Suitable Machining Parameters Research Articles

Tool Wear in GGG50 Cast Iron Milling Environments

In the present study, the impression of manufacturing parameters on cutting tool tip wear in the milling operation of GGG50 cast iron material with carbide coated cutting tool inserts was investigated. Taguchi orthogonal L18 experimental sequence was applied as the experimental design. As processing parameters; cutting speed, coolant and feed rate were chosen. In the test results, the amount of wear on the cutting tool tips was examined. Optimum processing multiparameters were determined by the Taguchi. Analysis of variance (ANOVA) was used to analyses the effect of input parameters on the cutting tool tip. Consequently, it has been determined that the wear is high in the working environment where the coolant is open and the cutting speed is high. In order to keep the cutting tool tip wear at a minimum level, the most suitable machining parameters are; coolant = closed, cutting speed = 160 mm/min, feed rate = 0.3 mm/rev. It was determined that the tip feed rate had little impression on tool wear.

Machining of additively manufactured alloy 718 in as-built and heat-treated condition: surface integrity and cutting tool wear

AbstractAdditive manufacturing (AM) using powder bed fusion is becoming a mature technology that offers great possibilities and design freedom for manufacturing of near net shape components. However, for many gas turbine and aerospace applications, machining is still required, which motivates further research on the machinability and work piece integrity of additive-manufactured superalloys. In this work, turning tests have been performed on components made with both Powder Bed Fusion for Laser Beam (PBF-LB) and Electron Beam (PBF-EB) in as-built and heat-treated conditions. The two AM processes and the respective heat-treatments have generated different microstructural features that have a great impact on both the tool wear and the work piece surface integrity. The results show that the PBF-EB components have relatively lower geometrical accuracy, a rough surface topography, a coarse microstructure with hard precipitates and low residual stresses after printing. Turning of the PBF-EB material results in high cutting tool wear, which induces moderate tensile surface stresses that are balanced by deep compressive stresses and a superficial deformed surface that is greater for the heat-treated material. In comparison, the PBF-LB components have a higher geometrical accuracy, a relatively smooth topography and a fine microstructure, but with high tensile stresses after printing. Machining of PBF-LB material resulted in higher tool wear for the heat-treated material, increase of 49%, and significantly higher tensile surface stresses followed by shallower compressive stresses below the surface compared to the PBF-EB materials, but with no superficially deformed surface. It is further observed an 87% higher tool wear for PBF-EB in as-built condition and 43% in the heat-treated condition compared to the PBF-LB material. These results show that the selection of cutting tools and cutting settings are critical, which requires the development of suitable machining parameters that are designed for the microstructure of the material.

Influences of Main Machining Process Parameters and Tool Wear on The Machining Damage Generated During Edge Milling CFRP Composites

Machining Carbon Fibre Reinforced Plastics (CFRPs) composites are typically accompanied by the appearance of machining damage which strongly impacts the structural integrity of composite parts during their service lives. Studying the correlation between machining damage and its affected factors has still been an open issue. Hence, it is necessary to do more research. This study focuses on investigating the influences of main process parameters and tool wear phenomenon in terms of machining length on the machining quality which was characterized by the surface roughness criterion, the ten-point max, Rz. A full factorial design of experiments was conducted including three levels of feed speed and two degrees of spindle speed. The results revealed that machining damage was mainly influenced by process parameters at a small machining distance, whereas at a longer machining distance, tool wear had a dominant effect on the machining quality than machining parameters. These findings could provide guidelines for selecting suitable machining parameters to enhance the machining quality of CFRP.

Examination of surface roughness values of 6061-T6 aluminum material after machining and after anodizing process

The use of aluminum material is very common, especially in parts that require precision mechanical processing, such as in the aerospace or defense industry. Since weight reduction in related vehicles or technologies in the fields of aviation and defense industry is one of the biggest goals, the use of aluminum as a metal material has become one of the first targets. The high weight/strength ratio of aluminum compared to steel is one of the main reasons why it is preferred. In addition to these advantages of aluminum materials, we have two expectations for 6061 aluminum parts in most of the projects we work on. The first is to minimize the frictional intensity of the aluminum parts working in contact with each other. The second is to provide the surface roughness of the gasket pressing surface on the surfaces where gaskets are used due to the need for sealing. For both requirements, our goal in this study will be to achieve the surface roughness value as maximum Ra 0.2 after machining and maximum Ra 0.3 after anodizing. The study was carried out with six different cutting tools. These tools, in order; end mill (with one insert) cutter, end mill (with two inserts) cutter, solid end mill, single insert diamond tool, monocrystalline diamond tool and superfinishing tool. Particular attention was paid to the cleanliness of the chemical baths used in the anodizing specific to this study. As a result, it has been observed that much more precise results can be achieved than the currently accepted surface roughness value when suitable machining parameters and optimum anodizing coating parameters are used. By using different cutting parameters with the same tool, by increasing the speed and feed values and decreasing the depth of cut, there is a slight improvement in the surface roughness values. The results of the experiments are presented in table and graphic and are suitable only for observed cutting conditions, used tools and material.

