Model Of Grinding Process Research Articles

Effect of magnetic needle magnetic particle grinding process on the performance of metal aluminum plates

Magnetic needle grinding processing technology is one of the magnetic grinding processing techniques. It possesses the characteristics of micro-cutting removal, small increase in processing temperature, flexible processing, high-quality, and high-precision processing. It is mainly utilized to remove burrs at the edge of the workpiece and the edge of the hole, as well as to finish the surface of the workpiece. It is frequently employed in civil, aerospace, navigation, and other fields. Due to the randomness and complexity of magnetic needle movement in magnetic abrasive finishing, it is difficult to quantify the processing parameters and predict processing effects. Therefore, this paper establishes a simulation model of magnetic needle in magnetic abrasive finishing by the coupling numerical simulation method of fluid dynamics discrete element method (CFD-DEM) to analyze the working state parameters of the magnetic needle. Through the simulation of actual working conditions, the machining process and parameters of magnetic abrasive finishing are quantified and analyzed, and the motion trend of magnetic needles during the machining process is studied. Then, the residual stress of single magnetic needle impact is analyzed with ABAQUS, and the performance enhancement of the workpiece is predicted. Finally, observations of surface morphology and validation of residual stress prediction were conducted through experiments on an aluminum plate. The results show that the residual stress of the aluminum plate is positively correlated with the number of strikes of the magnetic needle. The residual stress changes from tensile stress (+0.1 MPa) to compressive stress (-16.5 MPa). The comparison between simulation results and experimental results is good, indicating that the simulation model can comprehensively consider multiple factors such as magnetic field, particle motion, and fluid flow, and establish a magnetic needle magnetic grinding process model that is suitable for actual working conditions.

Improving the efficiency of gear grinding technology for mine conveyor drives

The aim of this work is to develop a mathematical model of the gear grinding process using the method of high-performance profile copying and determine the optimal parameters of grinding modes according to the temperature criterion. It is shown that in order to ensure defect-free machining of gears under deep grinding conditions, it is necessary to significantly reduce the rate of the feed speed of the grinding wheel along the tooth of the gear wheel. For a grinding depth of 0.4 mm, it should be equal to 2.27 m/min. In this case, the machining productivity can be increased up to 5 times with the simultaneous elimination of the formation of sticking, microcracks and other temperature defects on the machined gear surfaces. This processing effect is achieved by using a modern HOFLER RAPID 1250 gear grinding machine and highly porous abrasive wheels, which are characterized by high cutting capacity. Thanks to the improved quality of gear processing, the quality and performance of manufactured mine conveyor drives (planetary gearboxes with a power of more than 200 kW) have been improved, and the number of repairs required in harsh mine conditions has been significantly reduced.

Research on Grinding Force Prediction of Flexible Abrasive Disc Grinding Process of TC17 Titanium Alloy

Abrasive disc grinding is currently a key manufacturing process to achieve better accuracy and high-quality surfaces of TC17 components. Grinding force, which results from the friction and elastic–plastic deformation during the contact and interaction between the abrasive grains and the workpiece, is a critical parameter that represents the grinding accuracy and efficiency. In order to understand the influence factors of grinding force, the characteristics of the flexible abrasive disc grinding process were studied. Considering the contact state between the abrasive tool and the workpiece, the theoretical model of normal grinding force was established in detail, from macro- and micro-perspectives. By conducting single-factor and orthogonal grinding experiments of TC17 components, the influence of different process parameters on the normal grinding force was revealed. The normal grinding force prediction models of the abrasive disc grinding process were developed based on the Box–Behnken design (BBD) and particle swarm optimization–back propagation (PSO-BP) neural networks, respectively. The results showed that the normal grinding force was negatively correlated with the disc rotational speed, and positively correlated with the contact angle, grinding depth, and feed rate, and the interaction of the factor feed rate and grinding depth was the more influential factor. Both the BBD and PSO-BP force models had good reliability and accuracy, and the mean absolute error (MAE) and mean relative error (MRE) of the above two prediction models were 0.22 N and 0.16 N, and 13.3% and 10.9%, respectively.

