Machining Feed Rate Research Articles

Mechanistic Model of Fatigue in Ultrasonic Assisted Machining.

Anti-fatigue design in the machining process of aviation material requires advanced processes to enhance the surface integrity and a holistic model which can optimize the process aiming at maximum fatigue life. In the present study, the axial ultrasonic assisted milling process was utilized to machine the Inconel 718 while the process executes the thermomechanical cutting and peening action simultaneously. To optimize the process factors, a hybrid model using a combination of regression analysis and an analytical model was developed to correlate the machining factors, i.e., vibration amplitude, cutting velocity and feed rate to fatigue life. Herein, the former was used to map the process inputs to surface integrity aspects (SIAs), viz. roughness, hardness and residual stress; then, the SIA was mapped to fatigue life through a stress-based approach. The obtained results revealed that there is close agreement between the measured and predicted values of fatigue life where the prediction error is less than two times the dispersion. On the other hand, applying ultrasonic vibration at the highest amplitude together with the maximum feed rate and cutting velocity yield significant improvement in fatigue life, i.e., three times the same condition without ultrasonic vibration in light of the enhancement of compressive residual stress and work hardening of the surface layers.

Application of Taguchi Method, ANOVA Analysis, and TOPSIS Technique in Optimization of Process Parameters for Surface Roughness and Material Removal Rate in Electrochemical Machining of Al-SiC MMCs

Objectives: To evaluate the significance of advanced machining techniques, such as EDM, ECM, and USM, in increasing productivity and overcoming challenges associated with outdated Al-SiC MMC machining. To assess the surface roughness, tool wear, and machining cost implications of employing advanced machining methods for Al-SiC MMCs. Methods The parameters studied were voltage (V), feed rate (F), and electrolyte concentration (C) in electrochemical machining (ECM) of Al/15%SiC composites. To optimise process parameters, the Taguchi method for Design of Experiments (DOE) with an L27 orthogonal array was used. Signal responsiveness is optimised using the Taguchi approach. The Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) is used to find optimal machining settings. Findings: The outcome of this research is that the parameters affecting surface roughness and material removal rate are voltage, electrolyte concentration and feed rate. The minimum Surface Roughness achieved by selecting the best combination level is A2, B3, C3 (smaller is better) i.e., voltage 20 V, feed rate (f) 0.4 mm/min., electrolyte concentration (c) 30 g/lit. The maximum Material Removal Rate achieved by selecting the best combination level is A3, B3, C3 (larger-is-better) i.e., voltage 25V, feed rate (f) 0.4 mm/min., electrolyte concentration (c) 30 g/lit. Novelty : In this work, TOPSIS technique paired with Taguchi method is used which is rarely studied by other researchers. TOPSIS technique provides the best optimal solution as compared to other techniques. Keywords: Al-SiC MMCs, ECM, MRR, Ra, Taguchi method, TOPSIS

INFLUENCE OF MACHINING PARAMETERS AND TOOL GEOMETRY ON TOOL WEAR DURING COBALT CHROMIUM-MOLYBDENUM MICRO DRILLING

Cobalt chromium (CoCr) alloys find extensive use in medical applications due to their unique mechanical properties, such as high strength and low thermal conductivity. However, machining these alloys poses challenges as they are classified as hard-to-cut materials, leading to issues like short tool life, poor surface quality, and low productivity. Rapid tool wear is a significant problem when machining hard alloys, with cutting parameters, drill bit geometry, and types of cutting fluids being the main factors influencing tool wear. In this study, a series of experiments was conducted to investigate the influence of different cutting speeds and tool geometry on tool wear during micro drilling of CoCrMo. A flood cooling system was employed throughout the study, with a constant machining feed rate of 0.1 mm/rev. Three cutting tools with different point angles (118°, 130°, and 140°) and a diameter of 0.2 mm were utilized. The cutting speeds of 50 m/min, 65 m/min, and 80 m/min were varied. A total of 11 runs were performed, with each run consisting of drilling 30 holes. Forces, torques, and tool wear were measured after every subsequent 10 holes drilled. The results indicate that the combination of a 140° point angle and an 80 m/min cutting speed yielded the best performance, exhibiting the lowest force, torque, and tool wear values..

