize the model parameters. Finally, the model is validated at the micro and macro level. The results show that the average coefficient of determination of the model is greater than 0.86 in micro level. And the average fitting error is less than 6 °C in macro level, besides, the average relative error is less than 15%. The description of the uneven thermal distribution on tool is obtained with probability density function, it provides a theoretical support for the prediction and further optimization of thermal load on tool under multiple parameters in the future.

High stability multi-objective decision-making approach of dry hobbing parameters

High-speed dry hobbing is an advanced and green manufacturing technology. The use of intelligent algorithm for process parameter decision-making is receiving more and more attention in dry hobbing. The process parameter results of each operation of these methods are inconsistent, that is, the numerical fluctuation of results. To resolve this problem, a multi-objective decision-making approach of process parameters is proposed for high-speed dry hobbing based on K-means clustering, multi-objective Runge Kutta optimizer (MORUN) and Analytic Hierarchy Process (AHP). First, based on the past process cases of dry hobbing, K-means clustering is used to determine the cluster centers and case clusters. For the problem of dry hobbing process parameters to be decided, the distance from each cluster center is calculated and the similar case clusters are found. The numerical range of process parameters is determined. Then, based on the well-established machining parameters model of dry hobbing with the optimization objectives of machining energy consumption, quality and time, MORUN is developed and used to find the optimized process parameters. Finally, regarding the users' emphasis on objectives, AHP is used to sort all the optimized process parameters obtained, and the first ranked process parameter is used for machining. The feasibility of the proposed approach is verified by the actual hobbing. Compared with other well-established methods, the proposed approach can effectively solve the problem of numerical fluctuation of optimization results, has high stability, and select the optimal term from several optimization process parameters.

Optimization of chip repose angle in dry hobbing machine considering minimum thermal accumulation on workbench

The thermal deformation problem is quite serious for the workbench of the environmental dry hobbing machine due to the thermal accumulation of hot chips. A better understanding of the quantity and optimization of the chip repose angle is quite necessary to reduce the workbench thermal deformation. Hence, this paper focuses on the chip repose angle modeling and optimization for the workbench of the dry hobbing machine. Firstly, the dynamic flow characteristics of chips are clarified by analyzing the chip generation mechanism and the motion trajectory of dry hobbing. Then, the chip repose angle is mathematically characterized with consideration of the chip rolling characteristics, with which a chip repose angle optimization model is established by minimizing the thermal accumulation on the workbench, and a chip repose angle optimization method is proposed based on the intelligent optimization algorithm. Finally, the effectiveness of the proposed method is analyzed through the simulation experiment on the dry hobbing of automotive reverse gear. The results show that the maximum overall thermal deformation is reduced by 8 μm for the workbench, and the skewness is reduced by 32% for the workbench spindle with the help of the proposed optimization method. The study provides an effective solution for the quantitative analysis and optimal design of chip repose angle on the workbench of the dry hobbing machine.

The approach to multi-objective optimization for process parameters of dry hobbing under carbon quota policy

The approach to multi-objective optimization for process parameters of dry hobbing under carbon quota policy

Influence of thermal effect on dynamic behavior of high-speed dry hobbing motorized spindle system

Influence of thermal effect on dynamic behavior of high-speed dry hobbing motorized spindle system

Simulation and experimental study of tool wear in high-speed dry gear hobbing

Simulation and experimental study of tool wear in high-speed dry gear hobbing

Heat transfer enhancement strategies for eco-friendly dry hobbing considering the heat exchange capacity of chips

To reduce the adverse effect of thermal accumulation, a better understanding of heat transfer is quite necessary for eco-friendly dry hobbing, which is completely different from common turning and milling. The paper focuses on the cutting heat transfer enhancement of dry hobbing with consideration of the heat exchange capacity of dominant heat carrier. Firstly, the generation and transfer process of cutting heat are analyzed on a micro level according to the interrupted cutting characteristic with multiple cutting edge of dry hobbing. Secondly, a multi-field coupling simulation combined with thermal imaging reconstruction is carried out to determine the dominant heat carrier of cutting heat. Furthermore, influence factors are investigated for the heat exchange capacity of the dominant heat carrier (the chips) based on the modified model of specific cutting energy. Finally, heat transfer enhancement strategies are investigated considering the heat exchange capacity of chips. The findings demonstrate wide potential applications for thermal deformation reduction and machining quality improvement in dry hobbing process.

