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.     

Optimization of multi-pass turning operations using genetic algorithms for the selection of cutting conditions and cutting tools with tool-wear effect

A new genetic algorithms-based method is applied for the optimization of cutting conditions and the selection of cutting tools in multi-pass turning operations. A new methodology for the allocation of total depth of cut in multi-pass turning operations is also developed. A comprehensive optimization criterion for multi-pass turning operations is developed and used as the objective function integrating the contributing effects of all major machining performance measures in all passes. The effect of progressive tool wear in optimization processes for multi-pass turning operations is included. Presented case studies demonstrate the application of the new methodology for optimal allocation of total depth of cut as well as optimization of cutting conditions and the selection of cutting tool inserts, and offer a comparison between optimization processes with and without the effect of tool wear in all passes.     

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     

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.     

Application of integrated Taguchi and TOPSIS method for optimization of process parameters for dimensional accuracy in turning of EN25 steel

Abstract

The turning process is one of the fundamental machining operations wherein optimization of parameters leads to better machining performance. This study has applied integrated Taguchi and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to determine the optimum process parameters in turning operation of EN25 steel using coated carbide tools. The process parameters considered are cutting speed, feed rate, and depth of cut. The objective is to minimize circularity and cylindricity simultaneously. An orthogonal array, Signal to Noise (S/N) ratio, and TOPSIS are employed to analyze the effects of input parameters on the output parameters. In this study, a decision matrix is formed using S/N ratios; then the TOPSIS method is used to transmogrify a multi-criteria optimization problem into a single-criterion problem. The result revealed that the proposed method is appropriate for solving multi-criteria optimization of process parameters. Results also showed that cutting speed of 215 m/min, feed rate of 0.07 mm/rev, and depth of cut of 1.5 mm are the optimum combination of process parameters.     

Development of an integrated model for process planning and parameter selection for machining processes

The concept of ‘do it right the first time’ in the machining industry not only expects the best quality products but also at the best possible cost. The cost of machining depends on intelligent process planning and selection of machining parameters such as speed, feed, and depth of cut. The problem of machining parameter selection has received great attention by researchers and many techniques have been developed. A review of these techniques reveals that the selection of the machine and cutting tool is done before the process of cutting parameter selection and process sequencing, and often the selection is based on experience. The current research is an attempt to develop an integrated model (ExIMPro: Expert system based Integrated model for Machining Processes) which finds the sequence of operations with set of machines, tools, and other process parameters to minimise the cost of machining for a cylindrical part. This system consists of existing expert system Machining Parameter SELection (MPSEL) for machine and tool selection and a Microsoft Excel® and Visual Basic® based parameter selection model. The present model focuses on turning and cylindrical grinding operations but other processes can be incorporated with little modification to the software.     

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.     

Performance-based optimal selection of cutting conditions and cutting tools in multipass turning operations using genetic algorithms

The paper presents a new methodology involving the use of genetic algorithms for the selection of optimum cutting conditions and cutting tools in multipass turning operations based on a comprehensive optimization criterion. The optimization objective includes the contributing effects of all major machining performance measures. A hybrid process model, based on metal-cutting theories and numerical interpolation from an experimental database, predicts major machining performance measures. Presented case studies demonstrate the application of the new methodology for the determination of optimum cutting conditions and the selection of cutting tool inserts.     

Development of a knowledge-based expert system for solving metal cutting problems

In metal cutting, the problems need to be well analyzed in order to take precautions before any unexpected results are encountered. This process plays a significant role in achieving consistent quality and in controlling the overall cost of manufacturing. However, it is a difficult task that needs an expert who has a great deal of information and experience in metal cutting. In the present paper, a knowledge-based expert system (COROSolve) that investigates problems that are encountered in three main metal cutting areas: turning, milling and drilling is developed. A great deal of metal cutting operations such as external/internal turning with negative/positive inserts, aluminum turning, parting bars/tubes, grooving, profiling, recessing and threading operations in turning; face milling, square shoulder milling, end milling, multi-purpose milling and side and face milling operations in milling; and drilling operations that use solid drills or drills with indexable inserts in drilling are taken into consideration. COROSolve gives recommendations for the cutting data (i.e., cutting speed, depth of cut, and feed) and updates the problem, cause and remedy database, thus the number of problems that the system can handle is increased.     