Experimental modelling and multi-objective optimisation of electrochemical discharge peripheral surface grinding process during machining of alumina epoxy nanocomposites

Experimental modelling and multi-objective optimisation of electrochemical discharge peripheral surface grinding process during machining of alumina epoxy nanocomposites

Study on surface quality of CNTs/2009Al composites in grinding process with a volume fraction ratio of 3%

Composite materials made of aluminum-based carbon nanotubes (CNTs/Al) are often employed in industries like aerospace and national defense that place a high priority on material processing accuracy at the material’s surface. The most popular machining technique for enhancing the surface quality of materials is grinding. This paper built a prediction model for the surface roughness of CNTs/2009Al composites and identified the process of micro-grinding. Using the ABAQUS software, a non-uniform finite element simulation model of the single abrasive grain grinding process of CNTs/2009AL composites was created. An electroplated diamond grinding rod with a diameter of 2 mm was used in the micro-grinding experiment on the CNTs/2009Al composite, and the impact of the grinding parameters on the quality of the machined surface was examined. According to the findings, the feed speed has the least impact on the material’s surface roughness, whereas the spindle speed and grinding depth both have a significant impact. The measurement of the minimal roughness is 0.117 m. A shallower grinding depth, a lower feed rate, and a correspondingly higher spindle speed should be used in order to provide a superior surface quality. According to the prediction model of micro-grinding surface roughness and laser confocal microscope scanning, the primary phenomena of CNTs in the grinding process include pull-out, fracture, and elastic deformation.

Temperature modeling of creep-feed grinding processes for nickel-based superalloys with variable heat flux distribution

Temperature modeling of creep-feed grinding processes for nickel-based superalloys with variable heat flux distribution

Research on the consistency model of roundness error in journal cylindrical grinding with random parameters

The accuracy consistency of the journal of the same batch of workpieces directly affects the interchangeability of products, cylindrical grinding is an important means to form the final machining accuracy of workpiece journals. Due to the grinding process system is susceptible to interference, for a given grinding system, the existing model cannot be used to evaluate the consistency of roundness error in the same batch grinding process. In this paper, the vibration coupling model of the cylindrical grinding process is established, and the iterative algorithm of “grinding force-instantaneous grinding depth” is proposed. On this basis, the grinding parameters are reflected in the coupling model of the grinding system with random characteristics within the design range, and the roundness error distribution of the same batch of workpiece journals after grinding is simulated by the Monte Carlo method to form a statistical analysis method of roundness error batch consistency. The validity of the proposed grinding roundness error consistency analysis method is confirmed by the corresponding grinding test. Finally, the influence of the grinding parameters on the consistency of roundness error after grinding is analyzed, and the research conclusions can provide reference for the design of grinding quality consistency.

Experimental modeling and multiobjective optimization of electrochemical discharge peripheral surface grinding process during machining of alumina epoxy nanocomposites

Experimental modeling and multiobjective optimization of electrochemical discharge peripheral surface grinding process during machining of alumina epoxy nanocomposites

Modeling and Industrial Development of Grinding Processes in Roller Mills with Corrugated Rolls

Modeling and Industrial Development of Grinding Processes in Roller Mills with Corrugated Rolls

Optimal surrogate building using SVR for an industrial grinding process

ABSTRACT Transient states modeling of industrial grinding process with significant accuracy is extremely essential to run these energy intensive processes in optimal conditions ensuring sustainability. Traditional modeling using physics-based approach not only demands extensive process knowledge but also results in time-expensive models difficult to use during iterative processes like optimization. Proposing Support Vector Regression (SVR) as an alternative data driven tool, such a surrogate building task has been performed under an optimization framework. Minimizing square root of mean square error (RMSE) between ground truth and model predictions, optimal hyper-parameter combination is achieved using a novel genetic algorithm-based formulation indicating a paradigm shift as opposed to the usual practice of determining them heuristically. The RMSE of the grinding model obtained using the proposed formulation is reported as 0.00496. When compared with another model obtained using conventional approach, prediction plots indicate the effectiveness of the novel algorithm. Comparison with coefficient of correlation leads similar conclusion, where the least RMSE model has 99.88% and the conventional model has 71.40% correlation value. Such dynamic surrogates with optimal hyper-parameter settings can be extremely useful for control and optimization of grinding processes and can be easily extendable to design of experiment-based response surface modeling.

