Experimental investigation of cutting parameters influence on surface roughness and cutting forces in hard turning of X38CrMoV5-1 with CBN tool

This experimental investigation was conducted to determine the effects of cutting conditions on surface roughness and cutting forces in hard turning of X38CrMoV5-1. This steel was hardened at 50 HRC and machined with CBN tool. This is employed for the manufacture of helicopter rotor blades and forging dies. Combined effects of three cutting parameters, namely cutting speed, feed rate and depth of cut, on the six performance outputs-surface roughness parameters and cutting force components, are explored by analysis of variance (ANOVA). Optimal cutting conditions for each performance level are established. The relationship between the variables and the technological parameters is determined through the response surface methodology (RSM), using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed.     

Optimization of Tool Geometry and Cutting Parameters for Hard Turning

In the hard-turning process, tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. So reliable models and methods are required for the prediction of the output performance of the process. In the present work, experimental investigation has been conducted to see the effect of the tool geometry (effective rake angle and nose radius) and cutting conditions (cutting speed and feed) on the surface finish during the hard turning of the bearing steel. First- and second-order mathematical models were developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using genetic algorithms. The genetic algorithm program gives minimum values of surface roughness and their respective optimal conditions.     

Formulation of Surface Roughness Models for Machining Nickel Super Alloy with Different Tools

This paper presents a study of the development of surface roughness models for turning supermet 718 nickel super alloy (300 BHN), using different tool materials namely; CBN (SANDVIK CB50), Carbide (SANDVIK HIP k10), and ceramic (SANDVIK CC680) under dry cutting conditions and a constant nose radius. The models are developed in terms of cutting speed, feed rate, and depth of cut. These variables were investigated using design of experiments and utilization of the response surface methodology (RSM). A separate surface roughness model corresponding to each tool material is established, tested and reported.     

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.     

Investigating the Tool Life, Cutting Force Components, and Surface Roughness of AISI 302 Stainless Steel Material Under Oblique Machining

The aim of this work is to investigate the machinability of austenitic AISI 302 stainless steel under oblique cutting. This can be achieved by studying the cutting forces, analysis of tool life, and investigation of the surface roughness at different cutting conditions and nose radius. A factorial experiment and analysis of variance technique are used in which several factors are evaluated for their effects on each level. The machinability experiments are based on design of experiments to obtain empirical equations for machinability values for machining conditions such as speed, feed, depth of cut, and nose radius. The parameters considered in the experiments were optimized to attain maximum tool life using a response graph and a response table. Based on the response models, dual response contours (tool life and surface roughness as a response and metal removal rate) have been plotted in cutting speed-feed planes. Evaluating the effect of the predominant variables influencing the value of tool life is very important for improving the machined product quality.     

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     

Multi machining output—multi independent variable turning research by response surface methodology

A finish turning case is presented where an increase in tool Life was obtained without sacrificing surface finish. This was obtained by developing mathematical models for tool life and surface roughness in terms of the cutting speed, feed and depth of cut. Their contours were obtained utilizing PL 1 language and an IBM 360/50 computer, then the contours were superimposed in order to select the proper combination of cutting conditions.     

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.     

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.     

An experimental analysis of effective high speed turning of superalloy Inconel 718

Superalloy, Inconel 718 is widely used in the sophisticated applications due to its unique properties. However, machining of such superior material is difficult and costly due its peculiar characteristics. The present article is an attempt to suggest Taguchi optimization technique to study the machinability of Inconel 718 with respect to cutting force, cutting temperature, and tool life in high speed turning of Inconel 718 using cemented tungsten carbide (K20) cutting tool. Therefore, the objective of this work is divided into two phases: (i) to demonstrate a correlation between cutting speed, feed, and depth of cut with respect to cutting force, cutting temperature, and tool life in a process control of high speed turning of Inconel 718 in order to identify the optimum combination of cutting parameters; (ii) to show the effect of high speed cutting parameters on the tool wear mechanism and chip analysis. These correlations were obtained by multiple linear regressions. The confirmation tests were carried out to make a comparison between the experimental results and mathematical models proposed. The proposed models agree well with the experimental results.     

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.     

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.     

