An experimental investigation as to the effect of cutting parameters on roundness error and surface roughness in cylindrical grinding

This paper presents the results of an experimental investigation as to the effects of grinding parameters on roundness error and surface roughness in cylindrical grinding. Many variables including the wheel materials, wheel loading and dressing, workpiece metallurgy, work drive mechanisms, work holding methods, coolant types, feeds and speeds, machine stiffness and age, surface conditions, centre conditions, floor vibrations all influence the quality of ground parts. However, the composite sum of these grinding parameters creates static and dynamic forces. It is obvious that the roundness error and surface roughness are created by many parameters, but in this study, only the effects of the depth of cut, work speed and feed rate which create the grinding forces in cylindrical grinding are investigated. The grinding experiments were planned according to the principles of orthogonal arrays (OAs), developed by Taguchi, and were performed so as to understand the effects of these parameters on roundness error and surface roughness. The experimental data was analysed by using statistical tools: the percent contribution from an analysis of variance (ANOVA) and the correlation between machining parameters with roundness error (R) and also surface roughness (Ra). Roundness was found to be the most related with the cutting speed, grinding force and depth of cut, while surface roughness is related to feed rate and work speed.     

Tool condition monitoring in milling based on cutting forces by a neural network

Automated machining systems require reliable online monitoring processes. The application of a multilayered neural network for tool condition monitoring in face milling is introduced and evaluated against cutting force data. The work uses the back-propagation algorithm for training neural network of 5 2 10 2 2 architecture. An artificial neural network was used for feature selection in order to estimate flank wear ( Vb ) and surface roughness ( Ra ) during the milling operation. The relationship of cutting parameters with Vb and Ra was established. The sensor selection using statistical methods based on the experimental data helps in determining the average effect of each factor on the performance of the neural network model. This model, including cutting speed, feed rate, depth of cut and two cutting force components (feed force and vertical Z -axis force), presents a close estimation of Vb and Ra . Therefore, the neural network with parallel computation ability provides a possibility for setting up intelligent sensor systems.     

Evaluation of advanced alumina-based ceramic tool inserts when machining high-tensile steel

Three types of alumina-based ceramic tools (zirconia toughened, titanium-carbide reinforced and silicon-carbide-whisker reinforced) were used to evaluate their cutting performance when machining a high-tensile steel. Experimental studies were carried out at various cutting speeds, feeds and depths of cut, in dry conditions. The cutting performance of the alumina-based ceramic tools was judged by the cutting force produced during the process of machining, by the surface roughness of the workpiece and by the wear rate of the cutting inserts. The influence of the cutting parameters (that is, the cutting speed, feed rate and depth of cut) on the cutting performance is discussed.     

Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics

This article addresses an approach based on the Taguchi method with grey relational analysis for optimizing turning operations with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to solve the turning operations with multiple performance characteristics. Optimal cutting parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. Tool life, cutting force, and surface roughness are important characteristics in turning. Using these characteristics, the cutting parameters, including cutting speed, feed rate, and depth of cut are optimized in the study. Experimental results have been improved through this approach.     

Experimental investigation of cutting parameters in machining of 100Cr6 with tangential turn-milling method

The turn-milling methods for machining operation have been developed to increase efficiency of conventional machines recently. These methods are used especially by coupling some apparatuses on the computer numerical control (CNC) machine to decrease the production time and machine costs, ensure the maximum production and increase the quality of machining. In this study, 100Cr6 bearing steel extensively used in industry has been machined by tangential turn-milling method. This paper presents an approach for optimization of the effects of the cutting parameters including cutter speed, workpiece speed, axial feed rate, and depth of cut on the surface roughness in the machining of 100Cr6 steel with tangential turn-milling method by using genetic algorithm (GA). Tangential turning-milling method has been determined to have optimum effects of cutting parameters on the machining of 100Cr6 steel. The experimental results show that the surface roughness quality is close to that of grinding process.     

Prediction and optimisation models for turning operations

Selection of process parameters has very significant impact on product quality, production costs and production times. The quality and cost are much related to tool life, surface roughness and cutting forces which they are functions of process parameters (cutting speed, feed rate, depth of cut and tool nose radius). In this paper, empirical models for tool life, surface roughness and cutting force are developed for turning operations. The process parameters (cutting speed, feed rate, depth of cut and tool nose radius) are used as inputs to the developed machineability models. Two data mining techniques are used; response surface methodology and neural networks. The data of 28 experiments have been used to generate, compare and evaluate the proposed models of tool life, cutting force and surface roughness for the selected tool/material combination. The resulting models are utilized to formulate an optimisation model and solved to find optimal process parameters, when the objective is minimising production cost per workpiece, taking into account the related boundaries and limitation of this multi-pass turning operations. Numerical examples are given to demonstrate the suggested optimisation models.     

