Prediction of surface roughness of end milling operation using genetic algorithm

In this study, surface roughness generated by face milling of 38CrSi high-strength steel is discussed. Experiments based on 24 factorial design and Box-Behnken design method are conducted to investigate the effects of milling parameters (cutting speed, axial depth of cut and radial depth of cut and feed rate) on surface roughness, and a second-order model of surface roughness is established by using surface response methodology (RSM); Significance tests of the model are carried out by the analysis of variance (ANOVA). The results show that the most important cutting parameter is feed rate, followed by radial depth of cut, cutting speed and axial depth of cut. Moreover, it is verified that the predictive model possesses highly significance by the variance examination at a level of confidence of 99%. And the relationship between surface roughness and the important interaction terms is nonlinear.

This dissertation outlines research on studying the effects of machining parameters such that cutting speed, feed rate, axial depth of cut, radial depth of cut and helix angle on system dynamic stability and the surface quality of high-speed milling. With the use of structural tool modal parameters, the material cutting force coefficients and the axial depth of cut, the system can avoid the chatter phenomenon of the tool at high cutting speeds. The surface roughness finish in the milling process is determined by the machining parameters and tool structure dynamics. To perform high-speed milling, the chance of tool vibration (chatter phenomenon) which affects the cutting tool, must be minimized or eliminated. In this research, the linear and nonlinear mathematical force models including the effect of the helix angle are presented for an end-milling process. The linear force model includes cutting-edge coefficients. The cutting force coefficients are determined for an end-milling process using two methods, the average force method and the optimization technique method. The second method is developed to identify the cutting force coefficients in the milling process by forming the objective functions using the optimization technique to minimize the error between the experimental and the analytical forces. Moreover, this method produced a good force model that approximates the experimental force results, which compared with the average force method. The stability lobe diagrams are created using the analytical method to determine whether the cut is stable or unstable. In addition, simulations are performed to predict stability of the milling process. By comparing simulated and experimental results, the dynamics and stability of the milling operation can be easily identified before performing any cutting operation. The slot milling experiments show that while the system in the chatter region close to the stability limits and the axial depth of cut increased, the system changes from stable chatter to chaotic chatter. Furthermore, the nature of bifurcation in milling is investigated by performing experiments and simulations. The linear and nonlinear mathematical force models are used for simulating end-milling process. Simulated bifurcation diagrams are generated using both models and compared to experimental results. In addition, the effect of the feed rate on the location of the bifurcation point (start and end of bifurcation) is studied. By comparing simulated and experimental results, the simulation using a nonlinear force model is found more accurate in predicting the dynamics and stability of the milling operation. The applications of Taguchi and response surface methodologies (RSM) are used to minimize the surface roughness in the end milling process. Taguchi’s method for optimum selection of the milling process parameters is applied based on the signal to noise ratio and ANOVA analysis of the surface finish. A second-order model contains quadratic terms that have been created between the cutting parameters and surface roughness using response surface methodology (RSM). Surface roughness of the machined surfaces are measured and used to identify the optimum levels of the milling parameters. Based on Taguchi, ANOVA, and RSM analyses, the end milling process can be optimized to improve surface finish quality and machining productivity.

Coolant is a part of the cutting fluid used in the machining process. Application of cutting fluid in the industry causes environmental pollution problems. One of the sustainable cooling techniques is a CO2 cryogenic cooling system, which can reduce the effects of cutting fluids. This study aims to conduct mathematical modelling of surface roughness. Machining performance using CO2 as a cooling technique was used to measure surface roughness. Variations in machining parameters are cutting speed (Vc), radial depth of cut (ar), and axial depth of cut (ax). Mathematical modelling was present in this study. The minimum surface roughness, resulted by using Response Surface Methodology (RSM) is the surface quality 0.712 µm. This result was achieved using the cutting speed of 31.10 m/minute, the axial depth of cut 5 mm, and the radial depth of cut 0.2 mm. The minimum surface roughness value was achieved with optimized machining conditions with the desirability of 87.5%

