Cylindrical Grinding Machine Research Articles

Optimizing Cylindrical Grinding Proficiency and Surface Finish for EN24 Steel Alloy with the Use of Taguchi Analysis and Artificial Neural Network

Grinding is a material removal procedure used at the end of manufacturing to obtain high dimensional precision and a desirable surface polish. External cylindrical grinding is a type of grinding procedure that used to grind cylindrical things such as engine shafts, connecting rods, spindles, and axles. This study examines how control settings affect response parameters using EN24 alloy steel on a cylindrical grinding machine. Response parameters are material removal rate (MRR) and surface roughness (Ra), whereas control parameters are workpiece speed (v), feed rate (f), and depth of cut (d). Taguchi DOE is employed with L16 orthogonal array to optimize control parameter levels, followed by cylindrical grinding tests.An artificial neural network (ANN) model was created to validate and predict cylindrical grinding reaction parameters. To train the network, experimental data was used, and ANN predictions were compared to real data. Data collection has also completed.In the purposed work minimum Ra is 0.52 µm and maximum MRR is 0.6588 g/sec found and results indicate that feed rate and workpiece speed are the most dominating parameters of cylindrical grinding. The experimental results can be employed by various manufacturing and industrial firms and they can select suitable combinations of input parameters for desired Ra and MRR

Transforming Old to New

A machine overhaul by cylindrical grinding machine manufacturer Studer is helping to breath new life into old machines by upgrading their efficiency, performance and precision

Special Tools in Spain

The Spanish TEMSA Metallurgical Group is a leading manufacturer of special tools for cold forming. The company operates cylindrical grinding machines from Studer in its production

The continuous generating grinding method for face gears based on general cylindrical gear grinding machine

The continuous generating grinding method for face gears based on general cylindrical gear grinding machine

Method of digital automatic design of grinding operations carried out on CNC cylindrical grinding machines

Based on the literature review, the problem is formulated, which consists in the absence of detailed recommendations for the design of grinding operations for CNC cylindrical grinding machines. This paper provides a solution to the problem described above using the developed method, which includes: the formation of initial data, the formation of grinding cycles, and the calculated determination of cycle parameters.

Application of Multiple Back-Propagation ANN for Predicting Finish Surface Roughness Produced by Vereco CNC Cylindrical Grinding Machine

Large industrial operations, such as those in manufacturing, marine, and oil & gas, rely on cylindrical grinding as one of their most critical machining processes. One of the difficulties encountered throughout the cylindrical grinding process is anticipating the workpiece’s exact surface roughness after the process. Due to the process’s inability to predict the exact surface roughness, the processing time and quality produced are difficult to control. Several independent variables that are immediately quantifiable are used to build a data set for the training procedure in this study. Predicting the ultimate surface roughness generated by the cylindrical grinding process is critical for optimizing production time, quality, efficiency, and customer satisfaction. An artificial neural network with multiple backpropagation algorithms is applied. Through the learning process, the best combination of learning is obtained, namely: a learning rate of 0.057 and a momentum of 0.434 with one hidden layer in which there are 10 hidden nodes. This combination is believed to be the best training combination to produce the minimum error between the target and the true value. The root mean squared error of the test calculation was 0.0436 with a prediction accuracy of 95.64%. This set of experiment results produces predictive results through the validation process and succeeds in predicting the finish surface roughness with promising results (accuracy in the range of 94.683-97.661%).

Sustainable Grinding Performances of Nano-Sic Reinforced Al Matrix Composites under MQL: An Integrated Box–Behnken Design Coupled with Artificial Bee Colony (ABC) Algorithm

The presence of abrasive particles in ceramic reinforced composite materials makes the machining complicated by generating friction at elevated temperatures. Lubricants can be used to prohibit the hazard of higher temperatures. This research work is focused on examining the effects of lubricants on the grinding performances of Al matrix composites reinforced with nano-SiC particles under minimum quantity lubrication (MQL). A cylindrical grinding machine is used to perform the grinding experiments by employing a Box–Behnken design. Multiple performances, such as surface roughness, grinding forces and temperature, are optimized by considering the depth of cut, speed of the workpiece, wheel speed and wt % of nano-SiC using response surface methodology (RSM)-based artificial bee colony (ABC) algorithm. Atomic force microscope (AFM) and scanning electron microscopy (SEM) are used to observe the morphologies of the machined surfaces and the wheel.

