Optimization of Grinding Parameters for Minimum Surface Roughness by Taguchi Parametric Optimization Technique International Journal of Mechanical and Industrial Engineering (IJMIE), ISSN No. 2231 –6477, Volume-1, Issue-3, 2012 75 and wear resistance in comparison of low carbon steels.
03.05.2001· Output parameters namely wheel parameters, grinding time, G -ratio are computed by employing the trial infeed value. The infeed value is modified by the program in the immediate vicinity of the first trial infeed value both by increasing and decreasing in small steps of 0.0025 mm. Theses values are ±0.0025, +.0050, +.0075 mm.
The main objective of using Response surface methodology (RSM) on surface grinding operation of EN19 steel is to find optimum machining parameters which leads to minimize surface roughness and maximum metal removal rate. For conducting the experiment EN19 material was chosen due to various applications in automobile and mechanical components.
Surface finish depends on many factors such as grinding and dressing parameters. This paper presents an optimization of grinding parameters when grinding tablet by CBN grinding wheel on CNC milling...
Methodology (RSM) were used to optimize the parameters for minimum surface roughness. Minimum surface roughness indicates good surface finish. Confirmation experiments were conducted to verify the effectiveness of optimization. Optimization of Surface Grinding Process Parameters By Taguchi Method And Response Surface Methodology 1721
optimization of cylindrical grinding process parameters using taguchi method and regression analysis", International Journal of Engineering Science and T echnology, vol. 3, pp.
In the present study, Taguchi method or Design of experiments has been used to optimize the effect of cylindrical grinding parameters such as wheel speed (rpm), work speed, feed (mm/min.), depth of cut and cutting fluid on the Material Removal Rate of EN15AM steel.
In this paper, the grey relational analysis is applied to optimize the stainless steel cylindrical grinding parameters, and the corresponding grinding parameters are considered, such as spindle speed, feedrate, radial depth of grinding and workpiece speed.
Our aim in this project is to make Mathematical Modeling and Optimization of Grinding Parameters for Minimum Surface Roughness and Maximum MRR. C. Methodology For present study, efforts were made to find experiment values of parameters on grinding machine and they were measured on the basis of minimum surface roughness (Ra) for EN19 cylindrical bar. For this experimentation, parameters were
Grinding wheel speed, depth of cut, table feed, grinding wheel material and table travel speed for surface grinding operation, and work speed for cylindrical grinding operation were taken as the input parameters with four types of grinding wheels (Al 2 O 3 of grades K and L, and white alumina of grades J and K). The surface roughness was taken as an output parameter for experimentation. The
Moreover, the impact curves of the grinding parameters on the grinding indicators-the grinding efficiency, grinding wheel life, and surface roughness-were obtained by the multiple linear regression method. Finally, the multi-objective optimization method was used to comprehensively optimize the grinding process. (3) Compared with the traditional grinding process, under optimized grinding
Knowing key parameters that identify the effective lifetime of grinding media is significant to the casting industry. Methods described in this paper can be used to optimize grinding media life and determine optimum operating parameters.
This paper aims to investigate the effect of process parameters on the surface roughness in suface grinding 90CrSi tool steel. In this paper, many process parameters including the coolant concentration, the coolant flow, the cross feed, the table speed and the depth of cut were taken into account. Based on conducting and analysing 25 experiments which were created by using full factorial
OPTIMIZATION OF CYLINDRICAL GRINDING PARAMETERS OF AUSTENITIC STAINLESS STEEL RODS (AISI 316) BY TAGUCHI METHOD K Mekala1*, J Chandradas2, K Chandrasekaran2, T T M Kannan3, E Ramesh3 and R Narasing Babu4 *Corresponding Author: K Mekala, [email protected] Recently Austenitic stainless steel AISI-316 finding many applications like Automotive, Aerospace,
In order to achieve the precision and efficient processing of nanocomposite ceramics, the ultrasound-aided electrolytic in process dressing method was proposed. But how to realize grinding parameter optimization, that is, the maximum processing efficiency, on the premise of the assurance of best workpiece quality is a problem that needs to be solved urgently.
Cylindrical grinding process parameters optimization of Al. Table 9.Response table for S/N ratio of grinding temperature (V c ).The increase in the wheel velocity and workpiece velocity leads to the thermal softening of the aluminium matrix, which in turn, reduces the tangential grinding force [2]. The increase in the wheel velocity also reduces the maximum chip thick-ness, which results in a
OPTIMIZATION OF CYLINDRICAL GRINDING PROCESS PARAMETERS FOR AISI 1040 STEEL USING TAGUCHI METHOD Kirankumar Ramakantrao Jagtap Assistant Professor Mechanical Engineering Department MGM’s Jawaharlal Nehru Engineering College, Aurangabad, Maharashtra, India E-Mail ID: [email protected] S.B.Ubale Associate Professor Mechanical Engineering
The pulp density is an important parameter which influences the grinding efficiency. In iron ore, for instance, a variation of 2 to 3% solid content in the slurry could lead to a difference up to 10% on the energy (kWh/T) for a similar grind. Optimization of mill performance by using online ball and pulp measurements J o u r n a l P a p e r The Journal of The Southern African Institute of
01.10.2019· Optimal grinding parameters are also achieved by using models developed to maximize material removal by using tool life, surface roughness, and microstructure analysis. As a result, it is understood that the grinding ability of the tolls should be related to the degree of elastic failure energy of the bond, since wear is proportional to the energy of the unit volume. 6. Conclusion. In this
Moreover, the impact curves of the grinding parameters on the grinding indicators-the grinding efficiency, grinding wheel life, and surface roughness-were obtained by the multiple linear regression method. Finally, the multi-objective optimization method was used to comprehensively optimize the grinding process. (3) Compared with the traditional grinding process, under optimized grinding
This paper presents an optimization of grinding parameters when grinding tablet by CBN grinding wheel on CNC milling machine in order to minimize surface roughness. The experiment was conducted
In order to achieve the precision and efficient processing of nanocomposite ceramics, the ultrasound-aided electrolytic in process dressing method was proposed. But how to realize grinding parameter optimization, that is, the maximum processing efficiency, on the premise of the assurance of best workpiece quality is a problem that needs to be solved urgently.