Surface roughness is one of the most important requirements of the finished products in machining process. The determination of optimal cutting parameters is very important to minimize the surface roughness of a product. This article describes the development process of a surface roughness model in high-speed ball-end milling using response surface methodology based on design of experiment. Composite desirability function and teaching-learning-based optimization algorithm have been used for determining optimal cutting process parameters. The experiments have been planned and conducted using rotatable central composite design under dry condition. Mathematical model for surface roughness has been developed in terms of cutting speed, feed per tooth, axial depth of cut and radial depth of cut as the cutting process parameters. Analysis of variance has been performed for analysing the effect of cutting parameters on surface roughness. A second-order full quadratic model is used for mathematical modelling. The analysis of the results shows that the developed model is adequate enough and good to be accepted. Analysis of variance for the individual terms revealed that surface roughness is mostly affected by the cutting speed with a percentage contribution of 47.18% followed by axial depth of cut by 10.83%. The optimum values of cutting process parameters obtained through teaching-learning-based optimization are feed per tooth ( fz) = 0.06 mm, axial depth of cut ( Ap) = 0.74 mm, cutting speed ( Vc) = 145.8 m/min, and radial depth of cut ( Ae) = 0.38 mm. The optimum value of surface roughness at the optimum parametric setting is 1.11 µm and has been validated by confirmation experiments.

The goal of this study is to present a methodology for the determination of the optimal cutting parameters (spindle speed, feed rate and tool point angle) during the drilling process of carbon fiber reinforced polymer composites (CFRP) to maximize the material removal rate by considering surface roughness, delamination and thrust force as the constraints through coupling Response Surface Method (RSM) and Genetic Algorithm (GA). In this regard, the advantages of statistical experimental design technique, experimental measurements, Response Surface Method (RSM) and the genetic optimization method are exploited in an integrated manner. To this end, the experiments on CFRP were conducted to obtain surface roughness, delamination factor and thrust force values based on the full factorial design of experiments, and then analysis of variance (ANOVA) is performed. The predictive models for outputs were created using Response Surface Method (RSM) taking advantage of the experimental data. Material removal rate constituted the main function for the genetic algorithm, and thrust force, delamination, and surface roughness were applied as the constraints of the GA function. The function was optimized by the GA code, and finally, the optimum variables were obtained, and the results of the GA were tested experimentally. It can be clearly observed that good agreement exists between the predicted values and the experimental measurements.

Prediction of cutting force in end-milling operation of modified AISI P20 tool steel

The present paper discusses on development of fuzzy rule based models (FRBMs) for predicting cutting force and surface roughness in milling operation. The models use TakagiSugeno-Kang-type (TSK-type) fuzzy rule to study the effect of four (input) cutting parameters (cutting speed, feed rate, radial depth of cut and axial depth of cut) on outputs (cutting force and surface roughness). The appropriate FRBM is arrived after a thorough investigation of different structures of rule-consequent function. A combined approach of genetic algorithm and multiple linear regression method is used to determine the rule-consequent parameters. Performance analysis of models by comparing with experimental data implies its potential towards practical application. Analysis of the influence of various input parameters on different outputs is carried out based on FRBMs and experimental data. It suggests that the cutting force becomes higher with increasing feed rate, axial depth of cut and radial depth of cut and lower with increase in cutting speed, whereas surface finish is improved with increase in cutting speed and gets poorer with increase in radial depth of cut.

Micromilling mechanism studies are the fundamentals for high-quality micro components fabrications. Based on the finite element method (FEM), the simulation model for micromilling of the oxygen-free copper (OFC) was established in this paper. The influences of the key process parameters (feed engagement fz, axial depth of cut ap, radial depth of cut ae, and spindle speed n) on the milling forces were investigated. According to the simulation results, to achieve the minimum undeformed chip thickness, the critical feed engagement was identified to be 2.5 μm/z. when the axial depth of cut increased, the milling force was increasing linearly, but at the same time the milling force took an oscillator decreases due to the increasing of spindle speed. The overall trend of milling force under different radial depths of cut is upward. Therefore, the feed engagement should be greater than 2.5μm/z for micro milling of oxygen-free copper. Small radial depth of cut, small axial depth of cut, and appropriate spindle speed should be selected to obtain a high machining quality. Introduction As an excellent metal with extremely low oxygen content, high conductivity and high corrosion resistance, oxygen-free copper C10100 is widely used in the manufacturing of audio-visual equipment and communication components. With good ductility and no hydrogen embrittlement, it can also be processed into various precision micro parts. Compared with traditional cutting, high-speed micromilling is more suitable for machining micro-small parts. In order to obtain higher dimensional accuracy and better surface quality, it is necessary to study the milling parameters of OFC in the processing of precision parts. In the actual machining process, the changes of milling force caused by the changes of milling parameters can reflect the quality of the final machined parts more intuitively. Therefore, the adjustment of milling parameters can be guided by measuring the milling force in the milling process. In order to reveal the difference in mechanism between traditional cutting and micromilling, scholars have conducted a lot of studies. In the study of cutting poly-crystalling OFC with single crystalline diamond (SOD) micro-tools, X. Ding has proposed that the cutting strategy of reducing cross-feed can improve the cutting performance with using micro-tools. Constant cutting forces, burr size and an improved roughness of the machined surface have been obtained by employing this cutting strategy [1]. Niu has presented an innovative cutting force modeling concept by taking account of micro-cutting dynamics. Experimental cutting trial is conducted to validate the modeling approach and the cutting force model [2]. Qu has studied the impact of MQCL method on the machining results and mechanical properties of the component [3]. Yuan has proposed an innovative uncut chip thickness algorithm and developed the model for determining the instantaneous uncut chip thickness in micro end-milling processes [4]. D.DAS has studied the effect of stress parameters on ratcheting deformation stages of polycrystalline OFHC copper [5]. For the micromilling of pure copper, M. Rahman has studied the failure mechanism and factors which affect the micro end mill [6]. Liu has studied the relationship between size effect and burr in micromilling OFC and constructed a geometric model of exit burrs [7]. Liu has established SPH simulation model and carried out systematic research on formation mechanism of chip [8].For oxygen-free copper materials, Tian has established a constitutive model and carried out simulation analysis based on Abaqus [9]. Cheng has proposed 211