Energy consumption monitoring in DED-LB for enhancing the process sustainability

Energy efficiency is a highly relevant aspect in modern manufacturing processes, not only for economic reasons, but also because of the environmental impact it generates. With the aim of contributing to a more efficient and environmentally friendly manufacturing process, this research analyses the energy consumption of the Laser Directed Energy Deposition (DED-LB).First, the energy efficiency of the laser generator is characterized. In a second step, the deposition process is evaluated, which enables to categorize the process according to the amount of energy required per gram of material deposited, and the mass-deposition efficiency. For this purpose, a 3-level design of experiment (DOE) is performed in order to study the effect of the laser power, mass rate, and machine feed rate on the process efficiency. Besides, a metallographic study is also performed to ensure the metallurgical quality. Energy and material saving of 35% are obtained without influencing the clad quality.

Bead Characterization for Wire Based Laser Directed Energy Deposition Fabrication Process

A three-dimensional, solid object of almost any shape or design can be created using metal additive manufacturing, often known as metal 3D printing. One of the most popular materials utilized in additive manufacturing is metal. The far more complicated procedure of directed energy deposition (DED) is frequently employed to upgrade or repair existing components. DED fabrication process will be able to construct a 3D metal object with consideration of the weld bead characteristics. Without knowing the weld bead characteristics, the mechanical integrity will not hold as the bead size is not suitable for the product. In the current study, we will study the effect of variation of parameters of the DED machine to be able to print in a continuous deposition and we will also investigate the weld bead characteristics printed by the variation of parameters with the use of DED machine. The variation of parameters of the machine are the laser power with the unit of Watt and the feedrate of the machine with the unit of mm per minute. Nine preliminary samples are printed to check whether the bead can be printed in a continuous line or not. The value of variation of parameters that bring about a continuous deposition will be jotted and continued to be taken to bead characterization for study. Six samples were printed, and the bead width and height are calculated based on the variation of parameters. Based on the result, we found that laser power will increase the bead width, but the bead height needs optimal laser power which is at 473 Watt and optimal feedrate which is on 60 mm per min to reach optimal bead height which is at 2.1162 mm. The effect of the machine feedrate on the other hand is inconsistent, thus more samples need to be gathered.

Analysis of Tool Wear and Chip Morphology during Turning of AZ31B Magnesium Alloy under Dry Environment

The present research investigated the turning of AZ31B magnesium alloy in a dry environment using carbide tool inserts coated with tungsten carbonitride (TiCn) and thin alumina (Al2O3). A Box–Behnken design based on fifteen experiments showed a proportional increasing trend of flank wear with all three machining parameters, i.e., cutting speed, feed rate, and depth of cut. The most influential parameter is the cutting speed. A maximum flank wear of 299.34 µm due to excessive adhesion of work material on the tool face was observed at a high cutting speed. Machining at low speed resulted in a significant reduction in tool wear due to less chipping. The tool wear and chip morphology study confirmed the results.

Real-time optimal control of automatic sewing considering fabric geometric shapes

This study aims to improve the sewing accuracy and robustness of a control system for automating sewing operations. In a previous study, we experimentally demonstrated a control system for automating the butt seaming of two fabric pieces (one curved and another straight) into a 3D shape. However, because the control method was obtained through trial and error, there were problems, such as low sewing accuracy and low robustness, including sewing failure when changing the sewing machine feed rate. Therefore, this study improved the sewing accuracy using a real-time optimal control. Furthermore, robustness was enhanced using the feed rate and geometric shapes of the fabrics. The experimental results confirm that the proposed method improved sewing accuracy and robustness.

