Grinding Process Parameters Research Articles

Evaluation of surface topography of SiCp/Al composite in grinding

As the main processing technique of SiCp/Al composite, grinding directly affects usability performance. However, cavity defects usually occur during the SiCp/Al grinding process. In this study, the surface micro-topography of SiCp/Al composite in grinding was observed by means of SEM, and the chemical ingredients over the cavity defect surface were analyzed by energy dispersive spectrometry. The surface topography was reconstructed with bilinear interpolation algorithm by a point cloud, and the contour map including cavity defects was obtained. Based on the contour map including cavity defects, a new relationship curve between the projection area ratio and contour height was proposed. A novel comprehensive evaluation system was established and included four aspects, namely the profile height and surface roughness of the entire topography, profile height, and equivalent surface roughness of the cavity defect. The optimized algorithm was proposed with the objective function of maximum grinding efficiency and constraints of profile height and surface roughness. The optimized grinding process parameters were obtained and verification experiments were carried out. The results demonstrated that the predicted results were consistent with the experimental results, and the comprehensive evaluation system including cavity defects can reflect the surface topography intuitively. The comprehensive evaluation system for the surface topography including cavity defects in grinding provides guidance for the usability performance of SiCp/Al composite.

Evaluation of the influence of the parameters of the flat grinding process on the dynamic characteristics of the spindle unit

Evaluation of the influence of the parameters of the flat grinding process on the dynamic characteristics of the spindle unit

Multi-objective Optimization of Dressing Parameters of Internal Cylindrical Grinding for 9CrSi Aloy Steel Using Taguchi Method and Grey Relational Analysis

Abstract This study has been done to optimize the dressing parameters in internal cylindrical grinding process for 9CrSi tool steel to minimize surface roughness and maximize material removal rate (MRR) using Taguchi method and Grey Relational Analysis (GRA). This multi-objective optimization is obtained by optimizing five three-level and one six-level dressing parameters in eightteen experiments based on an orthogonal array L18(35×16). The results show that the optimal dressing parameters to obtain the minimal roughness average and maximal MRR are the coarse dressing depth of 0.02 mm, the coarse dressing times of 1 time, the fine dressing depth of 0.005 mm, the fine dressing times of 3 times, the non-feeding dressing of 5 times and the dressing feed rate of 1.4 m/min, respectively. The differences of the roughness average and MRR from the experiments and the predict model are small. Thus, the proposed method has been proven and it can be further applied in other studies.

An optimization of exchanged grinding wheel diameter when surface grinding alloy tool steel 9CrSi

Abstract This paper presents an optimization of exchanged grinding wheel diameter for surface grinding alloy tool steel 9CrSi based on the cost analysis for surface grinding. The optimum exchanged grinding wheel diameter was determined by minimizing the cost function. An experiment design was set up, and a computational program was built to perform the experiment in order to calculate the optimum exchanged grinding wheel diameter. The influence of grinding process parameters such as the initial grinding wheel diameter, the total dressing depth, and the radial grinding wheel wear per dress and the wheel life on the optimum exchanged grinding wheel diameter was investigated. In addition, the effect of the cost components such as the machine tool hourly rate and the grinding wheel cost on the optimum diameter of exchanged grinding wheel was also given. From the results, an explicit equation was obtained to determine the optimum exchanged grinding wheel diameter. The calculation value of the optimum exchanged grinding wheel diameter from the formula was also verified by the experiment.

A Study On Calculation Of Optimum Exchanged Grinding Wheel Diameter When Internal Grinding

Abstract This paper presents a study on optimum calculation of the exchanged diameter of grinding wheels in internal grinding of stainless steel. In this study, the effects of the grinding process parameters including the initial diameter, the total depth of dressing cut, the wheel life, the radial grinding wheel wear per dress and the ratio between the length and the diameter of the workpieces on the exchanged grinding wheel diameter were explored. The influences of cost factors including the machine tool hourly rate and the grinding wheel cost were also investigated. To evaluate the effects of these parameters on the optimum exchanged grinding wheel diameter, a simulation experiment was created and performed by and a computer program. A proposed model to determine the optimum exchanged grinding wheel diameter was given based on the results of the study.