Multi-verse optimizer based parameters decision with considering tool life in dry hobbing process

Dry hobbing has received extensive attention for its environmentally friendly processing pattern. Due to the absence of lubricants, hobbing process is highly dependent on process parameters combination since using unreasonable parameters tends to affect the machining performance. Besides, the consideration of tool life is frequently ignored in gear hobbing. Thus, to settle the above issues, a multi-objective parameters decision approach considering tool life is developed. Firstly, detailed quantitative analysis between process parameters and hobbing performance, i.e., machining time, production cost and tool life is introduced. Secondly, a multi-objective parameters decision-making model is constructed in search for optimum cutting parameters (cutting velocity v, axial feed rate $$f_{{\text{a}}}$$ ) and hob parameters (hob diameter d0, threads z0). Thirdly, a novel algorithm named multi-objective multi-verse optimizer (MOMVO) is utilized to solve the presented model. A case study is exhibited to show the feasibility and reliability of the proposed approach. The results reveal that (i) a balance can be achieved among machining time, production cost and tool life via appropriate process parameters determination; (ii) optimizing cutting parameters and hob parameters simultaneously contributes to optimal objectives; (iii) considering tool life provides usage precautions support and process parameters guidance for practical machining.

Data-driven based optimization for high-speed dry cutting gear hobbing processing parameters

The formulation of gear hobbing processing parameters relies on extensive professional knowledge and artificial experience, and inappropriate processing parameters will lead to low machining precision and high manufacturing costs. In order to obtain suitable processing parameters in high speed dry hobbing gear process, Gradient boosting regression (GBR) and Generalized Regression Neural Network (GRNN) are adopted to establish a process parameter optimization model targeting gear machining accuracy and machining energy consumption. And then a method based on Differential Evolution (DE) algorithm, parameter adaptive multi-object differential evolution (AMDE), for hobbing processing parameter optimization is proposed. Machining experiment verification shows that the established gear hobbing accuracy prediction model and energy consumption estimation model have high prediction accuracy, and AMDE has strong optimization capabilities and robustness.

Integrated optimization method for helical gear hobbing parameters considering machining efficiency, cost and precision

The formulation of dry hobbing processing parameters depends heavily on mass experiments and the experiences of skilled technicians, and the use of unsuitable parameters will lead to high cost, low efficiency and severe precision defects. To resolve this issue, a helical gear processing parameter optimization method (PPOM-HG) is proposed in this paper. First, an efficiency-cost-accuracy triple-target optimization model is established. A manufacturing efficiency model is established through a detailed analysis of the geometric trajectory of a hob. A helical gear manufacturing cost model is established by analyzing the power curve of the hobbing machine and the hob’s lifetimes under various processing parameters. A modified correlation analysis random forest (CARF) model is designed for predicting gear machining precision, which replaces the traditional empirical precision function. Then, for searching for the optimal solution of the established efficiency-cost-precision triple-target model, an adaptive multiobjective fusion evolutionary algorithm (AMFEA) with adaptive evolution parameters is proposed. Finally, via many helical gear machining experiments, the validity and advantages of the proposed CARF and AMFEA methods are demonstrated, and the selection strategy of the Pareto front solution under various conditions is discussed.