Prediction model of needle valve body extrusion grinding process based on PSO-SVR

The needle valve body is one of the core components of the diesel engine injection system, there is a complicated non-linear relationship between process parameters and process effects in its extrusion and grinding process, and it is difficult to establish specific mathematical expressions to describe the process rules. Therefore, this paper adopts support vector regression (SVR) establish a needle valve body extrusion grinding process model, and uses flow coefficient and grinding efficiency as dual output prediction targets. The particle swarm optimization algorithm (PSO) with better global search ability is introduced to optimize and improve the model. The results show that the optimized model has a smaller error between the predicted value and the actual value of the data, and the prediction accuracy is significantly improved. The model can reflect the process law of the needle valve body extrusion and grinding process to a certain extent, and it can provide certain guidance for selecting process parameters in the extrusion and grinding process.

Modeling of external cylindrical grinding process using T1 tool steel

The selection of the optimal external cylindrical grinding conditions importantly contributes to increase of productivity and quality of the products. The external cylindrical grinding is a method of finishing machine elements surface with an indeterminate blade shape. External cylindrical grinding can process surfaces that require high gloss and precision, although it can also be used to remove large surplus stock. Therefore, multi objective optimization for the external cylindrical grinding process is a problem with high complexity. In this study, an experimental study was performed to improve the productivity and quality of grinding process. By using the experimental date, the surface roughness, cutting force, and vibrations were modeled. To achieve the minimum value of surface roughness and maximum value of material removal rate, the optimal values of external cylindrical grinding conditions were determined by using the combination of Genetic Algorithms (GAs) and weighting method. The optimum values of surface roughness and material removal rate are 0.510 μm and 5.906 mm2/s, respectively. The obtained optimal values of cutting parameters were a feed rate of 0.3 mm/rev, a workpiece speed of 188.1 rpm, a cutting depth of 0.015 mm, and a workpiece Rockwell hardness of 54.78 HRC. The optimal values of cutting parameters, and workpiece hardness were successfully verified by comparing of experimental and predicted results. The approach method of this study can be applied in industrial machining to improve the productivity and quality of the products in external cylindrical grinding process of the T1 tool steel

Mathematical modeling of the sunflower cake grinding process

The design of an improved sunflower cake grinder is proposed, which consists in the modernization of knives in knife blocks in the form of an Archimedes Arbelo curvilinear triangle with saw-edged teeth along the perimeter of the entire surface of the cutting edge. This will allow obtaining cake in a crumbled form, depending on the type of the farm animal by constructing a mathematical model that considers physical and mechanical properties of the material, which describes the dependence of its design parameters on the factors under study that affect the technological process of its production and thereby improve the grinding quality. The article presents the mathematical model that allows determining the optimal values of the design parameters of the improved grinder. The improved sunflower cake grinder allows reducing its specific energy consumption compared to series-produced ones without deteriorating the quality of the material and to increase its performance. Based on the experimental studies conducted, the improved sunflower cake grinder allows it to be used in technological lines for the production of mixed feed with its adding in a crumbled form. The obtained design parameters of the improved grinder will be used in the further modernization of series-produced grinders for concentrated feed produced by Russian enterprises for various types of farm animals, which will allow replacing imported concentrated feed with Russian ones and thereby not depend on them due to the current situation in the world.