Optimization of cylindrical grinding process parameters on austenitic stainless steel 304 using Taguchi based Grey Relational Analysis

A cylindrical grinding machine is used to grind and form an object's exterior and is generally used in finishing process. Though near-net shape technology is evolving, finishing processes are frequently required to achieve dimensional accuracy and a satisfactory surface quality. Cylindrical grinding machine can operate with different types of shapes, provided the workpiece should have a rotating axis at center. In this study, austenitic SS304 was selected as the material of workpiece. It is used for domestic as well as industrial applications. This research focuses on applying Taguchi technique and Grey Relational Analysis for selecting optimal cylindrical grinding process variables for austenitic stainless steel 304. The process parameters in grinding operation serve as the input factors, the combination of which greatly affects the output responses. The grinding process variables investigated in this research work are workpiece speed, longitudinal feed, transverse feed and flow rate of the coolant. The effect of these grinding factors is analyzed on the performance measures: surface roughness and material removal rate. The experimentation was done based on L9 orthogonal array generated using the Taguchi technique. Further, optimal grinding process parameters (work speed = 20 m/min, longitudinal feed = 6 m/min, transverse feed = 0.02 mm, coolant flow rate = 1.43 l/min) which satisfy both the responses (surface roughness = 0.395 µm and Material Removal Rate = 189.37 mm3/s) were predicted using Grey Relational Analysis.

Diagnosis of two-axis cylindrical grinder machining error

This paper attempts to develop a machining error diagnosis method for classifying the error sources on the external/internal contour surfaces which are fabricated using a two-axis cylindrical grinding machine. A derivation of the contour profile to grinding wheel motion trajectory and also the grinding wheel motion trajectory to the contour profile equations has been performed. Due to the contours having a sinusoidal polynomial polar curve instead of a rose curve, the grinding wheel motion trajectory equation is then used to generate the NC code for the machining. The grinding wheel motion trajectory equation is needed for the synthesis of the profile error caused by the motion error as well as the variation of the grinding wheel diameter. The two-axis motion equation is obtained by transforming the non-circular contour equation through the coordinates of the grinding wheel and workpiece. The influence of different machining parameters such as grinding wheel outer diameter error, grinding wheel feed rate, and workpiece rotation speed on the external/internal contour profile is being studied and analyzed. The diagnosis method is based on the least square method to assemble the components of the profile error due to each individual error sources. The actual machining with probe system is used to verify the diagnosis result.

STUDY OF THE INFLUENCE OF THE WORKING LIQUID TEMPERATURE IN THE SPINDLE BEARINGS OF A CYLINDRICAL GRINDING MACHINE ON THE ERRORS OF ITS POSITION RELATIVE TO THE PART BEING MACHINED

The article presents the results of measurements of the ambient temperature around the working cylindrical grinding machines during the working day. The analysis of the behavior of the grinding head spindle of different cylindrical grinding machines during the work shift is performed, namely the results of experimental studies of the displacement of the front and rear ends of the grinding head spindle of cylindrical grinding machines are presented. The analysis of influence of temperature of working fluids in spindle bearings on its displacement is carried out. Possible changes in the geometric shape, namely, conicity, of parts machined on cylindrical grinding machines have been established.

