Advances in difficult-to-cut materials: fabrication, properties, process mechanics, and surface integrity assessment. This collection of papers also presents that – in addition to new manufacturing technologies – the current direction of research in hard-to-cut materials includes new processing techniques.
The Influence of Exposure Energy Density on Porosity and Microhardness of the SLM Additive
Manufactured Elements
- Introduction
- Material
- Experiments
- Porosity Analysis Results and Discussion
- Microhardness Analysis Results and Discussion
- Final Conclusions
Figures 6 and 7 show the changes in porosity in relation to the modification of hatch distance and exposure speed for all specimens. Similar to the porosity research, the influence of laser power, exposure speed and aperture distance (Figure 10) on the distribution of microhardness in the specimens was determined.
Synthesis, Characterization, Corrosion Resistance and In-Vitro Bioactivity Behavior of Biodegradable
Orthopaedic Applications
Materials and Methods
The corrosion characteristics of the synthesized composites were analyzed by potentiodynamic polarization test through an electrochemical system (Gamry 1000E, Potentiostat/Galvanostat, Gamry Instruments, Warminster, PA, USA) in simulated body fluids (9 g/L NaCl, 9 g/L, g24.4, 0.4Cl, 0.L0Cl, 0.L0. 2 g/L NaHCO3 at pH 7.2 ). The results of the MTT assay were expressed as a measure of the optical density that was determined at a wavelength of 570 nm.
Results and Discussion 1. Powder Morphology
When Si and HA were added in the Mg-Zn-Mn composite, the microstructure showed different morphologies (refer to Figure 5e). The Type-I composite had better corrosion resistance compared to Mg-Zn-Mn and the Type-II composite.
Conclusions
Microstructure, mechanical and corrosion properties and biocompatibility of Mg-Zn-Mn alloys for biomedical applications. Synthesis and characterization of Mg-Zn-Mn-HA composite by spark plasma sintering process for orthopedic applications.
An Experimental Study on the Precision Abrasive Machining Process of Hard and Brittle Materials with
Materials and Methods 1. Ultraviolet-Curable Resin
In the experimental production of the ultraviolet curable resin bond abrasive, we have developed various laboratory methods to realize the production. The schematic diagram of the curing processes of the ultraviolet curable resin bond abrasive tool is illustrated in Figure 3.
Results and Discussion
Meanwhile, the abrasive grains buried in the sublayer of the resin matrix were constantly exposed and reactivated as fixed abrasive grains. Figure 8 shows the observation of the optical image on the worn surface of the UV-curable resin plate after the overlay process.
Surface Modification of Ti-6Al-4V Alloy by Electrical Discharge Coating Process Using Partially Sintered
The mass percentage of Nb powder coating on the surface of the workpiece increases with increasing coating thickness. The microhardness of the EDM machined surface is low compared to the EDC machined surface.
Optimization of Power Consumption Associated with Surface Roughness in Ultrasonic Assisted Turning of
Swarm-Simplex Method
Nature-Inspired Algorithms
PSO is categorized as the nature-inspired optimization algorithm in which the problem of linear and nonlinear programming has been successfully solved [32]. For minimization, the variable with the largest objective value is used for a new reflection and the ideal point value is approximately placed in the negative gradient direction [36]. Note that the objective or fitness function is calculated at each point of the method and the complete process is processed again and again until the final solution is reached.
Ranking: The obtained solution is ranked according to their best fitness values, from equations (1) and (2). Selection step: Equation (2) is used to select the best position of each particle and the generation of the ideal solution is obtained.
Results and Discussion
This statement is purely justified with the following Equation (11) which shows that the surface roughness is directly proportional to the square of feed rate according to the basic relationship. Furthermore, the tool work contact ratio was reduced with the increase in frequency of the tool. Then the effect of cutting depth together with the cutting speed is represented in Figure 6b.
From this analysis, it was interestingly found that the energy consumption values increased slightly with the depth of cut. In addition, the power consumption value decreased with the increase of cutting tool frequency, as shown in Figure 6c.
Conclusions
However, in the conventional cutting (CC) process, the high-quality, high-precision machining of the micro-groove on titanium alloy has always been a challenge, because significant problems including poor surface integrity and a high level of material swelling and rebound remain unsolved. The experimental results demonstrate that the UEVC technology is a feasible method for the high-quality and high-precision processing of the micro-groove on Ti-6Al-4V alloy. Therefore, the high-quality and high-precision machining of the micro-groove on titanium alloy has always been a challenge with the conventional cutting (CC) process [15-17].
Even more surprisingly, the effect of material swelling and spring back force of titanium alloy increased due to its low modulus of elasticity and thermal conductivity [16]. In order to elucidate the effective mechanisms of UEVC technology in microgroove machining of titanium alloy, comparative investigations of surface defect, surface roughness, and material swelling and springback effect in CC and UEVC processes are carried out.
Materials and Methods 1. The UEVC Principle
The results showed that due to the influence of UEVC technology, the cutting forces were reduced, the critical depth of cut was increased, and the machining accuracy of the microgroove was improved. Relative to the workpiece, the transient position of the cutting tool can be described as follows: At time t3, the speed of the cutting tool in the z direction is equal to the speed of the chip flow.
Figure 4 shows a schematic representation of the UEVC process in microgroove machining and a magnified view of the generated microgroove. The theoretical value of the microgroove depth (Ld) is equal to the predetermined depth of cut.
Results and Discussion 1. Material Swelling and Springback
Thus, in the CC process, the actual parameters of the generated microgroove deviated greatly from the designed parameters. In addition, the microgroove depth deviations were smaller with the decrease of TSR. This means that the dominant factor in the microgroove depth deviation has been eliminated.