Design method and experimental study of a cathode tool with an extremely high leveling ratio for electrochemical machining of blisk

To obtain final parts with the desired dimensional accuracy and repeatability via electrochemical machining (ECM), the machining process must enter an ECM balanced state. However, for the ECM processing of blisk, a key component of aerospace engines, the surface of the blade blank often has an uneven allowance distribution due to the narrow passage of the cascade. It is difficult to remedy this issue in subsequent processing steps, which is necessary to ensure the dimensional accuracy and repeatability of the final blade profile. To solve this problem, electrolytic machining must be preceded by electrolytic shaping, which requires cathode tools with large leveling ratios to quickly homogenize the blank surface of the blade. In this study, to obtain a cathode tool with an extremely high leveling ratio, a design method based on the variation in the electrode gap in the non-equilibrium electrolytic state is proposed, and a dissolution model based on the non-equilibrium state is established. In this design method, the allowance on the blank to be machined is first divided into many discrete allowances with the normal direction. The initial machining clearance, feed rate, and total machining time are then calculated using classical ECM equilibrium state theory based on the maximum allowance. Meanwhile, the point coordinates of the cathode tool at maximum allowance can be determined. The non-equilibrium model can then be used to calculate the relative coordinate positions corresponding to the remaining discrete allowances. Finally, the entire cathode tool profile is designed. Simulations, fundamental experiments, and blisk unit workpiece experiments were carried out to validate the design approach. In the simulated processing of the plane workpiece, the leveling ratio of the cathode tool designed by the proposed method (0.77) was 83% higher than that of the cathode tool designed using the traditional method. The simulation results were confirmed by processing experiments. In the machining of blisk unit workpieces with complex curved surfaces, the leveling ratios of the convex and concave parts of the blade machined using the proposed cathode tool respectively reached 0.75 and 0.54, which are 75% and 38% higher than those obtained using the traditional method. This new cathode design method and machining technology can significantly improve the surface allowance distribution of blank before electrolytic finishing. It is helpful for finishing machine to enter electrolytic equilibrium state. Finally, the final blade profile accuracy can be guaranteed and repeated errors can be reduced.

Optimization of Hole quality parameters using TOPSIS method in drilling of GFRP composite

The attractive mechanical properties and light weight to strength ratio Glass Fiber Reinforced Plastic (GFRP) composites are preferred in automobile and aerospace industries. Drilling process is one of the basic and important manufacturing processes. Drilling of GFRP and its issues with hole quality are fiber crack, roughness of surface, dimensional error and delamination. In this work, the effect of three different drill (Slot type, twist type and brad type) and process parameters (machining speed and feed rate) on hole quality error is analyzed. Hole quality parameters, chosen are roundness error, roughness of the machined area, delamination factor and diameter deviation. Simultaneous optimization of multiple objectives is difficult task. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used for optimization process parameters and minimize the hole quality error during drilling of GFRP composite. The result revealed that spur type drill with higher range of spindle speed was provided less error in the drilled holes. Also, TOPSIS procedure has minimum computational time because of its less computational steps and highly preferrable for various decision-making problems in manufacturing industry. Hole quality error is directly influencing the assembly accuracy and its minimization is important one.

Sustainable Dry Machining of Stainless Steel with Microwave-Treated Tungsten Carbide Cutting Tools.

This paper presents a research investigation conducted on the turning of stainless steel 316 material under a dry environment using microwave-treated cutting tool inserts. Plain tungsten carbide WC tool inserts were exposed to microwave treatment for enhancement of their performance characteristics. It was found that a 20-min microwave treatment resulted in the best tool hardness and metallurgical characteristics. These tool inserts have been used to machine SS 316 material following the Taguchi L9 design of experimental techniques. A total of eighteen experiments have been conducted by varying three main machining parameters, i.e., cutting speed, feed rate, and depth of cut, at three levels per parameter. It has been found that tool flank wear increased with all three parameters and surface roughness decreased. At the longest dept of cut, surface roughness increased. An abrasion wear mechanism was found on the tool flank face at a high machining speed and adhesion at low speed. Chips with a helical shape and low serrations have been investigated. Turning SS 316 at optimum machining parameters of 170 m/min cutting speed, 0.2 mm/rev feed rate, and 1 mm depth of cut, as obtained by the multiperformance optimization technique grey relational analysis, resulted in the best values of all machinability indicators: 242.21 µm tool flank wear, 3.81 µm mean roughness depth, and 34,000 mm3/min material removal rate, at a single parameter setting. In terms of research achievements, the percentage reduction in surface roughness is approximately 30% and represents an almost ten-fold improvement in the material removal rate. The combination of machining parameters of 70 m/min cutting speed, 0.1 mm/rev feed rate, and 0.5 mm depth of cut is optimum for the lowest value of tool flank wear when considered for single parameter optimization.

