Mathematical Model For Surface Roughness Research Articles

Predictive modeling of surface roughness in high speed machining of AISI 4340 steel using yttria stabilized zirconia toughened alumina turning insert

An attempt has been made to investigate the surface finish of AISI 4340 steel for high speed machining using indigenously prepared yttria stabilized zirconia toughened alumina (ZTA) cutting inserts. These inserts are prepared through wet chemical co-precipitation route followed by powder metallurgy process. Response surface methodology (RSM) has been used to study the effect of different machining parameters i.e. cutting speed, feed rate and depth of cut on surface roughness of the job. The machining experiments are performed based on standard RSM design called central composite design (CCD). The mathematical model of surface roughness has been developed using second order regression analysis. The adequacy of the developed models and influence of each operating factors have been carried out based on analysis of variance (ANOVA) techniques. It can be concluded from the present study that for high speed machining this tool gives good surface finish. Key parameters and their interactive effect on each response have also been presented in graphical contours which may help for choosing the operating parameter preciously. Optimization of cutting parameters has also been carried out and 92.3% desirability level has been achieved using this optimal condition.

Modelling and analysis of factors influencing surface roughness and delamination of milling of GFRP laminates using RSM

PurposeThe purpose of this paper is to develop a mathematical model for surface roughness and delamination through response surface methodology (RSM) and analyse the influences of the entire individual input machining parameters (cutting speed, fibre orientation angle, depth of cut and feed rate) on the responses in milling of glass fibre reinforced plastics (GFRP) composites with solid carbide end mill cutter coated with PCD.Design/methodology/approachFour factors, five level central composites and a rotatable design matrix in response surface methodology were employed to carry out the experimental investigation. “Design Expert 8.0” software was used for regression and graphical analysis of the data were collected. The optimum values of the selected variables were obtained by solving the regression equation and by analyzing the response surface contour plots. Analysis of variance (ANOVA) was applied to check the validity of the model and for finding the significant parameters.FindingsThe developed second order response surface model was used to calculate the surface roughness and delamination of the machined surfaces at different cutting conditions with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.Originality/valueThe effect of fibre orientation during milling of GFRP laminates using RSM has not been previously attempted for analysis.

Optimization of Surface Roughness in End Milling of Medium Carbon Steel under the Influence of Magnets Attached to the Machine Spindle

One of the major technological parameters in metal cutting is surface roughness. It is an unavoidable, and often, unwanted by-product of all machining operations, especially end milling. Surface roughness is directly related to product quality and performance, operation cost, machining accuracy, and chatter. Today’s stringent customer requirements demand machined parts with minimum (mirror finished) products. Hence, the prediction, modeling, and optimization of surface roughness is a quintessential concern in machining research and industrial endeavor. This research was undertaken in order to determine whether end milling of medium carbon steel performed using chosen ranges of cutting parameter and under magnetic field generated by permanent magnets could effectively improve surface roughness. A small central composite design with five levels and an alpha value of 1.4142, in Response Surface Methodology, was used in developing the relationship between cutting speed, feed, and depth of cut, with surface roughness. Design-Expert 6.0 software was utilized to develop the quadratic empirical mathematical model for surface roughness. The experiments were performed under two different conditions. The first condition was cutting under normal conditions, while the other one was cutting under the application of magnetic fields from two permanent magnets. Medium carbon steel was used as the work material. The resultant average surface roughness was found to be reduced by a maximum of 59% due to magnet application.

Analysis of surface roughness and cutting force components in hard turning with CBN tool: Prediction model and cutting conditions optimization

In this study, the effects of cutting speed, feed rate, workpiece hardness and depth of cut on surface roughness and cutting force components in the hard turning were experimentally investigated. AISI H11 steel was hardened to (40; 45 and 50) HRC, machined using cubic boron nitride (CBN 7020 from Sandvik Company) which is essentially made of 57% CBN and 35% TiCN. Four-factor (cutting speed, feed rate, hardness and depth of cut) and three-level fractional experiment designs completed with a statistical analysis of variance (ANOVA) were performed. Mathematical models for surface roughness and cutting force components were developed using the response surface methodology (RSM). Results show that the cutting force components are influenced principally by the depth of cut and workpiece hardness; on the other hand, both feed rate and workpiece hardness have statistical significance on surface roughness. Finally, the ranges for best cutting conditions are proposed for serial industrial production.

Surface Intergrity of Inconel 718 under MQL Condition

The purpose of this study is to investigate the effect of turning parameters on the surface integrity of Inconel 718. The turning parameters studied were cutting speed of 90, 120, 150 m/min, feed rate of 0.15, 0.25, 0.25mm/rev and depth of cut of 0.3, 0.4, 0.5 mm under minimum quantity lubricant (MQL) using coated carbide tool. surface response methodology (RSM) design of experiment using Box-Behnken approach has been employed consisting of various combination of turning parameters Surface roughness, surface topography, microstructure and the micro hardness of the machined surface were studied after the machining process. Feed rate was found to be the most significant parameter affecting the surface roughness. The optimum parameter was obtained with Ra equal to 0.243 µm at cutting speed of 150 m/min, feed rate of 0.25 mm/rev and depth of cut of 0.3mm. A mathematical model for surface roughness was developed using Response Surface Methodology. The effect of turning parameters and factor interactions on surface roughness is presented in 3D graphical form, which helps in selecting the optimum process parameters to achieve the desired surface quality.