Effect of grinding depth on surface topography by considering vibrations and a force prediction model

Little consideration has been given to vibrations when the effect of grinding process parameters on the surface morphology is studied. Taking a grinding force as the intermediate variable, influences of grinding depths on the surface topography are investigated with considering vibrations in this paper. Firstly, a novel grinding force prediction model is proposed through amending the Malkin model by integrating with contact arc length and abrasive grain contact angle. Secondly, vibrations of the feed platform and the grinding wheel shaft are analysed. Vibration displacement in the x-direction of wheel axis remains substantially between 140-150 nm, while in the y-direction, it increases with the grinding depth. Finally, three-dimensional surface topographies with different grinding depths are investigated. It is observed that the pronounced defects and a coarse texture are generated as the grinding depth increases. Parameters like Sa, Sq, Sku, Ssk are more suitable to represent the real grinding quality of workpiece surface.

Effect of grinding depth on surface topography by considering vibrations and a force prediction model

Little consideration has been given to vibrations when the effect of grinding process parameters on the surface morphology is studied. Taking a grinding force as the intermediate variable, influences of grinding depths on the surface topography are investigated with considering vibrations in this paper. Firstly, a novel grinding force prediction model is proposed through amending the Malkin model by integrating with contact arc length and abrasive grain contact angle. Secondly, vibrations of the feed platform and the grinding wheel shaft are analysed. Vibration displacement in the x-direction of wheel axis remains substantially between 140-150 nm, while in the y-direction, it increases with the grinding depth. Finally, three-dimensional surface topographies with different grinding depths are investigated. It is observed that the pronounced defects and a coarse texture are generated as the grinding depth increases. Parameters like Sa, Sq, Sku, Ssk are more suitable to represent the real grinding quality of workpiece surface.

Determination of optimum exchanged grinding wheel diameter when external grinding stainless steels

Abstract This paper introduces a study on optimum determination of exchanged grinding wheel diameter when external grinding of stainless steel. In this study, the influences of grinding process parameters including the initial grinding wheel diameter, the total dressing depth, the radial grinding wheel wear per dress and the wheel life on the exchanged grinding wheel diameter were investigated. Also, the effect of cost parameters including the grinding wheel cost and the machine tool hourly rate were investigated. To estimate the influence of these parameters on the optimum exchanged grinding wheel diameter, a simulation experiment was designed and it was performed by a computer program. Based on the results of the experiment, a formula for calculation of the optimum exchanged diameter was introduced

Shark-Skin-Inspired Micro-Riblets Forming Mechanism of TC17 Titanium Alloy With Belt Grinding

Belt grinding could improve the surface integrity of titanium alloys, but it is difficult to achieve breakthroughs in the grinding mechanism due to the lack of grinding mechanism of titanium alloy microriblets structure. The characteristics of micro-riblets structure are discussed, and the belt grinding method for the micro-riblets is proposed based on the structural features. On this basis, the corresponding relationship model between the belt grinding and the surface parameters of the micro-riblets structure is established. The standard experimental platform was built and the belt grinding experiment was completed. The typical structural characteristics based on the method were obtained. The influence of the belt grinding process parameters on the formation of micro-riblets structures was analyzed. The results show that the micro-riblets structure achieved by the belt grinding method is dominated by sawtooth riblets. The width of the trench (s) is between 2.5μm and 8μm, the average value is 4.91μm, the height of the trench (h) is between 3.5μm and 9μm, the average value is 5.91μm, and the angle of the trench (α) is between 28° and 68°, the average is 42.3°. At the same time, it can be seen that increasing the grinding positive pressure (Fn), the feed step (P), and reducing the grinding feed rate (v <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ) can increase the sawtooth riblets width (s), the groove height (h), and the trench angle (α) of the micro-riblets structure surface. It can also increase the surface of the micro-riblets structure surface sawtooth riblets b <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , b <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . Moreover, the groove ratio h/s and the groove bearing side length ratiob <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> /b <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> have a sinusoidal fluctuation tendency, and the ratio mainly jumps up and down at a fixed value.

