Fuzzy rule based predictive model for cutting force in turning of reinforced PEEK composite

Carbon fiber reinforced plastics have gained large interest among the community of composites manufactures and consumers due to their excellent adaptability to various industrial applications. In particular, there exists a demand for optimizing machining conditions of mechanical parts made from poly ether ether ketone reinforced with 30% of carbon fiber when using TiN coated cutting tools. In this work, predictive models that describe the relationship between the independent machining variables: cutting speed, feed rate and depth of cut, and the criteria of machinability: cutting force, cutting power and specific cutting pressure were derived. This was achieved by using either classical response surface regression technique or by implementing fuzzy logic models which are based on the compositional rule of inference that establish a parametric relation between a given response and the independent input variables. Effectiveness of these models has been proved by analyzing their coefficients of correlation and by comparing predictions they give with experimental results.     

Optimisation of machining parameters for turning operations based on response surface methodology

Design of experiments has been used to study the effect of the main turning parameters such as feed rate, tool nose radius, cutting speed and depth of cut on the surface roughness of AISI 410 steel. A mathematical prediction model of the surface roughness has been developed in terms of above parameters. The effect of these parameters on the surface roughness has been investigated by using Response Surface Methodology (RSM). Response surface contours were constructed for determining the optimum conditions for a required surface roughness. The developed prediction equation shows that the feed rate is the main factor followed by tool nose radius influences the surface roughness. The surface roughness was found to increase with the increase in the feed and it decreased with increase in the tool nose radius. The verification experiment is carried out to check the validity of the developed model that predicted surface roughness within 6% error.     

Application of response surface methodology in controller fine-tuning

Despite the developments in advanced control techniques, the traditional PID controller is still being used in the majority of industrial processes. However, due to process non-linearities and modelling difficulties, common tuning techniques often yield tuning parameters that are not optimum. The subsequent fine-tuning stage is time-consuming because it is performed by trial and error. Several researchers have suggested that a statistically designed, experimental approach to controller tuning may be fruitful, e.g. Box and Kramer [1].

Using Response Surface Methodology (RSM), a model of the system performance as a function of the tuning parameters can be obtained. RSM can systematically lead the operator to improved tuning and provide a picture of the sensitivity of the process to the tuning parameters. The application of this technique in the fine-tuning of a simulated and real-time process is shown.     

Optimization of tool geometry parameters for turning operations based on the response surface methodology

This investigation focuses on the influence of tool geometry on the surface finish obtained in turning of AISI 1040 steel. In order to find out the effect of tool geometry parameters on the surface roughness during turning, response surface methodology (RSM) was used and a prediction model was developed related to average surface roughness (Ra) using experimental data. The results indicated that the tool nose radius was the dominant factor on the surface roughness. In addition, a good agreement between the predicted and measured surface roughness was observed. Therefore, the developed model can be effectively used to predict the surface roughness on the machining of AISI 1040 steel with in 95% confidence intervals ranges of parameters studied.     

Application of response surface methodology on finding influencing parameters in servo pneumatic system

Servo pneumatic positioning system is a mechatronics approach that enables to use pneumatic cylinders as multi-position actuators. In the present study, an endeavor has been made to simulate the response of pneumatic cylinder parameters. Response surface methodology based analysis have been conducted to evaluate the influences of system parameters such as external load, supply pressure and cross sectional area of cylinder on the response characteristics such as settling time, maximum overshoot, integral time absolute error and maximum force generated using fuzzy rule base models. From the experimental results, it has been inferred that supply pressure has mostly influent nature on determining maximum overshoot and integral of time absolute error (ITAE). It has been observed that cross sectional area and external load has significantly affected the maximum generated force and settling time respectively.     

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.     

Application of the central composite design in optimization of machining parameters in drilling hybrid metal matrix composites

In this study, the application of response surface methodology (RSM) and central composite design (CCD) for modeling, optimization, and an analysis of the influences of dominant machining parameters on thrust force, surface roughness and burr height in the drilling of hybrid metal matrix composites produced through stir casting route. Experiments are carried out using Al 356-aluminum alloy reinforced with silicon carbide of size 25 μm and Mica of size 45 μm. Drilling test is carried out using carbide drill of 6 mm diameter. The design of experiment concept has been used to optimize the experimental conditions. The experimental data are collected based on a three-factor-three-level full central composite design. The multiple regression analysis using RSM is used to establish the input–output relationships of the process. The mathematical models are developed and tested for adequacy using analysis of variance and other adequacy measures using the developed models. The main and interaction effect of the input variables on the predicted responses are investigated. The predicted values and measured values are fairly close, which indicate that the developed models can be effectively used to predict the responses in the drilling of hybrid metal matrix composites. The optimized drilling process parameters have been obtained by numerical optimization using RSM by ensuring the minimum thrust force of 84 N, surface roughness of 1.67 μm, and the burr height of 0.16 mm. After the drilling experiments, a scanning electron microscope (SEM) is used to investigate the machined surface and tool wear.     