This study aims to optimize the machining parameters in the manufacture of Yamaha motorcycle brake piston master cylinder and determine the effect on surface roughness. The method used is the Taguchi method. Machining parameters were varied based on the Taguchi method, each of which was experimented with using a finishing CNC lathe machine. From these experiments, the results obtained in the form of surface roughness values ​​which were then analyzed, in order to obtain the best parameters with the smallest surface roughness values ​​and the effect of each factor on surface roughness. This research produces the best parameters are spindle speed 1.755 RPM, feed rate 0.09 mm/rev, and depth of cut 0.30 mm. This parameter has a small surface roughness value. Based on surface roughness measurements, the factors that have the greatest influence on the level of surface roughness are feed rate of 67.9%, spindle speed of 15.4% and depth of cut of 3.3%. This proves that the smaller the value of feed rate, spindle speed and depth of cut, the smaller the value of surface roughness will be.

Natural fiber is a hairy like raw material which comes from natural sources such as animal, plant, and mineral fibers. Kenaf fiber known with scientific name as Hibiscus Cannabinus is one natural fibers which becoming popular as a reinforced for plastic composites material in the industrial application such as automobile, aircraft, and marine engineering. However, milling these materials present a few problems, which are surface roughness and delamination factors are appear during the machining process, associated with the characteristics of the material and the cutting parameter. The objective of evaluating the cutting parameters (spindle speed, feed rate, and depth of cut), the influence of the fibers under surface roughness (Ra) and delamination factor (Fd). In this research study, Response Surface Methodology (RSM) was used to conduct the experiment. In addition, this method established considering milling with prefixed cutting parameters using HSS end mill. The experiment result was analyzed using Design Expert software. It was found that the optimum parameters for the minimum surface roughness and delamination were spindle speed at 2000 rpm, feed rate at 300 mm/min, and depth of cut at 2.0 mm. The spindle speed and feed rate are the main factors influence the effect of surface roughness and delamination in kenaf fiber reinforced plastic. High spindle speed and low feed rate resulted in minimum surface roughness and delamination.KeywordsCompositeMillingSurface roughnessDelaminationRSM

This study evaluates the impacts of machining parameters on the milling of general-purpose poly (methyl methacrylate) (PMMA) with respect to cutting point temperature, maximum machining temperature, and surface roughness. The machining parameters used in the analysis are spindle speed (rpm), depth of cut (mm), and feed rate (mm/min). The extreme ranges of the machining parameters for the material are obtained from trial experiments. From these experiments, four values of each parameter are adopted. This yields 12 experiments, which are divided into three sets. In the first set of experiments, the depth of cut and feed rate are held constant at 0.2 mm and 25 mm/min, while the spindle speed is varied from 1000 rpm to 4000 rpm. In the second set of experiments, the spindle speed and feed rate are held constant at 1000 rpm and 25 mm/min, respectively, while the depth of cut is varied from 0.2 mm to 1.1 mm. In the last set of experiments, the spindle speed and depth of cut are held constant at 1000 rpm and 0.2 mm, respectively, as the feed rate is varied from 25 mm/min to 100 mm/min. Thermal images are obtained during milling, where the cutting point and maximum machining temperatures are obtained. The milled surfaces are then investigated for surface roughness. The chips are also collected from each experiment and used in conducting chip morphology. From the results, it is observed that to obtain the least temperatures and best surface quality, the least machining parameters should be chosen. These parameters are identified as 1000 rpm, 0.2 mm, and 25 mm/min for the spindle speed, depth of cut, and feed rate, respectively. An increase in spindle speed seems to increase the milling temperatures and surface roughness, which is attributed to the reducing chip thickness. An increase in the depth of cut does not affect the generation of chips, and the thickness is relatively constant. However, an increase in milling feed increases the chip thickness, which increases the surface roughness.

