Input Machining Parameters Research Articles

Optimization of Milling Operations Using Artificial Neural Networks (ANN) and Simulated Annealing Algorithm (SAA)

Process modelling and optimization are among the two important main issues in manufacturing. Optimization of process parameters not only increases the efficacy for machining economics, but also the product quality to a great extent. In this context, an effort has been made in the current research work to optimize the surface roughness value using Simulated Annealing and Neural Networks taking cutting speed, feed rate, tool rake angle and nose radius as input machining parameters. With the experimental data, objective function in the form of mathematical model is formulated by Response surface methodology. The response model of the system with independent variables is developed in the form of second order equation using regression analysis with the available experimental data and the statistical validation is done. Simulated Annealing and Artificial Neural Network Algorithms are used to optimize the response. The predicted values using genetic algorithm [10], simulated annealing and neural network algorithm are compared and analysed. The predicted values are in good agreement with the experimental values. It can be concluded that the artificial neural network, with the optimum structure, is a helpful approach to predict a target specially the surface roughness of the work piece for different cutting conditions and tool geometry.

GA based Optimization for the Production of Quality Jobs with Minimum Power Consumption in EDM of Hybrid MMCs

Metal matrix composites (MMCs) are commonly used in various manufacturing sectors such as automotive, defence and aerospace sectors due to their higher strength and stiffness, lower weights and resistance to wear and damage. The MMCs reinforced with two particulates i.e. the hybrid MMCs take advantage of both characteristics of reinforcement materials used in MMCs. Here, the experimental studies focus on optimizing the input machining parameters of electric discharge machining (EDM) method during machining of hybrid aluminium based metal matrix composites (AMCs) added with SiC and B4C reinforcement materials. Here pulse current (I), pulse duty factor (s), pulse-on-time (Ton), and gap voltage (V) are the important process parameters used to study their impact on the end results of machining by EDM process namely power consumed (P) and surface roughness (SR). Predictive models were developed and the predicted performance of the model shows an error percentage 6.10% and is 6.84% for SR and P respectively. The results from ANOVA analysis shows that pulse current (I) have significant contribution on both the output parameters. GA is used to as multi objective optimization tool. The GA optimized Pareto optimal fronts provide different optimum cutting conditions for different SR and P values. We need to select the preferred SR value of minimum P to get the optimal machining conditions. The approach is found to be an effective tool and can be developed with minimum effort and help shop floor engineer.

Rotary ultrasonic drilling of Ti6Al4V: Effects of machining parameters and tool diameter

This article presents the use of the rotary ultrasonic machining process for drilling holes in Ti6Al4V alloy which is regarded as a difficult-to-cut material due to its high-temperature strength and low thermal conductivity. This research presents an experimental investigation on the effect of the key rotary ultrasonic machining input parameters including ultrasonic power, spindle speed, feed rate, and the tool diameter on the main output responses including cutting force, hole cylindricity and overcut errors, and tool wear. No previous reports were found in literature to experimentally investigate the effect of the rotary ultrasonic machining parameters and the tool diameter on tool wear, surface integrity, and the accuracy of the drilled holes in Ti6Al4V alloy. The results showed that the rotary ultrasonic machining input parameters within the current ranges can significantly affect the quality of the drilled holes. Through proper selection of input parameters, holes could be drilled in Ti6Al4V alloy with smoothed surface morphology, low tool wear (0.7 mg) and very low cylindricity (2 µm) and overcut (120 µm) errors. Moreover, it was found that the selected level of any input parameter has the ability to significantly affect the influence of the other input parameters on the output responses.

A study on the effect of main process parameters of rotary ultrasonic machining for drilling BK7 glass

BK7 glass is an important engineering material with extensive applications in high-quality and precision transmissive optical components. However, BK7 glass is considered to be a difficult-to-cut material due to its high brittleness and nonconductivity. This article presents the use of rotary ultrasonic machining process for drilling holes in BK7 glass. No previous reports have been found in the literature to experimentally investigate the response of the BK7 glass to rotary ultrasonic drilling. The experimental investigations take into account the effect of the key rotary ultrasonic machining input parameters including the ultrasonic power, spindle speed and feed rate on the output responses of cutting force, exit chipping, surface roughness, hole cylindricity and overcut errors, and surface integrity. The results show that the input parameters within the current ranges can significantly affect the quality of the drilled holes. Moreover, the selected level of any input parameter has the ability to significantly affect the influence of the other input parameters on the output responses. Through proper selection of input parameters, holes could be drilled in BK7 glass with less fractured topography, low surface roughness (1.32 µm), low exit chipping size (0.85), and very low cylindricity (3 µm) and overcut (73.6 µm) errors.