Effects of machining parameters on enhancing Alpha-Beta Titanium alloy using Taguchi-grey relational analysis for aerospace applications

The need for enhancement of productivity and quality of the machined titanium alloy components is paramount to meet the high demands of aerospace parts. Various optimization techniques are being used widely to find suitable machining parameters to improve productivity and reduce surface defects. The present study aims to derive an optimal combination of process parameters during the end milling operation of Ti-6Al-4V alloy for enhancing performance measures which are surface roughness, specific cutting energy and material removal rate (MRR). The Grey relational optimization techniques along with Taguchi method has been utilized for finding the optimum machining parameters. It has been found that the axial depth of cut has the most significant factor on machining characteristics in end milling process of titanium alloy. Using Taguchi-Grey relational analysis technique, optimal process parameter combination has been computed and the performance enhancement using the optimal process combination has been verified by the confirmation test

WEDM Machining Performance of Al Based Metal Matrix Composites Reinforced with Rice Husk Ash

With the enhancement in science and technology, necessity of complex shapes in manufacturing industries becomes essential for more versatile applications. These lead to demand for light weight and durable materials for applications in aerospace, defence, automotive, as well as sports and thermal management. Due to its high-tech structural, functional applications like defence, automobile, aerospace, thermal sensitive materials. Al-Matrix composites are considered as one of those classes of advanced engineering materials. In the present study, Al-RHA (Rice Husk Ash) composites are prepared by powder metallurgy route using 10% and 15% RHA by weight as reinforcement. Presence of abrasive particles leads to difficulty of conventional machining on Al-RHA composites hence non-conventional machining WEDM (Wire-Electric Discharge Machining) has been investigated. Suitable machining parameters for composites using wire EDM have been tried to get maximum material removal rate and speed. Optimizations of experimental parameters have been studied using Taguchi and Anova to standardize the process parameters for machining. Prime process parameters like servo-voltage, pulse-on time and pulse-off-time have been taken into consideration to study cutting quality of Al-RHA Metal matrix Composite using cutting speed as response parameters while effect of RHA weight fraction addition is also considered for evaluation to understand its influence on affecting the response.

Study of self lubrication property of Al/SiC/Graphite hybrid composite during Machining by using artificial neural networks (ANN)

Particulate-Metal Matrix Composites have captivated huge attention for a wide range of engineering applications because of their superior mechanical properties such as high strength, corrosion resistance and wear resistance. However, they lag behind high machinability (due to the presence of hard ceramic reinforcements) and involve expensive processing techniques that restrict their widespread application. The present work is aimed at improving machinability of Al alloy/SiC/graphite hybrid composite developed by a low-cost stir casting technique. Microstructure studies of the hybrid composite were investigated by using SEM and optical microscope. The obtained results were then correlated with mechanical properties to reveal significant enhancement when compared to AA2024 alloy without reinforcements. The machining forces of hybrid composite during drilling were studied by custom-designed strain gauge-based dynamometer. Machinability was improved with graphite incorporation, which has a self-lubricant texture, without much compromising the hardness and tensile strength of the hybrid composite. Further, neural network analysis was adopted by training the model to accurately predict the cutting forces to realize efficient composite with suitable machining parameters.

Optimal cutting parameter specification of newly designed milling tools based on the frequency monitoring

The article deals with the specification of the most suitable machining parameters for three newly designed end mills in the term of stability of the deep groove machining, at which the depth of cut is minimally twice higher the diameter of the cutter. Online vibration analysis was selected as a tool for goal achievement. The partial objective of the first phase of experimental research was to set the boundary conditions of vibrodiagnostics at the specification of the behaviour of three commercially produced milling cutters when the results were compared with the surface roughness achieved at the machining with individual cutting parameters. Vibrodiagnostic conditions were subsequently applied in the second phase of the experiment to determine the most suitable machining parameters of newly designed milling cutters. The Pinnacle VMC 650 CNC machining centre with Fanuc control system was used to perform the experiments. The material of cutters was S-grade sintered carbide, and all the designed cutters were PVD coated with the same AlTiN (aluminium titanium nitride) coating. The machined material was 16MnCr5 (1.7131) steel. The surface roughness analysis after machining by newly designed cutters pointed out that they are better as for the surface quality in comparison with the commercially produced end mills. Finally, it was possible to state that the four-tooth cutter 01-FVT with helix angles (β1 = 39° and β2 = 41°) and tooth pitch (τ1 = 83° and τ2 = 97°) seems to be the best tool for milling deep-shaped grooves among all the tested milling cutters.