Prediction of specific grinding forces and surface roughness in machining of AL6061-T6 alloy using ANFIS technique

PurposeOptimisation of grinding processes involves enhancing the surface quality and reducing the cost of manufacturing through reduction of power consumptions. Recent research works have indicated the minimum quantity lubrication (MQL) system is used to achieve near dry machining of alloys and hard materials. This study aims to provide an experimental analysis of the grinding process during machining of aluminium alloy (Al6061-T6). MQL nanofluid was used as the lubricant for the grinding operations. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality was studied. Adaptive neuro-fuzzy inference system (ANFIS) prediction modelling was used to predict the specific normal force, specific tangential force and surface quality, the ANFIS models were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further study shows that both the specific grinding forces and surface roughness are inversely proportional to the nanofluid concentration. Also, the depth of cut and table feed rate were found to have a directly proportional relationship with both the grinding forces and surface roughness. Moreover, higher MQL air pressure was found to offer better delivery of the atomised nanofluid into the grinding region.Design/methodology/approachGrinding experiments were performed using MQL nanofluid as the lubricant. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality has been studied.FindingsThe grinding process parameters were optimised using Taguchi S/N ratio analysis, whereas the prediction of the response parameters was done using ANFIS modelling technique. The developed ANFIS models for predicting the specific normal force, specific tangential force and surface quality were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further findings show that both the specific grinding forces and surface roughness are inversely proportional to the percentage of nanoparticle concentration in the lubricant. Also, the depth of cut and table feed rate were found to exhibit a direct proportional relationship with both the grinding forces and surface roughness, while high MQL air pressure was observed to offer more efficient delivery of the atomised nanofluid into the grinding region.Practical implicationsThe work can applied into manufacturing industries to prevent unnecessary trials and material wastages.Originality/valueThe purpose of this study is to develop an artificial intelligent model for predicting the outcomes of MQL grinding of the aluminium alloy material using ANFIS modelling technique.

An Investigation of Surface Corrosion Behavior of Inconel 718 after Robotic Belt Grinding.

Surface corrosion resistance of nickel-based superalloys after grinding is an important consideration to ensure the service performance. In this work, robotic belt grinding is adopted because it offers controllable material processing by dynamically controlling process parameters and tool-workpiece contact state. Surface corrosion behavior of Inconel 718 after robotic belt grinding was investigated by electrochemical testing in 3.5 wt % NaCl solution at room temperature. Specimens were characterized by morphology, surface roughness and residual stress systematically. The potentiodynamic polarization curves and electrochemical impedance spectroscopy (EIS) analysis indicate the corrosion resistance of the specimen surface improves remarkably with the decrease of abrasive particle size. It can be attributed to the change of surface roughness and residual stress. The energy dispersive X-ray spectroscopy (EDS) indicates that niobium (Nb) is preferentially attacked in the corrosion process. A plausible electrochemical dissolution behavior for Inconel 718 processed by robotic belt grinding is proposed. This study is of significance for achieving desired corrosion property of work surface by optimizing grinding process parameters.

Estimation of CNC Grinding Process Parameters Using Different Neural Networks

Continuation of research on solving the problem of estimation of CNC grinding process parameters of multi-layer ceramics is presented in the paper. Heuristic analysis of the process was used to define the attributes of influence on the grinding process and the research model was set. For the problem of prediction - estimation of the grinding process parameters the following networks were used in experimental work: Modular Neural Network (MNN), Radial Basis Function Neural Network (RBFNN), General Regression Neural Network (GRNN) and Self-Organizing Map Neural Network (SOMNN). The experimental work, based on real data from the technological process was performed for the purpose of training and testing various architectures and algorithms of neural networks. In the architectures design process different rules of learning and transfer functions and other attributes were used. RMS error was used as a criterion for value evaluation and comparison of the realised neural networks and was compared with previous results obtained by Back-Propagation Neural Network (BPNN). In the validation phase the best results were obtained by Back-Propagation Neural Network (RMSE 12, 43 %), Radial Basis Function Neural Network (RMSE 13, 24 %, ), Self-Organizing Map Neural Network (RMSE 13, 38 %) and Modular Neural Network (RMSE 14, 45 %). General Regression Neural Network (RMSE 21, 78 %) gave the worst results.