Taguchi-Grey Relational Based Multi-Response Optimization on the Performance of Tool Coating Thickness in Pocket Milling

In this paper, the Taguchi method and Grey relational analysis is used to evaluate the effect of tool coating thickness by machining Titanium Alloy Grade 5 (Ti6Al4V) with Titanium Aluminium Nitrate (TiAlN) Nano coated tools by varying their coating thickness. The pocket milling operation is carried out using the L9 orthogonal array with three levels and four factors design on the CNC vertical machining center. The tool coating thickness, spindle speed, feed rate and depth of cut was selected as machining input parameters for the experiment. The various output parameters such as cycle time, tool wear, surface roughness, material removal rate, micro hardness were found out after machining process. After obtaining all the output parameters the optimization was done by finding out the S/N ratio and grey relation analysis method. According to grey relational grading it was found out that tool coating thickness is the most affected factor for the machining. The confirmation test was done using the optimized value and the results obtained were close to each other.

Mathematical modeling of delamination factor on drilling of ARALL composites through RSM

PurposeThe purpose of this paper is to develop a mathematical model for delamination during drilling by using a response surface methodology (RSM) and also to determine how the input parameters (tool diameter, spindle speed and feed rate) influence the output response (delamination) in machining of fiber metal laminates.Design/methodology/approachThree factors and a three-level central composite design in RSM are used to carry out the experimental investigation. A video measuring system is used to measure the width of maximum damage of the machined FML composite. The “Design Expert 7.0” is used to analyze the data collected graphically. Analysis of variance is carried out to validate the model and for determining the most significant parameter.FindingsThe response surface model is used to predict the input factors influencing the delamination on the machined surfaces of the ARALL composite at different cutting conditions with the chosen range of 95 percent confidence intervals. Analysis of the influences of entire individual input machining parameters on the delamination has been carried out using RSM.Originality/valueThe effect of delamination on drilling of ARALL composites with solid carbide tools of various diameters has not been analyzed yet using RSM.

Experimental investigation and analysis of factors influencing delamination and thrust force during drilling of carbon-fibre reinforced polymer composites

PurposeThe purpose of this paper is to develop a statistical model for delamination and thrust forcing during drilling of carbon-fibre reinforced polymer (CFRP) composites using response surface methodology (RSM) to determine the input parameters (drill speed, drill diameter and feed rate) that influences the output response (delamination and thrust force) in the machining of CFRP composite using solid carbide drill cutter.Design/methodology/approachThree factors, three levels central composite face centred (CCFC) design, is used to conduct the experiments on CFRP by carbide drill. The whole quality evaluation (delamination) was done by video measuring system to measure the width of maximum damage of the machined CFRP composite. The thrust forces during drilling are measured using digital multi-component cutting force (Make: IEICOS, Model: 652) dynamometer. The “Design Expert 7.0” is used to analyse the data collected graphically. An analysis of variance is carried out to validate the model and for determining the most significant parameter.FindingsThe response surface model is used to predict the input factors influencing the delamination and thrust force on the drilled surfaces of CFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. The analysis on the influences of the entire individual input machining parameters on the delamination and thrust force has been carried out using RSM. This investigation revealed that the drill diameter is the eminent factor which affects the responses.Originality/valueIn all, 0.3, 0.4 and 0.5 mm holes have been successfully made on CFRP using vertical machining center, whereas the previous researchers have not drilled hole size less than 1 mm in CFRP using vertical machining center.

Multi-objective optimisation on end milling of hybrid fibre-reinforced polymer composites using GRA

PurposeThis study aimed to develop a mathematical model for delamination and surface roughness during end milling by using grey relational analysis (GRA) and to determine how the input parameters (cutting speed, depth of cut, helix angle and feed rate) influence the output response (delamination and surface roughness) in machining of hybrid glass fibre-reinforced plastic (GFRP) (abaca and glass) composite using solid carbide end mill cutter.Design/methodology/approachThe Four factors, three levels Taguchi orthogonal array design in GRA is used to conduct the experimental investigation. The Shop Vision inspection system is used to measure the width of maximum damage of the machined hybrid GFRP composite. The Shop Handysurf E-35A surface roughness tester is used to measure the surface roughness of the machined hybrid GFRP composite. “Minitab 14” is used to analyse the data collected graphically. Analysis of variance is conducted to validate the model in determining the most significant parameter.FindingsThe GRA is used to predict the input factors influencing the delamination and surface roughness on the machined surfaces of the hybrid GFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. Analysis on the influences of the entire individual input machining parameters on the delamination and surface roughness has been conducted using GRA.Originality/valueEffect of milling of the hybrid GFRP composite on delamination and surface roughness with various helix angle solid carbide end mill has not been analysed yet using the GRA technique.