Optimization of surface grinding process parameter for AISI 321 by Using Taguchi Method Avinash S. Jejurkar1,but the main grinding parameters affecting the performance of grinding operations can also be found. Experimental results are provided to confirm the effectiveness of this approach. The results of this study showed that the depth of cut and the wheel speed have significant effects
grinding parameters on minimum quantity lubrication (MQL) and they compared the results with dry lubri-cation. He proposed that an engineering optimization of a process or product should be carried out with a three-step approach: i. system design, ii. parameter design, and iii. tolerance design10,11. Materiali in tehnologije / Materials and technology 47 (2013) 1, 105–109 105 UDK 621.923
Aiming to optimize these grinding-process parameters, we propose a grey target decision-making method based on the uniform effect measure to realize the intelligent optimization of process parameters. First, we obtain the experimental data of process parameters and evaluation parameters using the orthogonal experimental method, and then we calculate and analyze the degree of relation
When the details of a specific grinding task—workpiece material, type of grinding wheel, dimensional tolerances, surface finish requirements and so forth—are loaded into the model, the system will determine the machine settings, wheel speed, depth of cut, dressing frequency and other parameters required to optimize the operation.
Generally, the accuracy of flute parameters is determined by the computer numerical control (CNC) grinding machine through setting the wheel’s location and orientation. In this work, a novel algorithm was proposed to optimize the wheel’s location and orientation for the flute-grinding to achieve higher accuracy and efficiency. Based on the geometrical constraint that the grinding wheel
A Cycle in the Process of Optimization. In a recent unusual case the manufacturer agreed to do “in situ” optimization of the grinding process. Initially the grinding cycle was changed to make it more “wheel friendly” as discussed above. In this case the friendlier cycle was also ~5 sec shorter than the initial cycle.
M. Aravind, Dr. S. Periyasamy (2014) states that, the surface grinding process parameters can be optimized by using Taguchi method and Response Surface Methodology (RSM). The process parameters considered in this study are grinding wheel abrasive grain size, depth of cut and feed. An AISI 1035 steel square rod of 100 mm x 10
internal grinding of C40E steel was executed for the optimization of output parameters with respect to change of input parameters. The cutting force, cutting speed and depth of cut were chosen as input parameters for this experimental work and output was optimized using Taguchi technique.
In this paper a new evolutionary computation technique, particle swarm optimization, is developed to optimize the grinding process parameters such as wheel speed, workpiece speed, depth of dressing, and lead of dressing, simultaneously subjected to a comprehensive set of process constraints, with an objective of minimizing the production cost and maximizing the production rate per workpiece, besides
This thesis entitled Optimization of Grinding Parameter when grind Haynes 242 using water based Titanium Oxide (TiO2) Nanocoolant. The objective of this thesis is to find optimum parameter which is the Depth of cut. The thesis also is to investigate type of surface roughness and wheel wear produced during grinding process.
A Cycle in the Process of Optimization. In a recent unusual case the manufacturer agreed to do “in situ” optimization of the grinding process. Initially the grinding cycle was changed to make it more “wheel friendly” as discussed above. In this case the friendlier cycle was also ~5 sec shorter than the initial cycle.
Some researchers investigated the effects of grinding parameters on AISI 4340 steel grinding using conventional lubrication and MQL. They found that the surface roughness, diametric wear, grinding forces and residual stress improved when using the latter, due to optimum lubrication of the grinding zone, providing rather grain slipping at
The optimization of the parameters is done by Regression Analysis. The outputs are subjected to Regression Analysis and the optimal values are attained. Keywords:Cylindrical grinding Attachment, Surface finish, Work speed, Feed, Depth of the cut, Optimization
Determination of optimum parameters lies in the proper selection and introduction of suitable design of experiments (DOEs) at the earliest stage of the process and product development cycles. This paper compares and contrasts factorial design with Taguchi's design of experiments used in the determination of optimum grinding conditions. Optimum grinding conditions and grinding cycle time were estimated
dimensions and parameters determined from surveys to calculate cyclone throughput cut size, slurry recovery and water recovery. The primary equations are as follows: Optimizing Grinding Circuits 7 Charge Volume Estimator Like the AG Power Model the charge volume estimator is based upon the Morrell C Model. The model is used to determine the power curve for a particular set of conditions.