Analisa Keausan Mata Pahat Kardiba dan Kedalaman Potong pada Proses Milling Baja SKD 11

Not all machining processes are carried out using a CNC (Computer Numerical Control) system, but are started by using conventional machines that do not require a high level of accuracy. In accordance with the advantages it has for product accuracy, most CNC systems are intended for finishing processes. The level of surface roughness of a product is indeed adjusted to the usefulness of the product itself, but it cannot be denied that the better the quality produced, the higher the selling value of the product. This study aims to determine the effect of variations in depth of cut on the wear value of the EndMill Carbide chisel on the SKD 11 steel material used in the manufacture of Dies. This study used a literature study type method, research procedures, first material preparation, second specimen machining procedure, recorded cutting time, looked at the surface of the tool after the cutting process was carried out using a microscope, determined the condition of the tool damage and then re-cut until the tool could not be used again or wear has reached 0.3 mm, then record the cutting length every 5 minutes of cutting and finally data analysis. Based on the results of the test data obtained, it shows that the wear of the carbide endmill (VB) chisel blade from the comparison of machining time and feed rate has a graph, namely if the cutting time is longer, namely 30 minutes. The higher the cutting length, the faster the wear value occurs and vice versa the lower the cutting length value, the smaller the wear value achieved. The type of endmill carbide cutting tool wear that occurs is flank wear.

Machine Learning Facilitates the Application of Electrochemically Induced Precipitation for the Removal of Phosphorous

Electrochemically induced precipitation methods for phosphorous removal and recovery have received increasing attention, which have the advantage of achieving phosphorous recovery without the use of additional chemicals. In this work, a novel integrated electrochemical fixed bed packed with magnetite (EPM) for the removal of phosphorous was designed and constructed. To achieve control automatically, machine learning technology was utilized in this study. Accurately predicting the phosphorous removal efficiency and cost is the goal for model training and development. The artificial neural network (ANN), random forest (RF), and multiple linear regression (MLR) models were implemented using the experimental data of EPM. The MLR model showed poor prediction accuracy, indicating that the linear model is insufficient to describe the EPM process. ANN and RF achieved an acceptable accuracy in predicting phosphorous removal and cost, which were optimized using a grid-searching method and deeply analyzed by variable importance to identify the importance of variables. According to the machine learning model, the current, feed rate, and Ca2+ concentration have a significant role in the efficiency and cost of phosphorous removal. Future research should focus on data collection for electrochemical systems in actual operations, as well as designing and optimizing machine learning models suitable to electrochemical systems on automation.

Multi-Objective Optimization of Input Machining Parameters to Machined AISI D2 Tool Steel Material

Poor surface finish on die and mould transfers the bad quality to processed parts. High surface roughness is an example of bad surface finish that is normally reduced by manual polishing after conventional milling machining process. Therefore, in order to avoid disadvantages by manual polishing and disadvantage by the machining, a sequence of two machining operations is proposed. The main operation is run by the machining and followed by Rotary Ultrasonic Machining Assisted Milling (RUMAM). However, this sequence operation requires optimum input parameters to generate the lowest surface roughness. Hence, this paper aims to optimize the input parameters for both machining operations by three soft-computing approaches – Genetic Algorithm, Tabu Search, and Particle Swarm Optimization. The method adopted in this paper begins with a fitness function development, optimization approach usage and ends up with result evaluation and validation. The soft-computing approaches result outperforms the experiment result in having minimum surface roughness. Based on the findings, the conclusion suggests that the lower surface roughness can be obtained by applying the input parameters at maximum for the cutting speed and vibration frequency, and at minimum for machining feed rate. This finding assists manufacturers to apply proper input values to obtain parts with minimum surface roughness.