Machining of tough polyethylene pipe material: surface roughness and cutting temperature optimization

Manufacturing of high-density polyethylene (HDPE) pipes is usually achieved by extrusion processes. However, various joining or fitted parts and mechanical testing samples are prepared by material removal methods. This study focuses on the machinability of the HDPE tough resin used for piping and fittings to make standard test specimens. The experimental plan has been conducted using a Taguchi (L27) orthogonal array. Input machining parameters are cutting speed (V c), feed rate (f), and depth of cut (a p) while output effects are represented by conventional surface roughness criteria (Ra, Rt, and Rz) and the measured cutting temperature (t°). As a result, a second-order model was established between input and output parameters via the response surface methodology (RSM). The development of predictive models is essential for machining of extruded HDPE since few experimental trends and data are available in literature as compared to metals. Optimum cutting conditions are determined using the desirability function approach. It is revealed that the feed rate (f) is the main contributing factor when minimizing surface roughness of HDPE material. The analysis of variance (ANOVA) results showed that the contributions for surface roughness criteria (Ra, Rt, and Rz) are 96.11, 86.92, and 92.22% respectively. On the other hand, cutting temperature is mainly influenced by cutting speed (V c), depth of cut (a p), and the three interactions (V c × f), (V c × a p), and (f × a p). Finally, optimized cutting temperature is discussed for the three main cases, which are lower, targeted, and upper values, i.e., t° minimum, t° targeted = 30 °C, and t° maximum allowable = 32 °C.

Evolution and empirical modeling of compressive residual stress profile after milling, polishing and shot peening for TC17 alloy

Compressive residual stress is important to improve the fatigue life of components. This paper proposed an empirical model to predict the compressive residual stress profile induced by the integration manufacturing processes (firstly milling, then polishing, finally shot peening). An exponential decay function was used to describe the compressive residual stress profile induced by milling process. Moreover, a sinusoidal decay function was proposed to describe the compressive residual stress profile induced by shot peening process. The integration manufacturing processes model was a deterministic function of the combination of exponential decay function, sinusoidal decay function, and their interaction term. Additionally, an impact coefficient was introduced to describe the influence of polishing process on compressive residual stress profile. The coefficients of the proposed models were related to the input machining parameters. Experiments of TC17 alloy were carried out utilizing response surface methodology and full factorial design to construct these models. Flank wear, tool inclination angle, axial depth of cut, shot peening intensity, and shot peening coverage were selected as five input machining parameters. According to the experimental results obtained, the evolution of compressive residual stress profile after the integration manufacturing processes was investigated, and the proposed models had been developed. The empirical model was validated by two extra experiments and a significantly good prediction was achieved.

Optimization of process parameters in drilling of fibre hybrid composite using Taguchi and grey relational analysis

Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.

A comprehensive analysis of three-phase electrolyte conductivity during electrochemical macromachining/micromachining

Electrolyte electrical conductivity plays a vital role as a process parameter during electrochemical macromachining as well as micromachining, especially during anode shape prediction and tool design. Electrolyte electrical conductivity during electrochemical machining varies due to generation of gas bubbles at the tool and workpiece surfaces, sludge due to the dissolution of workpiece material, and heat due to the flow of electric current in the circuit. The electrolyte becomes a multiphase system. A mathematical model to predict the electrolyte electrical conductivity in the multiphase system is presented in this article. An experimental study has also been carried out to validate the proposed model. This model has been applied to study the variation in electrolyte electrical conductivity along the electrolyte flow direction during electrochemical micromachining by measuring change in workpiece thickness. Optimum input machining parameters are also presented at which the change in electrolyte conductivity is negligible in the machining zone.