Nanometric behaviour of monocrystalline silicon when single point diamond turned—a molecular dynamics and response surface methodology analysis

Hard and brittle materials such as silicon and silicon carbide are widely used in aerospace and integrated circuit. They are often poorly machined owing to non-linearity in machining process and complexities in selecting suitable machining parameters and tool geometry. The experimental difficulty involved in observing nanoscale physical phenomena (i.e. in-process measurement problems, inaccessible contact area of tool and workpiece, and the difficulty of surface analysis) has led to the use of molecular dynamics (MD) and response surface methodology (RSM) to investigate effect of tool edge radius, rake and clearance angles on monocrystalline silicon in this research. The response of subsurface deformation depth (SSD), tool temperature, kinetic friction cutting and thrust forces to tool edge radius, rake and clearance angles showed that SSD increased as the rake angle, edge radius and clearance angle increased while kinetic friction reduced as they increased. The increase in SSD as the clearance angle increased as observed in this study can be associated to the interactive/combined influence of the effects of both edge radius and rake angle.

Inverse modelling of electrochemical machining process using a novel combination of soft computing methods

Selection of optimal and suitable process parameters is a crucial issue in manufacturing processes especially in electrochemical machining (ECM). Since the utmost target is to find suitable machining parameters for gaining desired machining performances, a new hybrid approach has been applied for inverse modelling of ECM process. Four machining inputs, i.e. voltage, tool feed rate, electrolyte flowrate and concentration; and two machining responses, i.e. surface roughness (Ra) and material removal rate (MRR) are presented as input variables and responses, respectively. In the proposed approach, firstly, comprehensive mathematical equations have been established based on response surface methodology (RSM). The two machining performances are modeled in this step with machining parameters. Then, the differential evolution (DE) algorithm has been used for Pareto-based multi-objective optimization. Finally, group method of data handling (GMDH)-type neural networks is used through the Pareto table for inverse modelling. As a result, four models have been developed for each of the four machining parameters; therefore, each machining parameters is determined according to the machining performance as two new design variables. The results demonstrated that the suggested method is a helpful and promising tool for inverse modelling and determining such important relationships between optimized responses and input variables.

Intelligent Machining System Based on CNC Controller Parameter Selection and Optimization

This paper introduces an intelligent machining system (IMS) using an adaptive-network-based fuzzy inference system (ANFIS) predictor and the particle swarm optimization (PSO) algorithm with a hybrid objective function. The proposed IMS provides suitable machining parameters for the users, to satisfy different machining requirements such as accuracy, surface smoothness, and speed. First, the key computer numerical control parameters are selected, and the actual trajectories under different machining parameters obtained by linear scales are collected. These data are analyzed to obtain the machining time, contouring error, and tracking error, corresponding to the speed, milling accuracy, and surface smoothness, respectively. Second, a data-driven approach using ANFIS is established to obtain the corresponding relationship model between the machining parameters and three aforementioned performance indices. Subsequently, to establish the IMS, we combine the trained ANFIS model and establish a hybrid objective function optimization problem solved by PSO algorithm according the specific requirement of the user. Finally, the performance and effectiveness of the proposed machining system is demonstrated by experimental practical machining.

Multi-Cycle Process Signature of Laser-Induced Thermochemical Polishing

Laser-induced thermochemical polishing (LCP) is a non-conventional processing technique that uses laser radiation to smooth the surface of self-passivated metallic parts by initiating a localized anodic material dissolution. This technology can be used to selectively micro-polish without the need for masking or thermal and mechanical stress. However, there is still a lack in understanding the surface quality depending on the applied laser machining parameters. This paper takes up the concept of Process Signatures and interprets the surface smoothing as result of multiple, recurring internal material loads of a constant energy amount. The laser-induced thermal impact is identified as the relevant internal material load and is correlated with the surface roughness. This derives an empirical-based functional relation as multi-cycle Process Signature. The experiment results show an exponential decay in surface roughness with increasing cycle loads for titanium, Ti6Al4V, Nitinol, Stellite 21, and metallic glass. The Process Signature of LCP is a solution to a differential equation with respect to the cycle loads. The paper demonstrates how the multi-cycle Process Signature helps determine suitable machining parameters to predict the surface roughness, as well as to scale the polishing rate.