Surface model and tool-wear prediction model for solid lubricant-assisted turning

Mathematical models for surface roughness and tool wear are developed through regression analysis of the experimental data collected from machining. Different particle sizes and flowrates of solid lubricants are employed in the study. Experimental results show a significant effect of solid lubricant particle size and flowrate on surface roughness and tool wear. Decrease in the particle size resulted in reduced tool wear and surface finish improvement. Various machining parameters such as cutting forces, tool wear, and surface roughness improved with an increase in the flowrate of solid lubricant up to a certain level and remained constant at higher flowrates. To estimate the effect of solid lubricants on machining, exponential models are proposed in the present work to predict tool wear and surface roughness as a function of solid lubricant particle size, flowrate, machining time, and cutting force. Predicted values obtained from the developed model and experimental results are compared, and error<10 per cent is observed.

Mathematical modeling of surface roughness for evaluating the effects of cutting parameters and coating material

The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) onto the surface roughness through the mathematical model developed by using the data gathered from a series of turning experiments performed. An additional investigation was carried out in order to evaluate the influence of two well-known coating layers onto the surface roughness. For this purpose, the experiments were repeated for two CNMG 120408 (with an ISO designation) carbide inserts having completely the same geometry and substrate but different coating layers, in a manner that identical cutting conditions would be ensured. The workpiece material machined was cold-work tool steel AISI P20. Of the two types of inserts employed; Insert 1 possesses a coating consisting of a TiCN underlayer, an intermediate layer of Al 2O 3 and a TiN outlayer, all deposited by CVD; whilst Insert 2 is PVD coated with a thin TiAlN layer (3 ± 1 μm). The total average error of the model was determined to be 4.2% and 5.2% for Insert 1 and Insert 2, respectively; which proves the reliability of the equations established.

Patents: Europe

In this study, the effects of cutting speed, feed rate, workpiece hardness and depth of cut on surface roughness and cutting force components in the hard turning were experimentally investigated. AISI H11 steel was hardened to (40; 45 and 50) HRC, machined using cubic boron nitride (CBN 7020 from Sandvik Company) which is essentially made of 57% CBN and 35% TiCN. Four-factor (cutting speed, feed rate, hardness and depth of cut) and three-level fractional experiment designs completed with a statistical analysis of variance (ANOVA) were performed. Mathematical models for surface roughness and cutting force components were developed using the response surface methodology (RSM). Results show that the cutting force components are influenced principally by the depth of cut and workpiece hardness; on the other hand, both feed rate and workpiece hardness have statistical significance on surface roughness. Finally, the ranges for best cutting conditions are proposed for serial industrial production.

PATENTS: Europe

In this study, the effects of cutting speed, feed rate, workpiece hardness and depth of cut on surface roughness and cutting force components in the hard turning were experimentally investigated. AISI H11 steel was hardened to (40; 45 and 50) HRC, machined using cubic boron nitride (CBN 7020 from Sandvik Company) which is essentially made of 57% CBN and 35% TiCN. Four-factor (cutting speed, feed rate, hardness and depth of cut) and three-level fractional experiment designs completed with a statistical analysis of variance (ANOVA) were performed. Mathematical models for surface roughness and cutting force components were developed using the response surface methodology (RSM). Results show that the cutting force components are influenced principally by the depth of cut and workpiece hardness; on the other hand, both feed rate and workpiece hardness have statistical significance on surface roughness. Finally, the ranges for best cutting conditions are proposed for serial industrial production.

Optimization of surface finish in end milling Inconel 718

This paper presents an approach to optimize the surface finish in end milling Inconel 718 using uncoated carbide inserts under dry conditions. In view of this, the mathematical models for surface roughness have been developed in terms of speed and feed by response surface methodology. Response surface contours were constructed in speed feed planes by computer. From these contours it was possible to select a combination of cutting speed and feed that reduces machining time without increasing the surface roughness. These were obtained by superimposing the constant lines of metal removal rates on the surface roughness contours.

Surface roughness prediction model in end milling of Al/SiCp MMC by carbide tools

The advancement in automation and accuracy of machine tool made it possible to produce high quality industrial products. One of the main perceptions of quality in mechanical products is its physical appearance. One of the most important factors in physical appearance is the surface roughness. A number of research publications addressed this issue of surface roughness measurement and analyses. This research focuses on study and analyses of surface quality improvement in end milling operation of Al/SiCp metal matrix composite. These materials are selected as they are most widely used in automobile and aerospace industry. This research paper develops an improved mathematical model for surface roughness (Ra) prediction in end milling of Al/SiCp MMC. The impacts of spindle speed, feed rate, depth of cut and various percentage weight of silicon carbide are studied on surface roughness. The result obtained using Response Surface Methodology (RSM) gives a good prediction of surface roughness when compared with actual surface roughness.