Study of cutting force and surface roughness in the turning of polytetrafluoroethylene composites with a polycrystalline diamond tool

Despite the importance of the polytetrafluoroethylene (PTFE) composites in many industrial applications, especially for space industry, very little is known about the machinability of these composites. This paper presents an investigation into the turning of PTFE composites using a polycrystalline diamond tool in order to analyze the effect of the cutting parameters and insert radius on the cutting force and surface roughness. A strain gauge based dynamometer for the main cutting force measurement in turning was constructed. The force signals were captured and processed using a strain data acquisition system based on the Sider8 and CATMAN software. Cutting force and surface roughness were measured through longitudinal turning, according to the experimental plan developed based on the Taguchi methodology. The signal-to-noise ratio and the analysis of variance were applied to the experimental data in order to determine the effect of the process variables on the surface roughness and cutting force, and predictive models have been derived.     

A theoretical and experimental investigation of surface generation in diamond turning of an Al6061/SiCp metal matrix composite

In this paper, the surface generation in ultra-precision diamond turning of Al6061/15SiC_p metal-matrix composites was investigated based on different analytical approaches which include parametric analysis, cutting mechanic analysis, finite element method (FEM) analysis and power spectrum analysis. Parametric analysis was performed to explore the in situ inter-relationships between the process parameters and the surface roughness. The surface properties of the diamond turned surface were extracted and analyzed by the power spectrum analysis of the surface roughness profiles. Different surface generation mechanisms were deduced based on the cutting mechanics and FEM analysis. The results of the theoretical analyses were verified through a series of cutting tests conducted under various cutting conditions and a good correlation between the theoretical and experimental results was obtained.     

On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations

This research work concerns the elaboration of a surface roughness model in the case of hard turning by exploiting the response surface methodology (RSM). The main input parameters of this model are the cutting parameters such as cutting speed, feed rate, depth of cut and tool vibration in radial and in main cutting force directions. The machined material tested is the 42CrMo4 hardened steel by Al₂O₃/TiC mixed ceramic cutting tool under different conditions. The model is able to predict surface roughness of Ra and Rt using an experimental data when machining steels. The combined effects of cutting parameters and tool vibration on surface roughness were investigated while employing the analysis of variance (ANOVA). The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of cutting parameters and tool vibration with respect to announced objectives which are the prediction of surface roughness. The adequacy of the model was verified when plotting the residuals values. The results indicate that the feed rate is the dominant factor affecting the surface roughness, whereas vibrations on both pre-cited directions have a low effect on it. Moreover, a good agreement was observed between the predicted and the experimental surface roughness. Optimal cutting condition and tool vibrations leading to the minimum surface roughness were highlighted.     

System identification of a composite plate using hybrid response surface methodology and particle swarm optimization in time domain

Material properties of composites are identified using a novel hybrid RSM–PSO method in this paper. Different response surface methodology (RSM) methods and particle swarm optimization (PSO) methods are studied initially on a 4 degrees-of-freedom (4DOF) dynamic system on their performance in terms of speed and accuracy. The best combination is used as a hybrid RSM–PSO method to evaluate the performance on system identification of an orthotropic plate along with a 4DOF dynamic system and an isotropic plate. The novelty of the present paper is to identify the composite plate material properties using RSM methods based on time domain signals, which is not hitherto reported in the literature. Also, whereas previous papers have used full factorial design for system identification, here CCDI is used. The input factors (design variables) are the system parameters which are to be identified and the response (objective function) is error sum-of-square of acceleration response with respect to new test system. The performance of the proposed method is also evaluated with the addition of 5% Gaussian noise to simulate the experimental errors. The system parameters of the orthotropic plate were identified with 0% and 0.25% average prediction error with zero and 5% addition of noise respectively by the proposed hybrid RSM–PSO method. It is also showed a much better performance and robustness to noise addition when compared to the other RSM methods in the literature.     