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.     

Optimization of multipass turning operations with genetic algorithms

The paper proposes a new optimization technique based on genetic algorithms for the determination of the cutting parameters in multipass machining operations. The cutting process simultaneously considers multipass rough machining and finish machining. The optimum machining parameters are determined by minimizing the unit production cost subject to practical machining constraints. The cutting model formulated is a non-linear-constrained programming (NCP) problem with 20 machining parameter constraints. Experimental results show that the proposed genetic algorithm-based procedure for solving the NCP problem is both effective and efficient, and can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.     

Mathematical models to predict surface finish in fine turning of steel. Part II

This paper outlines further experimental development of mathematical models for predicting RMS surface finish in fine turning operation using TiC coated and cemented tungsten carbide throwaway cutting tools. The five independent variables included are: cutting speed, feed, depth of cut, time of cut of tool, nose radius. Using these five variables at different levels an experimental approach, predictive models for tungsten carbide and titanium coated tungsten carbide tools were developed. A sixth variable, 'the type of cutting tool,' was used to develop a single model for both the TiC coated and cemented carbide cutting tools. AIS1 4140 steel was used as workpiece specimen in the experimental work. Stepwise regression analysis was used in developing the models.     

Prediction of cutting force based on machining parameters on AL7075-T6 aluminum alloy by response surface methodology in end milling

Cutting forces modeling is the basic to understand the cutting process, which should be kept in minimum to reduce tool deflection, vibration, tool wear and optimize the process parameters in order to obtain a high quality product within minimum machining time. In this paper a statistical model has been developed to predict cutting force in terms of geometrical parameters such as rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed and axial depth of cut. Response surface methodology experimental design was employed for conducting experiments. The work piece material is Aluminum (Al 7075-T6) and the tool used is high speed steel end mill cutter with different tool geometry. The cutting forces are measured using three axis milling tool dynamometer. The second order mathematical model in terms of machining parameters is developed for predicting cutting forces. The adequacy of the model is checked by employing ANOVA. The direct effect of the process parameter with cutting forces are analyzed, which helps to select process parameter in order to keep cutting forces minimum, which ensures the stability of end milling process. The study observed that feed rate has the highest statistical and physical influence on cutting force.     

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.     

Analysis of hard turning process:thermal aspects

In manufacturing sector,hard turning has emerged as a vital machining process for cutting hardened steels.Besides many advantages of hard turning operations,one has to implement to achieve close tolerances in terms of surface finish,high product quality,reduced machining time,low operating cost and environmental friendly characteristics.In the study,three dimensional(3D) computer aided engineering(CAE) based simulation of hard turning by using commercial software DEFORM 3D has been compared to the experimental results of stresses,temperatures and tool forces in machining of AISI D3 and AISI H13 steel using mixed ceramic inserts(CC6050).In the following analysis,orthogonal cutting models are proposed,considering several processing parameters such as cutting speed,feed and depth of cut.An exhaustive friction modelling at the tool-work interface is carried out.Work material flow around the cutting edge is carefully modelled with adaptive re-meshing simulation capability of DEFORM 3D.The process simulations are performed at constant feed rate(0.075 mm/r) and cutting speed(155 m/min),and analysis is focused on stresses,forces and temperatures generated during the process of machining.Close agreement is observed between the CAE simulation and experimental values.     

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.     

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.     

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.     

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.     

Determination of optimal subdivision of depth of cut in multipass turning with constraints

Optimal subdivision of total depth of cut during cost optimization in multipass turning is an important decision along with the selection of speed and feed. In this paper a new approach for the determination of the optimal subdivision of depth of cut is presented. The total production cost minimization is achieved by summation of the minimum costs of individual rough passes and the finish pass. The cost of each rough pass or finish pass is independently minimized. The optimal subdivision of total depth of cut is obtained using an integer programming model. The resulting subdivision of depth of cut yields a lower minimum cost than that obtained by using the commonly practised strategy of having minimum depth of cut in the finish pass and removing the remaining depth of cut in number of rough passes of equal size.