Research on geometric error modeling and compensation method of CNC precision cylindrical grinding machine based on differential motion theory and Jacobian matrix

Research on geometric error modeling and compensation method of CNC precision cylindrical grinding machine based on differential motion theory and Jacobian matrix

Precise purchases for high performance

Ondrives adds a second Studer cylindrical grinding machine to meet demand; Marlor invests in a Rollomatic Shapesmart as it moves into the medical sector; Danish tool manufacturer puts trust in Vollmer; plus, news and products briefs

Cylindrical grinding - experimental investigation and Taguchi study of process parameters on EN31 and mild steel

Cylindrical grinding, a secondary machining operation, a finishing operation in the manufacturing industry across the world. The volume of removed material over a given time (MRR) and quality of the surface (Roughness) obtained are the two important characteristics that investigated by researchers with respect to output responses from the process in understanding product quantity and quality. These two output parameters, any machining operation, are primarily important in consumer perspective vis-à-vis manufacturer. In this investigation, experiments are conducted and analyzed to arrive at the optimal grinding conditions/parameters in cylindrical grinding. The outcome of the machining will have a good surface quality by removing maximum material; confirming ovality and cylindricity of the specimen made from EN31 and Mild Steel. Taguchi DOE recommendations are considered in investigating the influence of input process parameters i.e. speed, feed, and depth of cut on machining outcome. Regression module in Minitab is used to apply a linear fit which is a general/simple recommendation for the parameters in order to understand the influence of these parameters on the expected outcome i.e., the maximum volume of material removed and to achieve a better surface finish with a minimum value of deviations in ovality (circularity) and cylindricity of the machined component by conducting experiments on a general-purpose cylindrical grinding machine.

Experimental Investigation on the Wear and Damage Behaviors of Machined Wheel-Rail Materials under Dry Sliding Conditions.

Rail grinding and wheel turning can effectively remove surface defects and unevenness, which is a crucial process for the safe and smooth operation of trains. Machined surface integrity of wheel/rail materials significantly influences their tribological property. In this study, firstly, the rail blocks were ground via a cylindrical grinding machine, and the wheel rings were turned by a computer numerical control (CNC) lathe with varied parameters. Then, the sliding wear and damage characteristics of the machined wheel/rail samples under dry conditions were studied by virtue of a block-on-ring tribometer. The results show that the surface microhardness of the ground rail blocks is larger than that of wheel rings, while the surface roughness and the thickness of the subsurface plastic deformation layer (SPDL) of rail blocks are much smaller than those of wheel rings. After sliding, the surface microhardness of wheel/rail samples increases remarkably. The thickness of the SPDL, the wear loss, and the increase degree of surface microhardness of rail blocks are larger than those of wheel rings. Surface microhardness, roughness and the SPDL of the machined wheel/rail samples impose a combined influence on the anti-wear property, and the tribological pair with proper initial surface roughness and microhardness engenders the smallest amount of total wear loss.

Investigations on producing optimal grinding spindle using 36CrNiMo4 alloy steel

This exploration expects to fabricate the optimum grinding spindle utilizing toughened 36CrNiMo4 steel through the grinding route. First and foremost the 36CrNiMo4 steel items are made according to the creative design and exposed to coarse turning. Then the steel items are exposed to heat treatment procedures to improve the mechanical property hardness with the goal that the steel items become wear-safe. The exploratory runs are intended to rely upon Taguchi's L9(34) exhibit and led in a cylindrical grinding machine. The surface unevenness of the machined examples is estimated utilizing an adjusted surface unevenness analyzer. An expectation model is made through a relapse investigation for the result. The centrality of the chose grinding factors and their levels on surface unevenness is found by the response table. The ideal arrangement of machining factors was recognized by Taguchi technique. The ground surface of the steel item has been examined through a Scanning Electron Microscope (SEM) to study its surface integrity.