Effect of Different Cutting Speed towards Machinability of Titanium (Ti6Al4V) Curved Thin Wall using Trochoidal Milling Path

Aircraft parts and components used a lot of titanium as the material for body parts and engines. The materials offer rigidity, strength and light in weight. This unique characteristic was the major advantages in improving the payload capacity and improving the fuel consumption of the jet engines. The problem raised during the machining process of the material. Titanium is a hard material, elastic and poor thermal conductor. As the material is hard, higher machining force is required to perform the machining. Elasticity added the difficulties as it will spring away from the cutting tool which cause the tool to rub instead of cutting that can increased the heat. Thus, machining titanium alloy is expensive and difficult. This preliminary study looks into several machinability aspects and machining parameters for curved thin wall machining profile in the research. Machining accuracy and cutting tool wears were observed during the experiments. There are two set of machining parameters for the machining trials. At the same time, this research able to recommend the suitable machining parameters analysed from the experiments.

Optimasi Parameter Permesinan Terhadap Tingkat Kekasaran Permukaan Aluminium Proses Pembubutan Dengan Metode Taguchi

This study is to determine the most suitable machining parameters to produce optimum surface roughness on turning operations using the Hurco TM20 CNC machine, ISCAR DNMG IC907 insert tool with aluminum 6061 as an object test material. The analysis was carried out using the Taguchi method with objective functions smaller the better and using ANOVA (analysis of variance) that determines which machining parameters have a significant effect on surface roughness. The machining parameters that evaluated are spindle speed, feedrate, and depth of cut. The test results shows that the machining parameters that produce the optimal surface roughness level is on range of 0.28 ± 0.13, and the parameters are spindle speed = 2092 rpm, feedrate = 0.07 mm / ref, dept of cut = 0.5 mm.

Deterministic removal strategy for machine vision assisted scanning micro electrochemical flow cell

Small cavities on a sliding surface can improve lubrication performance, which has been verified by many researchers. Electrochemical machining (ECM) is an effective way to fabricate this kind of small cavities on a large scale. When the diameter and the removal volume for the cavities are specified, it is still required to efficiently determine the appropriate machining parameters. This paper presents a machine vision based control system for an ECM variant: the scanning micro electrochemical flow cell (SMEFC). The aim of this system is to control the diameter of the cavity in real-time. With the assistance of machine vision, fast acquisition of the machining parameters for the specified diameter and the specified removal volume is possible. The system configuration is first explained in detail, including hardware and software configuration and the image processing algorithms. The latter are based on the Shi-Tomasi corner detector and are used for feedback control, stability and symmetry evaluation of the electrolyte droplet. For convenience, all of these functions have been integrated into a self-developed unified G-code interface. Furthermore, the theoretical explanation for controlling the machining process by vacuum gap (VG) tuning has been investigated through a two-phase flow simulation model, which revealed how the VG influences the shear rate and the pressure difference near the meniscus. Finally, a case study shows how to use the proposed strategy to get suitable machining parameters for a cavity with a diameter of 900 μm and a target removal volume of 0.03 mm3. This demonstrates the availability of a deterministic removal strategy.

Experimental studies on Drilling of 410 Stainless Steel

Stainless Steel 410 (SS410) is 12% chromium martensitic steel which can be heat treated to obtain wide range of mechanical properties. Due to its strong corrosion resistance and excellent combination of toughness and strength, it is used for furnace parts, micrometer parts, steam turbine buckets, blades, pump parts, petrochemical equipments, etc.However, during machining of SS410, difficulties are there due to its low thermal conductivity, high ductility and work hardening which can be minimized by using suitable machining parameters and cutting fluids. Therefore, now a day’s research works have been focused towards machinability of SS410 through different machining processes. Among different machining processes, many works have not been started on drilling of SS410. Drilled holes are used to receive screws, bolts, shafts, steam pipes, fitting of furniture and equipment. By considering the above applications and challenges in machining of this material, drilling experiments were conducted on SS410 to analyze the effect of drilling parameters and machining environment on surface roughness and machining time. Experiments were conducted in a jig boring machine with HSS twist drill of ∅10 mm on 5 mm thickness SS410 plate.Drilling tests were carried out as per Taguchi’s L9 array using three cutting speeds (Vc: 11, 16 and 21 m/min) and three feeds (f: 0.02, 0.05 and 0.08 mm/rev) using three different cutting fluids (castor oil, kerosene and coconut oil). Surface roughness (Ra) values were decreased from 7.326 to 2.423 µm with increase in 'Vc' and decrease in 'f' and machining time was increased from 7.4 to 31.5 seconds with increase in 'Vc' and 'f'. Optimum process parameters were identified and verified experimentally to improve the machinability of the SS410. Coconut oil medium gave good machinability results at higher 'Vc' and 'f'.