Surface Roughness Analysis in Machining of Titanium Alloy

The use of response surface methodology for minimizing the surface roughness in machining titanium alloy, a topic of current interest, has been discussed in this article. The surface roughness model has been developed in terms of cutting parameters such as cutting speed, feed, and depth of cut. Machining tests have been carried out using CVD (TiN-TiCN-Al₂O₃-TiN) coated carbide insert under different cutting conditions using Taguchi's orthogonal array. The experimental results have been investigated using analysis of variance (ANOVA). The results indicated that the feed rate is the main influencing factor on surface roughness. Surface roughness increased with increasing feed rate, but decreased with increasing cutting speed and depth of cut. The predicted results are fairly close to experimental values and hence, the developed models can be used for prediction satisfactorily.     

Effect of Machining Parameters on Surface Integrity in High Speed Milling of Super Alloy GH4169/Inconel 718

Control of surface integrity is a vital consideration in the machining of components subjected to fatigue loading, for example, critical components of aerospace engines. In this research, three important aspects of surface integrity of a machined part—surface roughness, micro-hardness, and residual stresses—were analyzed for their variations with the cutting parameters. Finish milling of super alloy GH4169/Inconel 718 was carried out using coated cemented carbide and whisker-reinforced coated ceramic inserts. All of the three machining parameters—cutting speed, feed rate, and depth of cut—were found to have a substantial effect on the surface integrity of the finished part. Although different cutting parameters gave different effects for the two types of cutting inserts, overall better surface integrity was obtained at minimum cutting feed and medium cutting speed and depth of cut value. Moreover, carbide inserts produced better surface integrity of the finished part, whereas ceramic inserts generated very high surface tensile stresses and poor surface finish due to back striking of the adhered metal chips.     

Experimental Study of Cutting Force,Microhardness, Surface Roughness,and Burr Size on Micromilling of Ti6Al4V in Minimum Quantity Lubrication

In the present study, the effects of various cutting conditions on the surface integrity of titanium parts (Ti6Al4V) have been investigated during the micromilling process. In addition, to have a better understanding of the results, the cutting force was measured. The experiments were performed in the Minimum Quantity Lubrication condition using the tungsten carbide microtool with 0.5 mm in diameter. Micromilling parameters including feed rate, spindle speed and axial depth of cut were considered as process inputs, each in three levels, and their effects on the surface roughness, burr width, surface and in-depth microhardness as well as mean cutting force were evaluated. In the range of experimental parameters and according to the results, cutting speed and feed per tooth had the highest impact on the surface integrity characteristics of this alloy, respectively. While most research works concentrated on the feed per tooth as the main parameter in the micromilling process, the result of the study showed that the variation of cutting speed as one of the influential factors could also be used in order to decrease cutting forces and to improve surface quality.     

Studies on Machining Parameters While Milling Particle Reinforced Hybrid (Al6061/Al2O3/Gr) MMC

In this article, response surface methodology has been used for finding the optimal machining parameters values for cutting force, surface roughness, and tool wear while milling aluminum hybrid composites. In order to perform the experiment, various machining parameters such as feed, cutting speed, depth of cut, and weight (wt) fraction of alumina (Al₂O₃) were planned based on face-centered, central composite design. Stir casting method is used to fabricate the composites with various wt fractions (5%, 10%, and 15%) of Al₂O₃. The multiple regression analysis is used to develop mathematical models, and the models are tested using analysis of variance (ANOVA). Evaluation on the effects and interactions of the machining parameters on the cutting force, surface roughness, and tool wear was carried out using ANOVA. The developed models were used for multiple-response optimization by desirability function approach to determine the optimum machining parameters. The optimum machining parameters obtained from the experimental results showed that lower cutting force, surface roughness, and tool wear can be obtained by employing the combination of higher cutting speed, low feed, lower depth of cut, and higher wt fraction of alumina when face milling hybrid composites using polycrystalline diamond insert.     