High Speed Precision Dry Hobbing Replacing Conventional Hobbing and Shaving

High Speed Precision Dry Hobbing Replacing Conventional Hobbing and Shaving

Hobbing of Cylindrical Wheels without Coolants

This article studies dry hobbing of external cylindrical wheels by worm wheel hobs and reasons why some gear manufactures use hobbing without cutting fluids. Cutting fluids reduce frictional wear, provides temperature cooling of the tool or workpiece and helps flush away the chips from the cutting zone. But uneven cooling and different cutting conditions on the engaging and disengaging sides of a gear mesh provoke intensive wear of the teeth of the worm wheel hob, thus decreasing the life of worm hobs and increasing both the consumption of cutting tools and expenses for them. In this context, it becomes rather difficult to achieve efficiency and stability for the hobbing process. In the recent times, the cost of coolant disposal has been raised; in some cases, it accounts for 15-20% in terms of shop costs. Research was carried out under the following experimental conditions: a hobbing machine equipped with an automation system of high efficiency and with basic units of high static and dynamic stiffness; a high-accuracy worm hob from powdered metal wear-resistant high-speed steel of grade Р6М5К5; a workholding device with an elastic bush, and various cutting modes. Recommendations are given on using the multi-cycle hob-shifting strategy rather than the strategy of single-cycle shifting; and advantages gained by this technique are observed. Best cutting conditions and precision attained by dry gear-hobbing are described.

Exergy efficiency optimization model of motorized spindle system for high-speed dry hobbing

High-speed dry hobbing (HSDH) has been regarded as an environmentally benign gear machining technique. Current research on energy efficiency of machine tool focuses on the energy efficiency for workpiece material removal but rarely involves the energy consumption required to control thermal stability. Due to the fact that thermal effect dominates the machining accuracy and accuracy consistency, especially in the dry machining process, the energy consumption for thermal stability control should be taken as useful energy consumption. In view of this, by taking the motorized spindle system (MSS) as the study objective, which is a core subsystem of machine tool enabling HSDH and characterizes intensive and inefficient energy consumption, an exergy-based method is proposed to evaluate the comprehensive energy efficiency of MSS. Furthermore, an exergy efficiency optimization model is proposed to maximize total exergy efficiency and minimize average temperature of MSS. A solution method integrating Pareto Dominant-based Multi-objective Simulated Annealing (PDMOSA) and Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to search the best solution of the optimization model. A case study is introduced to validate the proposed model and a final optimal solution is obtained at the total exergy efficiency of 53.5% with balanced temperature of 35.4 °C. The cooling water in MSS is identified to be a dominant factor that affects total exergy destruction. The presented model can give a reference to select appropriate process parameters of MSS for green and precision machining.

Fundamental research on wear behavior of various coated tools in dry hobbing (Influence of hardness of work material)

Fundamental research on wear behavior of various coated tools in dry hobbing (Influence of hardness of work material)

Critical study on the thermal-structural characteristics of worktable assembly of a dry hobbing machine

Dry hobbing machine is a kind of specialized machine tool to manufacture high-quality small-module gears. With the development of shipbuilding, automobile, and wind power industries, higher request on the dry gear hobbing accuracy is called. The thermal-induced error, which accounts for 50–70% of machining error, needs to be reduced more efficiently. Hence, in-depth investigation on the thermal-structural characteristics of the dry hobbing machine is indispensable. In this paper, thermal-structural coupling numerical simulations were conducted to investigate the heat transfer process as well as thermal-induced deformation of the worktable of a YDE3120CNC gear hobbing machine in the large-volume gear production. New equations were used here to describe the convection heat transfer happened on the worktable assembly. Verifying test results proved the feasibility of the newly proposed numerical method. Following numerical simulation, results indicated that during the gear hobbing process, the highest surface temperature of the worktable assembly appeared at the top surface of the fixture, and corresponding thermal-induced deformation reached the maximum of 49.9 μm. Besides, in a large-volume production, the worktable assembly would attain thermal equilibrium in 15,000 s. Hence, the assumption widely used in previous studies on gear hobbing machines that the worktable assembly could be treated as an ideal solid without any thermal deformation is wrong. The thermal-induced deformation of the worktable assembly should be considered in the subsequent development of the thermal error compensation system.