L-DED numerical model for sensor embedding

Sensor integration is one of the drivers in modern industry for obtaining real-time data and enabling transition to Industry 4.0. Sensor integration on production systems and tooling is one of the key points for data acquisition. Although several techniques can be applied for sensor integration, Laser Directed Energy Deposition (L-DED) is becoming one of the most relevant, since the sensor can be placed into the manufactured layer-by-layer structure. However, the thermal nature of the L-DED poses a challenge when heat-sensitive parts, such as thermocouples, are to be embedded. In order to ease parametrization and anticipate the behavior of the L-DED process, modeling is an interesting tool that has attracted the attention of academia in the last years. Nevertheless, most models are highly complex and focused on a very local scale or include symmetry assumptions that restrict their use for real applications. In view of this need, in the present research work a thermal model that considers material addition and determines the clad geometry is developed. The model includes an automatic meshing algorithm that adapts the element size by refining the mesh where required. Besides, the model enables 5 axis L-DED, in-process variation of the machine feed rate, and allows to switch on and off the laser to simulate not only the material deposition, but also the idle movements. The model is validated in two steps: single clad deposition on a flat surface and single clads on a 0.3 mm thick thermocouple sheath. Finally, the validated model is used for defining the maximum laser power for embedding virtually a 3 mm diameter K-type thermocouple with a 0.3 mm thick sheath. The results of the simulation are also corroborated by experimental integration of the same thermocouple, which functionality is tested afterwards. Therefore, the L-DED modeling is proven to be an effective tool for manufacturing complex parts on the first try.

Hard turning of AISI D2 steel with cubic boron nitride cutting inserts

Industries use heat treated steel for various components due to its strength and other mechanical properties. Usually hardening of machining is carried out by energy and cost intensive grinding process. Recently, hard machining has replaced grinding for certain specific applications. In this study, Cubic boron nitride (CBN) of specification CNMG120408is employed to machine AISI D2 steel of 46 HRC hardness. Nine machining experiments established by L9 orthogonal array were conducted. Surface roughness and cutting force were taken as response variables. From the signal to noise ratio analysis, the optimum combination of cutting process parameters for surface roughness is found out to be 80 m/min (Cutting speed) 0.109 mm/rev (Feed) and 0.1 mm (depth of cut). From Analysis of variance (ANOVA), the share made by every process parameter on the machining performance is found out for this CBN tool-work piece combination. Feed rate has the maximum contribution (56 %) for main cutting force while Cutting speed has the maximum contribution (72 %) for surface roughness. Cutting speed exerts greater influence on surface finish compared to feed rate in hard machining.

Online interpolation of 5-axis machining toolpaths with global blending

Modern high-speed 5-axis machining toolpaths consist of densely discretized tool center points (TCP) and tool orientation vectors (TOV). This paper presents a global interpolation technique that can blend very densely discretized 5-axis toolpaths within user defined blending tolerance and interpolate them in real-time using minimal computational expense. Instead of geometric splines, Finite Impulse Response (FIR) low-pass filtering is used to blend TCP and TOV and interpolate them smoothly for synchronized 5-axis motion generation. Global blending errors of TCP and TOV are modeled based on path geometry, tool motion kinematics and dynamics of the FIR filter. These global blending errors are confined by modulating the machining feedrate. In other words, machining feedrate is adjusted, i.e. reduced and increased, to control the global blending accuracy along the 5-axis machining toolpath. A windowing scheme is proposed to solve this new feedrate scheduling problem. Since the proposed interpolation method is based on digital filtering (convolution), it enables online (real-time) interpolation of densely discretized 5-axis machining toolpaths in a real-time and at the same time provides control over the frequency spectrum of interpolated trajectories. The proposed global blending strategy delivers significant reduction in machining cycle-time as compared to conventional local blending techniques and generates smoother, frequency-controlled trajectories with a fraction of the computational effort required as compared to spline-based interpolation. Illustrative examples and experimental results are provided to showcase functionality and validate effectiveness of the proposed technique.