Therefore, the deviation of the microgroove depth gradually decreased with the increase of the predetermined depth of the cut. This indicated that the accuracy of the machined microgroove improved significantly by using the UEVC technology.
Performance Evaluation of Vegetable Oil-Based Nano-Cutting Fluids in Environmentally Friendly
Environmentally friendly cooling conditions, i.e. the minimum quantity lubrication system, has been implemented in this work. Therefore, lower cutting forces and tool wear can be observed for the cutting tests performed with MQL nanofluid. Experimental Study: The trend of almost all parameters was found to be the same viz. the cutting forces, tool wear and surface roughness values were significantly affected with small changes in any of these machining parameters.
Optimization of Machining Parameters and Cutting Fluids During Nano-Fluid Based Minimum Lubrication Turning of Titanium Alloy Using Evolutionary Techniques. Effects of Minimum Quantity Lubrication (MQL) in Machining Processes Using Conventional and Nanofluid Based Cutting Fluids: A Review.J.
Dimensionless Analysis for Investigating the Quality Characteristics of Aluminium Matrix Composites
Dimensionless modelling: Buckingham Pi Approach
It is then mandatory to determine the degree of importance of the input process parameters for the measured results. The average hardness values obtained at different levels of "ρ" (in full Table 1) are plotted (see details in Figure 4). For this, the average values of dimensional accuracy obtained at different levels of “BFW” were plotted (in full Table 1); see Figure 5.
Ra=K·(V·t·l·ˆ(1/6))/F1/3·W2/3, (30) Similar to the dimensional accuracy, volume of FDM reinforced pattern which is the most significant parameter (refer to Table 2) with respect to surface roughness, of the cast composites, was taken as the mathem representative parameter to develop. For this, the average values of the surface roughness obtained at different levels of "VP" (through Table 1) were plotted; refer to figure 6.
Optimal Machining Strategy Selection in Ball-End Milling of Hardened Steels for Injection Molds
Experimental Procedure 1. Milling Tests
In the present study, a factorial design of experiments was used to select the experimental conditions in the ball milling process. The tools used were new or slightly worn (average flank wear VB < 0.1 mm) to avoid the effect of wear on surface roughness. An evaluation length of 4.8 mm (6×0.8 mm) was used and a probe tip with a radius of 2 μm was used in conjunction with a 0.8 Gauss cutoff filter and a bandwidth ratio of 320:1 to evaluate the Ra and Rt parameters.
A stylus speed of 0.5 mm/s was used together with a static stylus force of 0.8 mN and the stylus cone angle was 90◦. a) Example of roughness profile; (b) Profile roughness tester Taylor-Hobson Form Taylsurf Series 2. A Leica S8AP0 binocular magnifier (Leica Camera AG, Wetzlar, Germany) was used to take photographs of the workpiece surface at 80× magnification.
Surface Roughness Results
Models for Surface Roughness
Four main effects (ae,Ang,vcandfz) appeared to be relevant in the model to obtain the highest adjusted-R2. Four main effects (ae, vc, Angandap,) were relevant in the model to obtain the highest adjusted-R2. Four main effects (ae,Ang,fzandap,) were present in the model to obtain the highest adjusted-R2.
Three main effects (ae,ap and Ang) were present in the model to obtain the highest adjusted-R2. Prediction of Surface Roughness in End Milling Machining Using Artificial Neural Network. Expert system.
Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for
Smart Manufacturing
Materials and Method
For example, consider that in iteration "i" the number of subjects taught is "m", the size of students is "n" number, for the specific subject "j" the average of the result Mj,i. In recent times, the adaptation of the bacteria search optimization method [17], primarily inspired by the attitudes of E. For that reason, the average behavior of the surface roughness parameters as well as the cutting temperature are plotted in Figure 3.
Therefore, during optimization, the change in shear rate is more important to favorably approximate the response value. With the number of iterations, the overall fitness function of TLBO better matches the optimal value of the fitness function.
Prediction of Tool Wear Using Artificial Neural Networks during Turning of Hardened Steel
Results
The input data were diagnostic measures based on the analysis of vibration accelerations and shear force components. Networks created with different configurations of activation functions operate at the hidden and output layers. A comparison of the effectiveness of individual networks based on new data is presented in Table 3.
Notably, by increasing the number of neurons in the hidden layer, the performance of the model was improved. Proper selection of the number of neurons in the hidden layer and activation function in the hidden and initial layers significantly affects the effectiveness of tool wear value prediction.
Evaluating Hole Quality in Drilling of Al 6061 Alloys
Results and Discussion 1. Axial Force and Torque
Figure 4 shows the variation of the average axial (pressure) force and torque with respect to spindle speed and feed rate. Figure 5 illustrates SEM photos of the cutting edges of the drill after the 10th hole for each combination of spindle speed and feed rate. Figure 8 shows the change of output burr thickness and height with respect to spindle speed and feed rate.
Figure 9 shows a representative topography of the side exit nozzle in relation to velocity and shaft speed. Figure 11 shows the cutting chips after the 10th hole with different combination of spindle speed and feed speed.
Multiscale 3D Curvature Analysis of Processed Surface Textures of Aluminum Alloy 6061 T6
The curvature tensor is considered constant with respect to the size of the area representing the scale. The range of scales available in measurement ranges from the sampling interval to the size of the region being measured. These two methods apply to the selection of the measured heights used to estimate the normal vectors and to the selection of the three points that form the triangular patches.
It is the eight heights closest to the vertices of the triangular patches (Figure 2a) and the central point (apex) that are used for the eigenvalue problem. For the nominal scale, both methods use the same measured heights for the calculation of the unit normal vectors.