Thermal energy balance control model of motorized spindle system enabling high-speed dry hobbing process

High-speed dry hobbing has been confirmed as a dominant advanced technique for gear machining due to its outstanding performance in terms of high productivity and environmental friendliness. The motorized spindle system is the key component of the high-speed dry hobbing machine, and its thermal stabilization is of significant importance for the machining precision. However, due to the integration of motor and spindle, the adoption of high cutting speed and the heavy cutting load, thermal energy will accumulate in the motorized spindle system and result in thermal deformation and stability degeneration, which eventually affects the consistency of hobbing accuracy. In this paper, an analytical model is proposed to control the thermal energy balance of a high-speed dry hobbing spindle system by optimizing the thermal energy accumulation with the hob rotation speed, hob axial feed rate, cooling water flow rate and the compressed air temperature. The optimal solution is obtained by solving the proposed optimization model with the simulated annealing method. A motorized spindle system is introduced as a case study and the experimental results indicate that the maximum value of the average temperature of the motorized spindle system is reduced from 39.6 °C to 35.0 °C, an 11.6% margin, and the material removal time is reduced from 2.07 min to 1.06 min, a 48.8% margin, under the optimal condition. Moreover, the average runout value of a hobbed workpiece is effectively controlled, by a 15.7% margin. Therefore, the presented optimization model can give a reference for the selection of suitable process parameters for thermal stability control and higher machining productivity and accuracy.

A method for thermal characteristics modelling of hob assembly on dry hobbing machine

Gear hobbing is the use of machinery to manufacture external gears. With the booming motor industry, there are more requirements for gear hobbing accuracy than ever before. Thermal error – as a major source of error in a dry hobbing machine – must be effectively compensated to achieve accuracy. Thus, studies on the thermal error of hob assembly are important both in theory and practice. This paper discusses the development of a valid numerical modelling method for the hob assembly of a dry hobbing machine. The equations used to determine the values of heat sources and heat transfer coefficients are given. The temperature field and thermal deformation of the hob assembly were obtained by thermal-structural coupling numerical simulations. Numerical results showed that the deformation can maximally reach to 94.5 µm, which is non-ignorable in the thermal deformation analysis of the whole dry gear hobbing machine. Subsequently, by comparing the simulation results and experimental data, the newly proposed method to determine the forced convection heat transfer coefficient proved more fitting for describing the airflow pattern inside the gear hobbing zone. The satisfactory agreement between simulation results and experimental data also suggests that the numerical analysis method proposed in this paper can provide an effective research tool to optimize the design of hob assembly. And the results obtained by the proposed method can be used for thermal error modelling in real error compensation.

Study on mapping rules and compensation methods of cutting-force-induced errors and process machining precision in gear hobbing

Based on the homogeneous coordinate transformation method and finite element simulation method of a whole hobbing machine, this paper proposes a highly applicable force-induced error model for a high-speed dry hobbing machine. The number of parameters needed in the error estimation can be effectively reduced by using this model, which has great value in industry application. According to the engagement features of the conjugating surface and the principle of two-degrees-of-freedom hobbing, the meshing equation was deduced and the force-induced errors of the system were mapped to the normal errors of gear surface. In this way, the mapping relationship between different kinds of force-induced errors and hobbing precision can be obtained. Then, the theoretical tooth surface and the real tooth surface under the influence of force-induced errors were respectively calculated by using a numerical simulation method. Based on numerical simulation results, the mathematical relationship between the tooth profile root-mean-square error (RMSE) and the compensation variables was obtained, as well as the optimal value of the compensation variables. The following experimental results validate the feasibility and accuracy of this error compensation method. This study has an important guiding role in the improvement of dry gear hobbing precision.