Surface roughness predictive modeling: neural networks versus regression

Surface roughness plays an important role in product quality and manufacturing process planning. This research focuses on developing an empirical model for surface roughness prediction in finish turning. The model considers the following working parameters: work-piece hardness (material), feed, cutter nose radius, spindle speed and depth of cut. Two competing data mining techniques, nonlinear regression analysis and computational neural networks, are applied in developing the empirical models. The values of surface roughness predicted by these models are then compared with those from some of the representative models in the literature. Metal cutting experiments and tests of hypothesis demonstrate that the models developed in this research have a satisfactory goodness of fit. It has also presented a rigorous procedure for model validation and model comparison. In addition, some future research directions are outlined.     

Effect of machining parameters on surface roughness and material removal rate in finish turning of ±30° glass fibre reinforced polymer pipes

This paper studies the effect of varying machining parameters in turning on surface roughness and material removal rate (m.r.r.) for ±30° filament wound glass fibre reinforced polymers (GFRP) in turning operations using coated tungsten carbide inserts under dry cutting conditions. The paper describes the development of an empirical model for turning GFRP utilising factorial experiments. Second order predictive model covering speed, feed, depth of cut and tool nose radius has been developed at 95% confidence interval for surface roughness and material removal rate. Contour plots of the surface roughness and m.r.r. for different machining conditions have been generated from the empirical equations. Overlaid contour graph help in obtaining iso-value of roughness for different values of m.r.r.     

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.     

Determination of Optimal Parameters for SKD11 CNC Turning Process

This study investigated the optimization of a CNC turning process for SKD11 (JIS). The design of experiments (DOE) method with an orthogonal array was applied. Nine experimental runs were performed based on the orthogonal array. The surface properties of roughness average and roughness maximum and the roundness were studied; the analysis of variance (ANOVA) was adapted to investigate which parameters had the most influence on the CNC turning process for SKD11 (JIS). Also, models for predictions of the roughness average, roughness maximum, and roundness had been developed in terms of cutting speed, feed rate, depth of cut, and the mixture ratio of cutting fluids.     

Fuzzy Modeling and Analysis of Machining Parameters in Machining Titanium Alloy

Titanium alloys are utilized in many engineering fields such as chemical, industrial, marine, and aerospace due to their unique properties. Machining of these materials causes severe problems. At high temperatures, they become chemically active and tend to react with tool materials. In the present study, fuzzy logic (a tool in artificial intelligence) is used for the prediction of cutting parameters in turning titanium alloy (Ti-6Al-4V). The parameters considered in this study are cutting speed, feed, and the depth of cut. Fuzzy rule-based modeling is employed for prediction of tool flank wear, surface roughness, and specific cutting pressure in machining of titanium alloy. These models can be effectively used to predict the tool flank wear, surface roughness, and specific cutting pressure in machining of titanium alloys. Analysis of the influences of the individual important machining parameters on the responses have been carried out and presented in this study.     

Design,evaluation and optimisation of cutter path strategies when high speed machining hardened mould and die materials

The use of high speed milling (HSM) for the production of moulds and dies is becoming more widespread. Critical aspects of the technology include cutting tools, machinability data, cutter path generation and technology. Much published information exists on cutting tools and related data (cutting speeds, feed rates, depths of cut, etc.). However, relatively little information has been published on the optimisation of cutter paths for this application. Most of the research work is mainly focused on cutter path generation with the main aim on reducing production time. Work with regards to cutter path evaluation and optimisation on tool wear, tool life, surface integrity and relevant workpiece machinability characteristics are scant. Therefore, a detailed knowledge on the evaluation of cutter path when high speed rough and finish milling is essential in order to improve productivity and surface quality. The paper details techniques used to reduce machining times and improve workpiece surface roughness/accuracy when HSM hardened mould and die materials. Optimisation routines are considered for the roughing and finishing of cavities. The effects of machining parameters notably feed rate adaptation techniques and cutting tools are presented.     

FACTORS AFFECTING SURFACE ROUGHNESS IN FINISH TURNING OF GRAY CAST IRON

The objective of this study was to ascertain the effect of tool wear on surface roughness and develop a more thorough understanding of the process variables affecting surface roughness. Experimental data from a finish turning operation on gray cast iron with uncoated tungsten carbide tools was used to develop a model for surface roughness as a function of cutting speed, feed rate, nose radius of the tool and the amount of wear on the tool. The experiment was statistically designed to minimize the number of runs. Tool wear was treated as a variable notwithstanding the fact that it is one of the responses of the process. The results showed that surface roughness is significantly affected by tool wear and the interactions between tool wear and other variables like cutting speed, feed rate and nose radius. The results also provide better insight into the problem of “adaptive” process control for finish turning operations.     

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.