Realization of high efficiency and low damage machining of anisotropic KDP crystal by grinding

Potassium dihydrogen phosphate (KDP) is a non-linear material used in various opto-electronic applications including Q-switches, high-speed photography shutters, frequency harmonic generation lens and Pockels cells in the Inertial Confinement Fusion (ICF) devices. KDP belongs to the most difficult-to-cut material, due to its delicate and unique characteristics including the combination of softness with brittleness, anisotropic performances, tendency for deliquescence and sensitivity to temperature change. Single point diamond turning (SPDT) is considered to be the ideal method for machining KDP components. However, the process efficiency is rather low and often accompanied with severe tool wear issues. This paper studies the feasibility using grinding method to remove the surface material of KDP components with high process efficiency and low damage, fulfilling the task of re-aligning the surface orientation to the crystalline axis. The grinding tests were carried out on a common CNC grinder, using resin bonded diamond grinding wheel, whilst the diamond abrasives are coated with Ni-P alloy. The direction of precision grinding was determined by studying the anisotropy of KDP, including its elastic modulus E, Vickers hardness HV and fracture toughness KIC, to reduce the influence of material anisotropy on machining quality. The grinding process parameters were preliminarily determined based on the experimental results investigating the effects of peripheral speed of the grinding wheel, worktable feed rate and grinding depth on the ground surface roughness. The surface defects, surface morphology and sub-surface damage under different process parameters were investigated. Surface roughness Ra ≤ 0.3 μm and sub-surface damage depth SSD ≤ 6 μm were obtained. The machining efficiency can be improved by nearly ten times using the proposed precision grinding method, producing nearly the same surface quality (Ra ≤ 0.2 μm, SSD ≤ 6 μm) as that in the axis fixing phase in SPDT.

Silicon Carbide Surface Quality Prediction Based on Artificial Intelligence Methods on Multi-sensor Fusion Detection Test Platform

On the basis of the grinding process experiments for SiC ceramic workpiece, grinding process parameters are measured on the multi-sensor fusion detection test platform and experimental results are analyzed. Lempel–Ziv complexity (LZC) is introduced to reflect the integrated grinding process stability due to kinds of factors such as vibration from grinding machine parts and noise from experimental platform. The greater the LZC is, the fewer period factors are in the grinding process, which reflect the nonlinear correlations in the grinding process impacting on grinding process. A method is given based on LZC for analyzing grinding process stability. Under consideration of experimental results, a predictive model for surface quality is given by the Kernel Principle Component Analysis and Modified Extreme learning machine method (KPCA-MELM), and grinding process parameters can be optimized too. KPCA-MELM predictive model overcomes disadvantages of MELM predictive model of the randomness of weight ω and threshold value b by introducing improved genetic algorithm, which makes the roughness predictive error more accurate with the maximum error of 4.803%.

Fractal roughness effects on nanoscale grinding

Three-dimensional Molecular Dynamics simulations have been performed to investigate the effects of fractal roughness on nanoscale grinding. The first part of this investigation focuses on the effects of the workpiece rough top surface on the grinding process characteristics, with special emphasis placed on the friction coefficient, the grinding forces and the subsurface temperature. The second part focuses on the alternation of the aforementioned parameters due to the rough abrasive contact surface. Rough surface profiles have been generated using the multivariate Weierstrass-Mandelbrot function while the abrasive has been modelled as a trapezoid. The irregular surface topography has been controlled by tuning the value of the fractal dimension Ds. The aforementioned experiments have been repeated for various values of the cutting depth. Our results indicate that the grinding process parameters are mainly dependent on the cutting depth as well as the abrasive lower surface profile, which also defines the interface contact area between the workpiece and the abrasive, rather than the topography of the workpiece top surface.