Process Capability Analysis and Optimization in Turning of 11sMn30 Alloy

This article depicts the optimization of the three prominent turning process parameters, cutting speed, fede rate and depth of cut respectively for obtaining better process capability index(Cpk) of turning operation performed on the 11SMn30 alloy using carbide tool in dry condition.Surface roughness (Ra and Rz) is the output parameter identified in the study to optimize the process capability index(Cpk). The influence of various input parameters of the turning process and their impact on determining the process capability were studied by adopting Taguchi approach. The surface roughness values (Ra and Rz) are optimised individually for optimizing the input machining parameters with the objective of identifying the optimum cutting speed, feed rate and depth of cut which can maximize the turning process capability. The ANOVA result reveals that the feed rate and cutting speed have equal significance in determining the surface roughness (Ra and Rz).

Machinability study of Zr-Cu-Ti metallic glass by micro hole drilling using micro-USM

Metallic glasses are the new class of materials researched and developed extensively for their applications in fabrication of micro components because of their exceptional mechanical properties. Micro machining of metallic glass to the required tolerance without any structural damage is a challenging task. Micro-ultrasonic machining (micro-USM) is a nontraditional machining process which can machine micro features in hard and brittle materials without heat generation. In present research work the machinability of Zr60Cu30Ti10 metallic glass is investigated by micro hole drilling using micro-USM. Machinability study is carried out by analyzing the performance measures like overcut, edge deviation, taper angle, material removal rate (MRR) and tool wear rate (TWR) with respect to the input machining parameters such as feed, abrasive grit size and concentration of abrasive slurry. The edges of the drilled holes are analyzed using scanning electron microscope (SEM) and energy dispersive spectroscopy (EDS) to study the micro structural changes which are taken place in metallic glass due to micro machining. SEM and EDS analysis revealed that the amorphous structure of metallic glass is not affected during machining by micro-USM. A range of feed rate, abrasive grit size and slurry concentration are recognized for micro-USM drilling in metallic glass using multi-objective optimization on the basis of ratio analysis (MOORA) method. The micro-USM drilling in metallic glass provides a new horizon for the precision machining of glassy alloys otherwise which are very difficult to machine conventionally without any change in its amorphous structure.

Mathematical modeling of delamination factor on end milling of hybrid GFRP composites through RSM

Purpose This paper aims to develop a mathematical model for delamination during end milling by using response surface methodology (RSM) and to determine how the input parameters (cutting speed, depth of cut and feed rate) influence the output response (delamination) in machining of hybrid glass fibre reinforced plastic (GFRP; abaca and glass) composite using solid carbide end mill cutter. Design/methodology/approach Three factors, three levels Box–Behnken design in RSM is used to carry out the experimental investigation. Shop microscope Mitutoyo TM-500 is used to measure the width of maximum damage of the machined hybrid GFRP composites. The “Design Expert 8.0” is used to analyse the data collected graphically. Analysis of variance is carried out to validate the model and for determining the most significant parameter. Findings The RSM is used to predict the input factors influencing the delamination on the machined surfaces of hybrid GFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. Analysis on the influences of the entire individual input machining parameters on the delamination has been carried out using RSM. Originality/value Effect of milling of hybrid GFRP composite on delamination with solid carbide end mill has not been analysed yet using RSM.

Optimization of wire electrical discharge machining parameters for cutting electrically conductive boron carbide

In this work, Pure boron carbide (B4C) was consolidated using spark plasma sintering (SPS) at 2050°C with a dwell of 10min under 50MPa uniaxial pressure in Argon atmosphere. The sintered specimen was >99% dense and offered characteristic Vickers hardness and fracture toughness of 31.4GPa and 4.21MPa-m0.5, respectively, at 4.9N indentation load. The specimen showed satisfactory wire electrical discharge machining (WEDM) performance because of its good electrical conductivity. The design of experiment (DOE) was arranged by L32 orthogonal array (OA) between the machining input parameters namely pulse on-time, pulse off-time, pulse peak current, dielectric fluid pressure and servo feed rate and the output responses like machining speed and surface roughness (Ra). Regression models were employed to establish the numerical correlation between the machining parameters and output responses. Experimental observations were utilized to formulate the first-order regression models to predict responses of WEDM. The optimized input parameters were 27 μs pulse on time, 48 μs pulse off time, 180A pulse peak current, 7kg/cm2 water pressure and 2200mm/min servo feed rate for the WEDM performance to produce an optimum machining speed and Ra.