Variation of wheel-work contact geometry and temperature responses: Thermal modeling of cup wheel grinding

For the thermal modeling of cup wheel grinding process, most previous studies ignored the effect of wheel-work contact geometry on the amplitude and distribution of heat flux and grinding temperature, which oversimplifies the heat transfer condition when compared with that in the real grinding process, as a cup wheel typically has a rounded edge, due to the rapid wear during the initial grinding passes. In this paper, the relationships among the wheel-work contact geometry, the local material removal pattern at the grinding zone and the grinding temperature distribution have been investigated. A comprehensive 3D analytical thermal model considering the wheel-work contact geometry and its effect on the grinding heat flux distribution has been established and experimentally validated. The heat flux distribution in cup wheel grinding varies with the contact geometry and also the grinding parameters, which has never been mentioned in previous works. It has been found that the variation of the contact geometry significantly changes the local material removal pattern, and thus affects the grinding temperature distribution. Validation experiment results have demonstrated that the developed model could, to a great extent, describe the realistic grinding temperature. The relative errors of the maximum temperature are less than 6.6%, and the relative errors of the position of the maximum temperature are less than 8.5%. This research not only provides a new method to predict grinding temperature, but also enhances the understanding of cup wheel grinding processes.

Unified approach to developing analytical models of different grinding processes based on basic cutting process model

The appearance of modern CNC grinding machines allowed concentrating multipass and multistage processing of different workpiece surfaces by means of using different grinding types and different tool types. Meanwhile, the processing of different surfaces is carried out with different allowances and accuracy requirements and performed according to the specified stepwise cycles of the feeds control. As a result, there is a difficult task of quick and reliable calculation of the optimal feed cycles and other cutting modes for different types of processing of different surfaces with various grinding conditions. The solution to this problem is developing of mathematical models that link processing accuracy with cutting modes and other technological conditions of the processing. The development of such models should begin with the creation of a complex of the cutting forces` models for each grinding type. This article describes a method for deriving generalized analytical model of the cutting force for the different grinding types which is based on the functional interrelation between the intensity of the metal removal performed by the wheel and elementary volumes of metal deformable in the shear zone. The complex of the cutting forces models for different grinding types, obtained by means of using this technique, establishes functional interrelation of the cutting force with cutting modes, strength properties of the treated material, kinematics of the grinding process, geometry of the cutting zone, characteristics and geometric parameters of the grinding wheel, etc. It should also be noted that the developed models cover the majority of production conditions and they are wide-range in terms of the main technological parameters (dimensions of the treated surfaces, allowances, tolerance grades, etc.).

Building a model of the process of grinding screws for ball-screw transmission

Studies of domestic and foreign scientists show that the radius of the thread profile has a significant impact on the performance of BS transmissions: load capacity, rigidity, smoothness and durability. Therefore, the accuracy of the thread profile is high requirements. In order to ensure the high quality of transmission functioning, it is very important to obtain a minimum deviation on the entire length of the propeller of parameters such as the moment of idling, the changes of which characterize the smoothness of the work, and the rigidity on which it depends. precision of movement and installation in the required position of the machine’s working organs. Therefore, special attention is paid to ensuring the stability of the thread profile radius. For ensuring the stability of the radius of the thread profile, the article developed a mathematical model of the thread grinding process that ensures the preservation of the circle profile. It is shown that the obtained mathematical model requires experimental verification in the conditions of grinding the thread of the rolling screws and, if necessary, its corresponding refinement.

3D modeling and simulation of thermal effects during profile grinding

A new heat transfer model for profile grinding was developed to analyze distortions caused by residual tensile stresses in linear guide rails. The simulative analysis of the thermal effects caused by a non-uniform heat source on the surface using the finite element method depends on an accurate representation of the locally variable contact area. The complexity of the V-groove profile disqualifies a 2-dimensional simulation approches so far used in the literature. This paper focuses on the redefinition of these mathematical relationships of the process parameters and the resulting heat flux. The heat flux model is adapted to the geometry of the workpiece depending on the grinding parameters and approximating the V-groove of a linear guide rail. This 3-dimensional modeling allows a better understanding of the thermo-metallurgical effects that occur during the grinding process. Furthermore, the calculation of the internal stresses induced into the workpiece material through the grinding process is possible. The simulation model results in a generally valid model for the analysis of distortions. In order to confirm the validity of the new heat flux profile, a comparison of the different finite element simulation results was made and experiments under wet grinding conditions were conducted. The results show that the newly developed grinding process model allows a more accurate prediction of workpiece distortion caused by grinding forces and temperatures. This research also offers a new approach to a method based on a 2-dimensional implementation developed in the literature for predicting the distortions of linear guide rails and a derivation of possible simulation-based compensation strategies.