Development of a Snake Gourd Seed Decorticating Machine

Aims: A snake gourd seeds sheller which comprises of hopper, decorticating chamber, and the cleaning chamber was designed, fabricated and evaluated in this study.
 Methodology: A 3-level factorial response surface methodology (RSM) of design expert version 6.0.8 of 2002 was used to identify the relationship between the response functions and the process variables of the device. The factors considered are shaft speed (300, 350, 400 rpm), soaking time (8, 15, and 20 minutes.), hammer diameter (115, 135 and 150 mm) and feed rate (90, 120, 150 kg/hr.) in the determination of shelling efficiency while air speed (2, 4, and 6 m/s) and angle of air injection (20, 40, 600) were used in the determination of cleaning efficiency.
 Results: The shelling efficiency was observed to increase with increase in hammer speed, hammer diameter and soaking time but decreased with increase in machine feed rate. The maximum shelling efficiency of 97.61% was recorded when the soaking time is 20 minutes, hammer speed is 400 rpm, hammer diameter is 150 mm and feeding rate is 90 kg/hr. The cleaning efficiency increases with increase in air speed and angle of air injection. The cleaning efficiency of the machine was found to be 92.5 % when the angle of injection and air speed is 600 and 5.0 m/s respectively. The effect of the speed and the angle of injection was found to be significant (p<0.05).
 Conclusion: The study concluded that with the result of the performance evaluation of the machine, it is suitable for inclusion in the process line for the seed and hence its potential could be harnessed.

Experimental study on machining properties of a high-strength composite material with Ti-555 titanium alloy matrix

Targeted at a composite material with a novel Ti-555 high-strength titanium alloy matrix developed using the method of "reinforcement wet grinding-spark plasma sintering-heat treatment", a study is conducted on the machining performance during the machining process. Orthogonal experiment method, single factor experiment comparison method and empirical model analysis method are adopted to explore the pattern of changes in cutting force, surface roughness and the wearing of cutting tools under different parameters. There are a number of points revealed by the experimental results as follows. In the machining process, due to the high-strength and hardness of the composite material with Ti-555 high-strength titanium alloy matrix, the selection of machining parameters is limited, and the highest machining speed reaches up to merely 45 m/min. Most affected by the depth of machining, the cutting force increases as machining depth and feed rate are on the rise. The empirical model of cutting force is constructed using the least square regression method, the level of significance is high as indicated by the F test method. and feed rate will make difference to surface roughness. Not only will a greater feed rate increase roughness value, it will also aggravate the wearing of the tool.

Accurate prediction of machining feedrate and cycle times considering interpolator dynamics

This paper presents an accurate machining feedrate prediction technique by modelling the trajectory generation behaviour of modern CNC machine tools. Typically, CAM systems simulate machines’ motion based on the commanded feedrate and the path geometry. Such approach does not consider the feed planning and interpolation strategy of the machine’s numerical control (NC) system. In this study, trajectory generation behaviour of the NC system is modelled and accurate cycle time prediction for complex machining toolpaths is realised. NC system’s linear interpolation dynamics and commanded axis kinematic profiles are predicted by using finite impulse response (FIR)–based low-pass filters. The corner blending behaviour during non-stop interpolation of linear segments is modelled, and for the first time, the minimum cornering feedrate that satisfies both the tolerance and machining constraints has been calculated analytically for 3-axis toolpaths of any geometry. The proposed method is applied to 4 different case studies including complex machining toolpaths. Experimental validations show actual cycle times can be estimated with > 90% accuracy, greatly outperforming CAM-based predictions. It is expected that the proposed approach will help improve the accuracy of virtual machining models and support businesses’ decision-making when costing machining processes.

SIS Parameters Optimization and Reliable Analysis to Achieve Reduced roughness of PA12 Parts

Selective inhibition sintering (SIS) results in easy, flexible, fast and cost-efficient fabrication of functional parts by using powder material for various applications. The functional part is important for operational examination by fabricating the part unswervingly from CAD data. However, poor surface quality is the major disadvantage in SIS procedure. Selection procedure of optimal operating parameters plays a major role in the fabrication of end products. The present study discusses the effect of key contributing operating parameters on the surface quality of the Polyamide parts fabricated by the SIS process. The parameters like heater power (HP), layer thickness (LT), heater feed rate (HFR), machine feed rate (MFR) and bed temperature (BT) were considered in this study. Face-Centered Central (FCC) design was employed as a statistical technique to set the optimal inhibition sintering parameters. Different mathematical models had also been generated in order to develop a relationship between influencing parameters. Further, adequacies of generated models were validated by analysis of variance (ANOVA) approach. Moreover, to decide the survival rate of the SIS parts for industrial applications, the surface roughness reliability with higher error ([Formula: see text]%) was tested by using Weibull statistics. It was observed that HP, LT and HFR are contributing more to increase surface roughness.