An application of goal programming technique in metal cutting

This paper outlines the use of the goal programming technique in selecting levels of machining parameters in a fine turning operation on A1S1 4140 steel using cemented tungsten carbide tools. Goals that are proposed to be achieved are: (i) to finish turning the required depth in one pass, mid (ii) to finish turning within a stipulated time. Constraints used are: R.M.S. surface finish values, cutting horse power of the machine, ranges for cutting speed, feed and depth of cut. A predictive equation to predict the R.M.S. Surface roughness values from the machining variables, cutting speed, feed, depth of cut, and time of cut was used. This mathematical model was developed using stepwise regression analysis on the experimental data for 1/64 in. nose radius cemented tungsten carbide cutting tool. Experiment with the machining variables at different levels were performed to obtain the data. A statistically designed experiment called the rotatable design was used for the experimental design     

Comparison between constant force and constant rate of feed in materialographic cut-off machines: Surface quality in relation to cutting speed, force, and rate of feed

With the precision cutting of materialographic samples, it is of the utmost importance that the cut surface exhibits as little deformation as possible. A number of factors influence the quality of the cut surface: type of cut-off wheel, rate of feed (mm/s), force (N), and specific pressure in the cut (N/mm²). In this study, cutting tests were carried out and two cutting principles, constant force and constant rate of feed, were compared. The resultant cut surfaces were examined using both light optical microscopy and atomic force microscopy, with the corresponding surface roughness measured on a profile meter. This study shows that when cutting workpieces of varying shape, the most uniform surface is obtained by using a constant rate of feed. Also, a constant rate of feed, combined with a high cutting speed, will produce surfaces with the least and most uniform deformation.     

Experimental study on the meso-scale milling of tungsten carbide WC-17.5Co with PCD end mills

Tungsten carbide is a material that is very difficult to cut, mainly owing to its extreme wear resistance. Its high value of yield strength, accompanied by extreme brittleness, renders its machinability extremely poor, with most tools failing. Even when cutting with tool materials of the highest quality, its mode of cutting is mainly brittle and marred by material cracking. The ductile mode of cutting is possible only at micro levels of depth of cut and feed rate. This study aims to investigate the possibility of milling the carbide material at a meso-scale using polycrystalline diamond (PCD) end mills. A series of end milling experiments were performed to study the effects of cutting speed, feed per tooth, and axial depth of cut on performance measures such as cutting forces, surface roughness, and tool wear. To characterize the wear of PCD tools, a new approach to measuring the level of damage sustained by the faces of the cutter's teeth is presented. Analyses of the experimental data show that the effects of all the cutting parameters on the three performance measures are significant. The major damage mode of the PCD end mills is found to be the intermittent micro-chipping. The progress of tool damage saw a long, stable, and steady period sandwiched between two short, abrupt, and intermittent periods. Cutting forces and surface roughness are found to rise with increments in the three cutting parameters, although the latter shows signs of reduction during the initial increase in cutting speed only. The results of this study find that an acceptable surface quality (average roughness R_a<0.2 μm) and tool life (cutting length L>600 mm) can be obtained under the conditions of the given cutting parameters. It indicates that milling with PCD tools at a meso-scale is a suitable machining method for tungsten carbides.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00298-y     

A surface roughness model for a turning operation

A mathematical model for the surface roughness in a turning operation was developed in terms of the cutting speed, feed and depth of cut. Utilizing PL1 language and an IBM 360/50 computer, the model was used to generate contours of surface roughness in planes containing the cutting speed and feed at different levels of depth of cut. The surface roughness contours were used to select the machining conditions at which an increase in the rate of metal removal was achieved without sacrifice in surface finish.     

An experimental study on grinding of Zr-based bulk metallic glass

There are limited studies in the literature about machinability of bulk metallic glass(BMG).As a novel and promising structural material,BMG material machining characteristics need to be verified before its utilization.In this paper,the effects of cutting speed,feed rate,depth of cut,abrasive particle size/type on the BMG grinding in dry conditions were experimentally investigated.The experimental evaluations were carried out using cubic boron nitride(CBN) and Al_2O_3 cup wheel grinding tools.The parameters were evaluated along with the results of cutting force,temperature and surface roughness measurements,X-ray,scanning electron microscope(SEM)and surface roughness analyse.The results demonstrated that the grinding forces reduced with the increasing cutting speed as specific grinding energy increased.The effect of feed rate was opposite to the cutting speed effect,and increasing feed rate caused higher grinding forces and substantially lower specific energy.Some voids like cracks parallel to the grinding direction were observed at the edge of the grinding tracks.The present investigations on ground surface and grinding chips morphologies showed that material removal and surface formation of the BMG were mainly due to the ductile chip formation and ploughing as well as brittle fracture of some particles from the edge of the tracks.The roughness values obtained with the CBN wheels were found to be acceptable for the grinding operation of the structural materials and were in the range of 0.34-0.58 μm.This study also demonstrates that conventional Al_2O_3 wheel is not suitable for grinding of the BMG in dry conditions.     