In this study, by using Taguchi method, with four controllab le factors-three levels (milling type, axial depth of cut, feed rate, and spindle speed), the orthogonal array L 27 was used to investigate the effects of milling type and cutting conditions on the surface roughness.By analysis of variance (ANOVA ), the influences degree of milling type, axial cutting depth, feed rate, and spindle speed on the surface roughness were 9.26 %, 12.85 %, 12.69 %, and 63.08 %, respectively.The interaction factors of these factors that have a quite small influence on the surface roughness.The surface roughness was modeled as a quadratic regression with the confidence level is more than 99.82%.Th is model was successfully verified by comparison of experimental and predicted results.The optimization process of surface roughness was performed by both Taguchi method and the ANOVA analysis with the same results.The optimu m value of surface roughness was 0.374 µm that was obtained in the half up milling, at a cutting depth of 0.4 mm, a feed rate of 480 mm/ min, and a spindle speed of 5000 rpm.

This study aims to increase the microhardness of Ti-6Al-4 V produced by laser polishing (LP) with selective laser melting (SLM), to make micromachinability with optimum parameters and to minimize surface roughness. LP process has started to attract great industrial interest today due to the significant increase in surface quality. In addition, the processing of small geometry channels, requiring precision and high surface quality, further increases the importance of micromilling. In this experimental study, the surface morphology, microhardness and micromachinability of Ti-6Al-4 V material produced by SLM were investigated before and after LP. The aim is to investigate the increase in microhardness, surface roughness, and burr amount with 3 different spindle speeds (4000-6000-8000), 4 different feed rates (2-4-6-9), and 2 different depths of cut used as micromilling parameters. When the SLM material was compared to the LP material, the hardness value increased by approximately 27%. It was observed that there was a 400% improvement in surface roughness values (Sa). When viewed with three-dimensional surface topography, it is seen that the cutting marks are more prominent in the material made with LP. Surface roughness values are inversely proportional to cutting speed and directly proportional to feed rate. While materials with high hardness should have lower surface quality in machined areas, Sa values are lower in LP areas. In addition, the difference between the surface roughness values is maximum for both SLM and LP material at the same depths of cut. These findings are aimed to determine the machinability parameters during the manufacturing of materials used especially in the aviation, defense, medical, and automotive industries.

The high-intensity noise generated during high-speed milling of wood-plastic composites, due to the material properties of anisotropy and non-uniformity, seriously affects the working environment and operator comfort. The influence of axial depth of cut, radial depth of cut, cutting speed, and feed per revolution on the sound pressure level of milling noise in wood-plastic composites was analyzed through single-factor milling experiments. Furthermore, a principal component variance analysis was conducted using multi-level factorial milling experiments to investigate the interaction effects of milling parameters on milling noise variation. The results showed that, for a fixed milling length, the significance of milling parameters on milling noise sound pressure level decreased in the order of cutting speed, axial depth of cut, radial depth of cut, and feed per revolution. A smaller axial depth of cut was suggested to control noise emission while ensuring machining efficiency. With a constant axial depth of cut, lower feed per revolution and radial depth of cut helped achieve reduced noise levels. This study provides a theoretical basis for addressing the challenge of high-intensity noise generated during high-speed milling of wood-plastic composites.

It is well known that machining parameters have strong effect on the properties of surface roughness. Many investigations have done on this area. This work studies of combining effect of turning process parameters (cutting speed, feed rate, and depth of cut) with on surface roughness. Where, nose radius of the tool and machining parameters have taken as input variables and the surface roughness (Ra) as response or output. Three experiments were conducted; they were used to investigate the surface roughness resulted by tool corner radiuses of the values: 0.4mm, 0.8mm, and 1.2mm Response surface methodology (R.S.M) is applied as a tool to show the cause and effect of output (response) and input control and relationship between them as a two or three dimensional hyper surface. A three factor with five level central composite rotatable factors design was used. The results showed that R.S.M is a strong tool and capability tool to predict the effect of machining parameters on surface roughness. Results improved that the five level factorial designs can be employed for developing statistical models to predict surface roughness by controllable machining parameters. Results showed that the combined effect of cutting speed at its higher level, feed rate and depth of cut at their lower values, and large nose radius can result in better surface roughness.