Modeling, planning, and control of robotic grinding on free-form surface using a force-controlled belt grinding tool

With the increasing demand for efficiency and intelligence in grinding operations, the research of the automatic robotic processing method for complex surface workpieces becomes necessary. This paper proposes a new approach for robotic grinding on the free-form surface. Particularly, the authors design a novel force-controlled belt grinding tool, on which a contact model of grinding process is further developed. In order to improve the efficiency of grinding, a rapid robot trajectory planning method is proposed based on the workpiece’s computer-aided design model, and the process parameters are identified from simple experiments. Furthermore, a piecewise parameterized force control method based on impendence control for the tool is presented, and the purpose of this method is to compensate for the error caused by the rapid planning method and low consistency workblanks. Finally, the grinding experiments of the plate workpiece and complex shape workpiece are performed. The experiment results demonstrate that the proposed method is effective.

Adaptive Hybrid Soft-Sensor Model of Grinding Process Based on Regularized Extreme Learning Machine and Least Squares Support Vector Machine Optimized by Golden Sine Harris Hawk Optimization Algorithm

Soft-sensor technology plays a vital role in tracking and monitoring the key production indicators of the grinding and classifying process. Least squares support vector machine (LSSVM), as a soft-sensor model with strong generalization ability, can be used to predict key production indicators in complex grinding processes. The traditional crossvalidation method cannot obtain the ideal structure parameters of LSSVM. In order to improve the prediction accuracy of LSSVM, a golden sine Harris Hawk optimization (GSHHO) algorithm was proposed to optimize the structure parameters of LSSVM models with linear kernel, sigmoid kernel, polynomial kernel, and radial basis kernel, and the influences of GSHHO algorithm on the prediction accuracy under these LSSVM models were studied. In order to deal with the problem that the prediction accuracy of the model decreases due to changes of industrial status, this paper adopts moving window (MW) strategy to adaptively revise the LSSVM (MW-LSSVM), which greatly improves the prediction accuracy of the LSSVM. The prediction accuracy of the regularized extreme learning machine with MW strategy (MW-RELM) is higher than that of MW-LSSVM at some moments. Based on the training errors of LSSVM and RELM within the window, this paper proposes an adaptive hybrid soft-sensing model that switches between LSSVM and RELM. Compared with the previous MW-LSSVM, MW-neural network trained with extended Kalman filter(MW-KNN), and MW-RELM, the prediction accuracy of the hybrid model is further improved. Simulation results show that the proposed hybrid adaptive soft-sensor model has good generalization ability and prediction accuracy.

On the temperature field in the creep feed grinding of turbine blade root: Simulation and experiments

Although there have been many theoretical, numerical and experimental studies focusing on grinding temperature, very few of them investigated the temperature domain when performing profile grinding of free-form surfaces, where excessive heat can be considered as the key issue due to the long and complex contact zone. In this study, the finite element (FE) based thermal model of the Creep Feed Grinding (CFG) process of Inconel 718 turbine blade root was established in terms of energy partition, material properties, geometry, and thermal boundary. The validation experiments aided with the imbedded thermocouples showed the reasonable match with the experimental results where the average difference was of about 20% proved the simulation feasibility and accuracy. The effects of the blade root profiling and root geometry on the grinding temperature were discussed based on the validated FE model. Considering the research gaps mentioned above, this work is not only expected to be meaningful to deepen the understandings of the temperature field distribution in the CFG of turbine blade root, but also helpful to provide industry guidance to optimize the process physics in precision machining of high-valued parts with complex profiles.