Multi response optimization of machining parameters of drilling Al/SiC metal matrix composite using grey relational analysis in the Taguchi method

This paper presents a new approach for the optimization of drilling parameters on drilling Al/SiC metal matrix composite with multiple responses based on orthogonal array with grey relational analysis. Experiments are conducted on LM25-based aluminium alloy reinforced with green bonded silicon carbide of size 25 μm (10% volume fraction). Drilling tests are carried out using TiN coated HSS twist drills of 10 mm diameter under dry condition. In this study, drilling parameters namely cutting speed, feed and point angle are optimized with the considerations of multi responses such as surface roughness, cutting force and torque. A grey relational grade is obtained from the grey analysis. Based on the grey relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in drilling process can be improved effectively through the new approach.     

A micromechanics analysis of the material removal mechanisms in the cutting of ceramic particle reinforced metal matrix composites

In previous investigations on the cutting of ceramic particle reinforced metal matrix composites using the finite element (FE) method, the particles are usually considered to be rigid. This is inconsistent with the actual situation and thus makes the FE predictions less practical. This paper proposes a micromechanics model to investigate the material removal mechanisms by considering the elasticity and fracture of the particles. It was found that the interaction position of a particle relative to the cutting edge greatly influences the particle and matrix fracture, particle-matrix debonding, surface integrity and cutting forces. There are two particle cracking mechanisms. One is caused by the direct contact of the cutting edge with the particle, and the other is due to the indirect tool-particle interaction through matrix. When the cutting path is below a particle, a smooth surface without subsurface damage can be achieved. When it is passing through a particle, particle fracture mostly occurs. If it is above a particle, subsurface damage is dominated by particle-matrix debonding. Cutting force peaks once the cutting edge is in contact with a particle and the cutting edge is easier to be damaged when the tool is passing through the upper part of the particle.     

A novel surface analytical model for cutting linearization error in fast tool/slow slide servo diamond turning

Fast tool/slow slide servo (FTS/SSS) technology plays an important role in machining freeform surfaces for the modern optics industry. The surface accuracy is a sticking factor that demands the need for a long-standing solution to fabricate ultraprecise freeform surfaces accurately and efficiently. However, the analysis of cutting linearization errors in the cutting direction of surface generation has received little attention. Hence, a novel surface analytical model is developed to evaluate the cutting linearization error of all cutting strategies for surface generation. It also optimizes the number of cutting points to meet accuracy requirements. To validate the theoretical cutting linearization errors, a series of machining experiments on sinusoidal wave grid and micro-lens array surfaces has been conducted. The experimental results demonstrate that these surfaces have successfully achieved the surface accuracy requirement of 1 μm with the implementation of the proposed model. These further credit the capability of the surface analytical model as an effective and accurate tool in improving profile accuracies and meeting accuracy requirements.     

Optimization of end mill tool geometry parameters for Al7075-T6 machining operations based on vibration amplitude by response surface methodology

This paper aims at developing a statistical model to envisage vibration amplitude in terms of geometrical parameters such as radial rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed and axial depth of cut. Experiments were conducted through response surface methodology experimental design. The material chosen is Aluminum (Al 7075-T6) and the tool used was high speed steel end mill cutter with different tool geometry. Two channels piezoelectric accelerometers were used to measure the vibration amplitude. The second order mathematical model in terms of machining parameters was built up to predict the vibration amplitude and ANOVA was used to verify the competency of the model. Further investigation on the direct and interactive effect of the process parameter with vibration amplitude was carried out for the selection of process parameter so that the vibration amplitude was maintained at the minimum which ensures the stability of end milling process. The optimum values obtained from end milling process are Radial rake angle-12°, Nose radius-0.8 mm, Cutting speed-115 m/min, Cutting feed rate-0.04 mm/tooth, axial depth of cut-2.5 mm. The vibration amplitude exhibited negative relationship with radial rake angle and nose radius. The dominant factors on the vibration amplitude are feed rate and depth of cut. Thus it is envisaged that the predictive models in this study could produce values of the vibration amplitude close to the experimental readings with a 95% confidence interval.     

Die design optimization for axisymmetric hot extrusion of metal matrix composites

Strain rate sensitive materials such as Ti alloys, superplastic materials and metal matrix composites (MMCs) can be deformed only in very narrow range of strain rate. In this work, a new process design method for controlling strain rate in workpiece during hot extrusion process is proposed. In this approach, a coupled numerical approach of finite element analysis and optimization technique to optimal profiled die which yields more uniform strain rate distribution in the deforming region is applied to the hot extrusion process of MMCs. Extrusion die profiles are defined by Bezier curves, and FPS (flexible polyhedron search) method is used as optimization technique. The change of relative deviation of strain rate, the progressive development of die profiles with increase of iteration for optimization and the corresponding strain rate distributions are investigated. In addition, the die profiles by optimization scheme for different extrusion ratios are compared with those by analytical solution.     