Anisotropy of surface roughness in diamond turning of brittle single crystals

This paper deals with an investigation of the effect of crystallographic orientation and process parameters on the surface roughness of brittle silicon single crystals in ultraprecision diamond turning. The process parameters involve the depth of cut, feed rate, and spindle speed. Experimental results indicate that anisotropy in surface finish occurs when the cutting direction relative to the crystal orientation varies. There exists a periodic variation of surface roughness per workpiece revolution, which is closely related to the crystallographic orientation of the crystals being cut. Such an anisotropy of surface roughness can be minimized with an appropriate selection of the feed rate, spindle speed, and depth of cut. The findings provide a means for the optimization of the surface quality in diamond turning of brittle silicon single crystals.     

Multi-attribute optimization of end milling epoxy granite composites using TOPSIS

Epoxy granite composites are identified and recognized as better materials for machine tool applications due to inherent damping properties. However, end milling of these composites has not been explored much. Milling of epoxy granite composites presents a number of problems, namely, cutting forces and surface roughness appear during machining. This research work focuses on end milling of epoxy granite composite specimens using high-speed steel end mill cutter by varying the cutting conditions such as spindle speed and feed with a uniform depth of cut and selection of optimal machining parameters. The experimental runs of 27 different trials were carried out and three different attributes such as thrust force, tangential force, and surface roughness were analyzed. This research work presents a sequential procedure for machining parameters selection. Selection of optimal machining parameters is done on the basis of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method.     

Study on the influential process parameters in machining the austempered ductile iron

Since the machinability data on grade 3 austempered ductile iron is scarce, this experimental work mainly focuses on the impact of machining parameters on cutting force and surface roughness while turning the above work material with cubic boron nitride and tungsten carbide inserts. Parameters like depth of cut, cutting speed and feed were considered in this study when analyzing the machinability of austempered ductile iron. Austempered ductile iron was turned with CBN and coated WC inserts. The response surface methodology was utilized to design the experiments and optimize the cutting parameters for the work material by each of the above inserts. The cubic boron nitride insert performs well as compared to the coated tungsten carbide for turning the austempered ductile iron and it has been concluded by taking lower force and higher surface finish in to consideration. The optimum parameters for turning austempered ductile iron with the cubic boron nitride insert is as follows: 174 meter/minute cutting speed, 0.102 millimeter/revolution feed and depth of cut of 0.5 millimeter.     

The Impact of Tool Material and Cutting Parameters on Surface Roughness of a Nickel-Base Superalloy

The objective of the present work, is to assess the effect of tool material and cutting parameters on surface roughness of the supermet 718 Nickel-base superalloy, under dry cutting conditions and a constant nose radius (0.5 mm). The parameters investigated are cutting speed, feed rate, depth of cut and tool material. The tool materials used were the ceramic (Sandvik CC 680) and the CBN (Sandvik CB 50) inserts. These variables were investigated using a 2^k factorial design.

The present work demonstrates a favorable effect for ceramic inserts on surface roughness, when compared with CBN inserts. The work also, showed that the feed rate has the dominant effect among the parameters studied on the surface roughness, irrespective of the tool material used.     

Optimization for Turning of Al-6061-SiC-Gr Hybrid Nanocomposites Using Response Surface Methodologies

Metal matrix composites have cemented their applicability in industrial sector by virtue of their excellent mechanical properties. However, work has largely been done on the studies related to macro/microsize particles. This work has been aimed to evaluate the influence of input parameters in turning of Al-6061-SiC-Gr hybrid nanocomposites. This article evaluates the effect of process parameters on the cutting force and average roughness of the machined surface in turning of Al-6061-SiC-Gr nanocomposites. The experiments were designed using CCD, and cutting force and roughness were evaluated using response surface methodology. Statistical models were generated. The results of the study indicated that feed rate and depth of cut are the major influencing factors in descending order for the cutting force. The analysis of surface roughness revealed that both these factors are having identical effect. The cutting speed had little effect on cutting force and an improvement is seen in surface finish. The experiments also revealed that tool wear is negligible for nanocomposites. The software-predicted values and the experimentally obtained values of the responses were acceptably close to each other with an error percentage of less than 5%. Using response surface optimization, optimal combinations of machining parameters are also obtained.