Experimental investigation of machinability characteristics in Al-TiB2metal matrix composite (MMC) based on the Taguchi method with fuzzy logics

Purpose– The purpose of this paper is to develop a mathematical model for metal removal rate and surface roughness through Taguchi method and analyse the influence of the individual input machining parameters (cutting speed, feed rate, helix angle, depth of cut and wt% on the responses in milling of aluminium-titanium diboride metal matrix composite (MMC) with solid carbide end mill cutter coated with nano-crystals.Design/methodology/approach– Taguchi OA is used to optimise the material removal rate (MRR) and Surface Roughness by developing a mathematical model. End Milling is used to create slots by combining various input parameters. Five factors, three-level Taguchi method is employed to carry out the experimental investigation. Fuzzy logic is used to find the optimal cutting factors for surface roughness (Ra) and MRR. The factors considered were weight percentage of TiB2, cutting speed, depth of cut and feed rate. The plan for the experiments and analysis was based on the Taguchi L27 orthogonal array with five factors and three levels. MINITAB 17 software is used for regression, S/N ratio and analysis of variance. MATLAB 7.10.0 is used to perform the fuzzy logics systems.Findings– Using fuzzy logics, multi-response performance index is generated, with which the authors can identify the correct combination of input parameters to get higher MRR and lower surface roughness value with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.Originality/value– Machinability characteristics in Al-TiB2MMC based on the Taguchi method with fuzzy logic has not been analysed previously.

Evaluation of Surface Roughness and Material Removal Rate in End Milling of Complex Shape

In this work, an attempt has been made to analyze the influence of various machining input parameters of CNC end milling process viz. cutting speed, feed rate and depth of cut on machining output variables (surface roughness and material removal rate) during machining complex shape of copper. Three different levels of input parameters were planned as per Taguchi's L9 orthogonal array. The parameters are optimised from analysis of mean (ANOM). Analysis of variance (ANOVA) was employed to investigate the effect of machining parameters on the variables. Results of this study indicate that the depth of cut has the most significant effect on Ra having percentage contribution of 71.06% followed by feed rate and cutting speed having percentage contribution of 23.22% and 2.12% respectively. For material removal rate, it is observed that the percentage contribution of feed rate is maximum i.e. 68.58% followed by depth of cut and cutting speed having percentage contribution of 22.13% and 7.52% respectively. Also, the results revealed that optimum combination of machining parameters which resulted in optimum value of the surface roughness is A3B1C2 i.e. cutting speed of 6000 rpm, feed rate of 500 mm/tooth and depth of Cut of 0.06 mm. Similarly, optimum combination of machining parameters which resulted in optimum value of material removal rate is A1,B3C3 where the values for cutting speed, feed rate and depth of cut are 2000 rpm, 1500 mm/tooth and 0.08 mm respectively.

Investigation of the surface integrity characteristics in wire electrical discharge machining of Inconel 617

The wire electrical discharge machining is one of the best options for machining of high strength materials like Inconel 617. In this study, the effects of wire electrical discharge machining input parameters, such as pulse current and pulse duration on micro-hardness of machined surfaces and subsurface and also density of created surface cracks were investigated. Also the energy dispersive X-ray spectroscopy technique was used to elemental analysis of machined workpiece. The results of this study showed that increasing pulse current and pulse duration, decreases surface micro-hardness while subsurface micro-hardness is increased by increasing pulse duration. Also subsurface micro-hardness is increased by increasing pulse current up to 10 A, but after that the subsurface micro-hardness is decreased. According to the results, the micro-hardness of workpiece is reduced by increasing the distance from the top surface. Also the surface crack density is increased by increasing pulse current and pulse duration first, but it is decreased by increasing more of these two parameters.

Experimental investigation and analysis of machinability behaviour of hybrid GFRP composites during end milling

Purpose This paper aims to develop a mathematical model for analysing surface roughness during end milling by using response surface methodology (RSM) and to determine how the input parameters (cutting speed, depth of cut and feed rate) influence the output parameter (surface roughness) in the machining of hybrid glass fibre reinforced plastic (GFRP; Abaca and Glass) composite by using solid carbide end mill cutter. Design/methodology/approach Three factors and a three-level Box–Behnken design in RSM were used to carry out the experimental investigation. Handysurf E-35A was used to measure the surface roughness of the machined hybrid GFRP composites. The “Design Expert 8.0” was used to analyse the data collected graphically. Analysis of variance was carried out to validate the model and determine the most significant parameter. Findings The response surface model was used to predict the input factors influencing the surface roughness of the machined surfaces of hybrid GFRP composite at different cutting conditions with a chosen range of 95 per cent confidence intervals. Analysis of the influences of the entire individual input machining parameters on the surface roughness carried out using RSM. Originality/value The effect of the milling of hybrid GFRP composite on the surface roughness with solid carbide end mill by using RSM has not been analysed yet.