Analysis of shrinkage and warpage in an injection-molded part with a thin shell feature using the response surface methodology

This paper presents a systematic methodology to analyze the shrinkage and warpage in an injection-molded part with a thin shell feature during the injection molding process. The systematic experimental design based on the response surface methodology (RSM) is applied to identify the effects of machining parameters on the performance of shrinkage and warpage. The experiment plan adopts the centered central composite design (CCD). The quadratic model of RSM associated sequential approximation optimization (SAO) method is used to find the optimum value of machining parameters. One real case study in the injection molding process of polycarbonate/acrylonitrile butadiene styrene (PC/ABS) cell phone shell has been performed to verify the proposed optimum procedure. The mold temperature (M _T), packing time (P _t), packing pressure (P _P) and cooling time (C _t) in the packing stage are considered as machining parameters. The results of analysis of variance (ANOVA) and conducting confirmation experiments demonstrate that the quadratic models of the shrinkage and warpage are fairly well fitted with the experimental values. The individual influences of all machining parameters on the shrinkage and warpage have been analyzed and predicted by the obtained mathematical models. For the manufacture of PC/ABS cell phone shell, the values of shrinkage and warpage present the reduction of 37.8 and 53.9%, respectively, using this optimal procedure.     

Effect of type and percentage of reinforcement for optimization of the cutting force in turning of Aluminium matrix nanocomposites using response surface methodologies

Aluminium matrix composites (AMCs) now hold a significant share of raw materials in many applications. It is of prime importance to study the machinability of such composites so as to enhance their applicability. Sufficient work has been done for studying the machining of AMCs with particle reinforcements of micron range. This paper presents the study of AMCs with particle reinforcement of under micron range i.e. nanoparticles. This paper brings out the results of an experimental investigation of type and weight percent of nanoparticles on the tangential cutting force during turning operation. SiC, Gr and SiC-Gr (in equal proportions) were used with Al-6061 alloy as the matrix phase. The results indicate that composites with SiC require greater cutting force followed by hybrid and then Gr. Increase in the weight percent also significantly affected the magnitude of cutting force. RSM was used first to design and analyze the experiments and then to optimize the turning process and obtain optimal conditions of weight and type of reinforcements for turning operation.     

Optimisation of parameters affecting surface roughness of Co28Cr6Mo medical material during CNC lathe machining by using the Taguchi and RSM methods

This study involves modelling of experimental data of surface roughness of Co28Cr6Mo medical alloy machined on a CNC lathe based on cutting parameters (spindle rotational speed, feed rate, depth of cut and tool tip radius). In order to determine critical states of the cutting parameters variance analysis (ANOVA) was applied while optimisation of the parameters affecting the surface roughness was achieved with the Response Surface Methodology (RSM) that is based on the Taguchi orthogonal test design. The validity of the developed models necessary for estimation of the surface roughness values (Ra, Rz), was approximately 92%. It was found that for Ra 38% of the most effective parameters is on the tool tip radius, followed by 33% on the feed rate whereas for Rz tool tip radius occupied 43% with the feed being at 33% rate. To achieve the minimum surface roughness, the optimum values obtained for spindle rpm, feed rate, depth of cut and tool tip radius were respectively, 318 rpm, 0.1 mm/rev, 0.7 mm and 0.8 mm.     

Application of Taguchi and response surface methodologies for surface roughness in machining glass fiber reinforced plastics by PCD tooling

This paper discusses the use of Taguchi and response surface methodologies for minimizing the surface roughness in machining glass fiber reinforced (GFRP) plastics with a polycrystalline diamond (PCD) tool. The experiments have been conducted using Taguchi’s experimental design technique. The cutting parameters used are cutting speed, feed and depth of cut. The effect of cutting parameters on surface roughness is evaluated and the optimum cutting condition for minimizing the surface roughness is determined. A second-order model has been established between the cutting parameters and surface roughness using response surface methodology. The experimental results reveal that the most significant machining parameter for surface roughness is feed followed by cutting speed. The predicted values and measured values are fairly close, which indicates that the developed model can be effectively used to predict the surface roughness in the machining of GFRP composites. The predicted values are confirmed by using validation experiments.