A Novel Method of Twist Drill Fluting Fulfilling Required Web Thickness and Rake Angle

As substitute of the meshing theory based fluting method, other analytical, machining movement simulation or empirical method are developed in last decades. Currently, a kind of flute prevails. It is ground by using 1V1/1A1 standard grinding wheel and should fulfil requirements of designated web thickness and radial rake angle. This paper presents a novel method by straightforwardly determining install position of the grinding wheel. Based on the relative movement with variables’ parameterization, equations to keep web thickness are firstly derived. Then, a family of flute cross-sectional curves is computed automatically with respect to grinding process parameters and wheel geometry. The calculation process is characterized by concise in principle and easy to use. Its validity is verified by good agreement between the results computed and manufactured example.

Determination of Optimal Exchanged Grinding Wheel Diameter when Internally Grinding Alloy Tool Steel 9CrSi

This paper introduces a study on optimal determination of exchanged grinding wheel diameter in internal grinding. In the study, the influences of grinding process parameters including the wheel life, the total dressing depth, the radial grinding wheel wear per dress and the initial grinding wheel diameter on the exchanged grinding wheel diameter were investigated. In addition, the influence of cost components including the machine tool hourly rate and the grinding wheel cost were taken into account. For evaluating the effects of these factors on the optimal exchanged grinding wheel diameter, an “experiment” was designed and a computer program was built for performing the “experiment”. Based on the results of the experiment, a model for calculating the optimal exchanged grinding wheel diameter was proposed

Development of a hybrid particle swarm optimization algorithm for multi-pass roller grinding process optimization

In the field of metal rolling, the quality of steel roller’s surface is significant for the final rolling products, e.g., metal sheets or foils. The surface roughness of steel rollers must fall into a stringent range to guarantee the proper rolling force between the sheet and the roller. To achieve the surface roughness requirement, multiple grinding passes have to be implemented. The current process parameter design for multi-pass roller grinding mainly relies on the knowledge of the experienced engineers. This always requires time tedious “trial and error” and is insufficient to work out cases: (1) multi-pass with complex interaction for one pass with its neighboring passes; (2) large number of process parameters setup; (3) multiple process objectives and constrains. In this paper, a process planning method for multi-objective optimization is proposed with a hybrid particle swarm optimization while incorporating the response surface model of the surface roughness evolution. The hybrid particle swarm optimization regards the entire grinding process parameters (from rough grinding, semi-finish grinding, finish grinding to spark-out grinding) as a whole, and realizes the parameter optimization by considering multiple objectives and constrains. The establishment of the response surface model of surface roughness evolution is capable to incorporate the inter-correlation of neighboring passes into the multi-pass parameter optimization. Finally, the experimental verification was implemented to verify the effectiveness of the proposed method. The error between predicted roughness and experimental roughness is less than 16.53%, and the grinding efficiency is improved by 17.00% compared with the empirical optimal process parameters.

Numerical simulation and experimental analysis of temperature field of gear form grinding

Gear form grinding is a method for precision machining of gears. However, the instantaneous high temperature generated in the grinding zone always cause tooth surface burn due to incorrect processing parameter selection. To optimize the grinding process parameters and prevent tooth surface burn, mathematical model of generation and conduction of heat in the process of gear form grinding is proposed in this paper. The heat distribution ratio and convective cooling coefficient of the grinding process are calculated by theoretical analysis. The finite element simulation software is developed to simulate the distribution of temperature field of grinding zone and get the change of tooth surface temperature generated in grinding process. Form grinding and metallographic analysis test are performed, which verifies the validity and feasibility of the theoretical arithmetic and simulation analyses proposed.

Investigations of surface layer temperature and morphology of hard machinable materials used in aircraft industry during abrasive electrodischarge grinding process

AbstractIn this work the results related to the influence of selected electrical parameters of the abrasive electrodischarge grinding process on the surface layer temperature and morphology of machined samples in comparison to the conventional grinding method are presented. The basis of this work has been investigations of the deep grinding of surfaces of the samples made of titanium 5553 β, Inconel 617, Hastelloy X and magnesium AZ31 using a cubic boron nitride (CBN) grinding wheel with metallic binding agent. For the comparative evaluation of the conventional grinding and abrasive electrodischarge grinding, measurements of the specific grinding energy, temperature on the surface layer (at the contact of the grinding wheel‐workpiece) and geometric structure of the surface layer have been used.