Experimental Investigation on the Wear and Damage Characteristics of Machined Wheel/Rail Materials under Dry Rolling-Sliding Condition

To guarantee the smooth operation of trains, rail grinding and wheel turning are necessary practices to remove surface defects. Surface integrity of machined wheel/rail materials is significant to affect their tribological performance. In this paper, firstly, the wheel specimens were turned by a CNC lathe and the rail specimens were ground by a cylindrical grinding machine with various machining parameters. Then, the wear and damage behavior of the machined wheel/rail discs was systematically investigated via a twin-disc wear testing apparatus under dry rolling-sliding condition. The experimental results show that the surface hardness of rail discs after machining is slightly higher than that of wheel discs, while the surface roughness and plastic deformation layer of wheel discs are much larger than those of rail discs. The surface hardness increase degree of rail discs and their thickness of plastic deformation layer are greater than those of wheel discs after the rolling-sliding test. The wear loss of wheel discs is much larger than that of rail discs. Surface roughness, hardness and plastic deformation layer of wheel/rail discs after machining exert a comprehensive effect on the wear behavior, and friction pair with appropriate original surface hardness and roughness generates the smallest amount of wear loss.

Volumetric error analysis and modelling of CNC internal and external cylindrical grinding machine tool

In order to improve grinding accuracy, it is necessary to analyze and study geometric and thermal errors of NC machine tools. Based on the method of coordinate transformation of multi-body system theory, the error matrix of cutting points is established in workpiece and tool kinematic chains. The coupling relationship between thermal error and geometric error is analyzed, and the comprehensive mathematical model of geometric error and thermal error of CNC internal and external grinder is deduced. The precise machining constraint equation of grinder is established, which lays a theoretical foundation for subsequent error compensation.

Geometric Error Modeling and Sensitivity Analysis of CNC Internal Circular Compound Grinding Machine

In order to improve the machining accuracy and efficiency of the hole and sleeve parts, it is necessary to improve the overall grinding accuracy of the CNC (Computer Numerical Control) internal cylindrical compound grinding machine more accurately and efficiently. First of all, it is necessary to clarify the degree of influence of each error parameter on the grinding accuracy, and compensate each error according to the different degree of influence. In this paper, modeling calculation analysis is carried out for a certain type of CNC internal cylindrical compound grinding machine. Firstly, based on the theory of multi-body system dynamics, the topological structure of the CNC internal cylindrical compound grinder is established. According to the topological structure, the position, motion matrix and error matrix of the moving parts of the grinder are written. After data processing, the numerical control internal cylindrical compound grinder is calculated. Use this model to derivate each error parameter to obtain the sensitivity expression of each error parameter. After the actual structure parameters of the grinder are brought into the expression, the sensitivity coefficient of each error parameter can be determined by normalization treatment. The key error parameter with larger sensitivity coefficient is the key error parameter. Finally, several error parameters which have the greatest impact on the overall grinding accuracy of the grinder are obtained. This method provides the basis for the improvement of the grinding accuracy of the subsequent grinder, and creates conditions for the improvement of the machining accuracy of sleeve parts.

In-process characterization of surface finish in cylindrical grinding process using vibration and power signals

Grinding being a finishing process, the quality of the ground surface is one of the most important performance evaluation parameters. Grinding process being highly stochastic in nature, surface finish is affected by many factors and experimental evaluation of each factor is a tedious task. In this study, the in-process signals collected using various sensors attached to a cylindrical grinding machine such as Accelerometer and Power are processed, and their features are correlated with a surface finish parameter. This correlation is modelled using gradient boosting algorithm and surface finish obtained is predicted and validated on an industrial application.

Producing Optimum Quality Grinding Spindle Using Hardened AISI 4340 Steel through a Cylindrical Grinding Process

The intent of this study is to produce optimum quality grinding spindle using hardened AISI 4340 steel through the cylindrical grinding process. Primarily the AISI 4340 steel specimens are cut according to the product specification and subjected to rough machining. Then the steel specimens are subjected to a heat-treatment process to enhance the mechanical property hardness so that the specimen becomes wear-resistant. The experimental runs are planned depending on Taguchi’s L27(37) array and conducted in a cylindrical grinding machine (Toyoda G32 cylindrical grinding machine). The surface roughness of the machined specimens is measured using a calibrated surface roughness tester. A prediction model is created through regression analysis for the outcome. The significance of the selected grinding factors and their levels on surface roughness is found by analysis of variance (ANOVA) and F-test and finally. An affirmation test is directed to produce the ideal components.