Design and Machining of the Femoral Component of Total Knee Implant

Manufacturing of medical implants constitutes always a challenge, regarding the constraints involved for these applications, e.g. need for suitable materials or appropriate dimensional tolerances. The aforementioned pose also challenges for the machining process itself, regarding the appropriate machining conditions and machine tool setup and so it is considered as a subject of interest. In the present work, the manufacturing process for knee implants, especially for the femoral component of this type of implants, is discussed, encompassing all the stages from design and planning of each step of the process up to actual machining of the implant component. Finally, the surface quality of the implant after finishing process is assessed for each of the three different finishing processes applied, in order to determine the suitable machining parameters required.

Optimization of Cutting Parameters in Machining GFRP Using End Mill Cutter through DoE and Verification through Genetic Algorithm

This article discusses optimization of critical parameters such as cutting speed, feed, depth of cut and method of machining while machining Glass Fiber Reinforced Plastic (GFRP) in vertical machining center using standard end mill cutter made up of High Speed Steel (HSS) for lesser cutting load, maximum material removal rate for better surface finish and dimensional accuracy through design of experiments. In composite material machining, surface finish is the critical deciding factor in determining surface quality. In this study, as per Taguchi’s L9 orthogonal array, predictable and unpredictable parts are followed to evaluate the consequence of cutting parameters on the machined component. The study includes surface roughness measurement using surface profilometer continued by physical measurement of machined pocket dimension. The experimental results, suggest suitable machining parameters in order to achieve the above target goal. In addition, C++ program is developed to cross check the most favorable machining parameters for maximum material removal rate using genetic algorithm. It is inferred from the study that the genetic algorithm results coincides very closely with the result given by the method of design of experiments.

Investigation on laser drilling of AA6061-TiB2/ZrB2 in situ composites

ABSTRACTLaser beam machining is considered as economic machining process to machine the composite materials. AA6061-TiB2/ZrB2 in situ composites are drilled by using Ytterbium fiber laser machine with input parameters as laser trepanning speed, laser power, and standoff distance. Entry diameter, exit diameter, and taper are responses which are to be measured by metallurgical microscope. The contribution of the paper is to analyze the influence of reinforcement ratio of the composites and machining parameters on the responses. Analysis of the results shows that the entry and exit diameters and taper of unreinforced alloy are less than the composites for all the experimental conditions. Increase in laser trepanning speed decreases the entry and exit diameters whereas increases the taper of the laser drilled hole. Increase in laser power enlarges the entry and exit diameters but reduces the taper of the hole. The increase in the standoff distance reduces the entry and exit diameters of the hole. This investigation helps to find the suitable machining parameters for attaining the desired accuracy of laser drilled holes.

Optimization of Micro-milling Parameters Regarding Burr Size Minimization via RSM and Simulated Annealing Algorithm

In micro-machining process, there are a lot of factors that affect formation of burr along micro-component’s edges. Therefore, finding suitable machining parameters significantly reduces the burr size in micro-products. In the current work, experimental investigations have been performed to study effects of micro-milling parameters (i.e. cutting speed, feed rate and depth of cut) on burr height and burr thickness of the micro-grooves of 316 stainless steel in up milling and down milling operations. The aforementioned factors were varied over their working ranges while other parameters such as tool material, tool condition, lubrication etc. were kept constant. Here, experiments were designed and conducted based on three factors-three levels face centered central composite design. The response surface methodology (RSM) and analysis of variances were applied on generated data to correlate empirical relationships between micro-milling parameters and burr characteristics. Further, the developed RSM models was then associated with principal component analysis and simulated annealing to minimize burr characteristics in both up-milling and down-milling processes, simultaneously. According to optimization results, spindle speed of 15,000 RPM, feed rate 5 mm/tooth and depth of cut of 0.15 is the most optimal factor combination that causes minimum burr sizes.