Search

Inconel 718 is widely used in many applications specifically in the aerospace and nuclear industry due to its superior properties in strength, hot hardness, and thermal and corrosion resistance. However, it is classified as difficult-to-cut material due to its extreme hardness that led to high cutting forces and temperature which further worsened by its strain hardening effect. Thus, it is crucial to analyze the different types of wear mechanisms and failure modes, to analyze causes, and also to understand how cutting parameters affect the wear mechanisms and failure modes. The study is conducted with PVD TiAlN-NbN coated inserts with varying cutting speeds (40, 60, and 80 m/min) and varying feed/tooth (0.7, 0.1, and 0.13 mm/tooth) under the wet condition of face milling. The flank wear progression and length of cut were measured and recorded to study the tool life against length of cut. The tool wear and failure modes of inserts were observed under the optical microscope and SEM/EDX. Results showed that cutting speed has a major effect on the tool failure as compared to feed/tooth. At low speed, the dominant tool failures were macro-chipping due to the severe BUE (built-up edge)/BUL (built-up layers) formation. At higher speeds, the dominant tool failures were flaking and notching which led to the sudden tool breakage. At low feed/tooth, the dominant failures were flaking and macro-chipping, but notching and tool breakage became dominant at higher feed/tooth. Moreover, it is found that the main wear mechanisms which contributed to the tool failures were adhesion, abrasion, thermal and mechanical cracks, diffusion and oxidation wear.

Optimization of flank wear width (VB) progression during face milling of Inconel 718 is challenging due to the synergistic effect of cutting parameters on the complex wear mechanisms and failure modes. The lack of quantitative understanding between VB and the cutting conditions limits the development of the tool life extension. In this study, a Gaussian kernel ridge regression was employed to develop the VB progression model for face milling of Inconel 718 using multi-layer physical vapor deposition-TiAlN/NbN coated carbide inserts with the input feature of cutting speed, feed rate, axial depth of cut, and cutting length. The model showed a root-mean-square error of 30.9 (49.7) µm and R2 of 0.93 (0.81) in full fit (5-fold cross-validation test). The statistics along with the cross-plot analyses suggested that the model had a high predictive ability. A new promising condition at the cutting speed of 40 m/min, feed rate of 0.08 mm/tooth, and axial depth of cut of 0.9 mm was designed and experimentally validated. The measured and predicted VB agreed well with each other. This model is thus applicable for VB prediction and optimization in the real face milling operation of Inconel 718.

Owning to the extremely abrasive silicon particles, low melting point of aluminum, and its susceptibility to adhere to the tool, high-speed drilling of aluminum alloys containing high silicon content becomes a challenging operation. Hence, the understanding of the tool wear mechanisms is essential in order to develop and select the efficient tool material. This paper reports on the investigation of performance and wear mechanism of uncoated and TiAlN and AlTiN-coated tools when high-speed drilling of Al-Si (A383) alloy. Drilling tests were conducted at various cutting parameters, while thrust forces were measured using a dynamometer. The wear mechanisms that contributed to the drill failure were assessed by analyzing the worn cutting edge and drill bit cross section; and by employing scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). Results showed that feed rate has the highest effect on the primary wear stage; and flank wear at the outer cutting edge found to be dominant failure mode for all tools. Moreover, it is found that plastic deformation, diffusion, attrition, abrasion, and fracture are the main operating tool wear mechanisms. The longest tool life was recorded for AlTiN-coated tool, but more adhesion of Al was observed on this tool surface. At the end, TiAlN-coated drill was proposed as the tool with the best performance among the tool materials used in this study.

Load distribution has been studied extensively for ISO thread, but the load distribution on power screw threads, specifically ACME and Square threads, has not been studied yet. In this article, axisymmetric two-dimensional and three-dimensional Finite Element Analysis have been conducted on bolts with different sizes and thread geometries to examine the effect of the thread geometry on the load distribution. The thread geometries were studied with ISO, ACME, and Square threads attention. The sizes used are from the ISO coarse series. In order to investigate on the effect of bolt thread geometry, several simulations have been performed. The two-dimensional simulation results have shown reliable performance in determining the load distribution behaviour when the thread geometry is modified. Moreover, the results agreed with the three-dimensional simulation outcomes regarding the load distribution behaviour when the size is varied.

Machining is becoming increasingly advanced to satisfy industrial precision standards of the components. With accuracy being analogous to quality, the study of tool wear is growing in importance as wear can notably affect the tool life. In smart manufacturing, machining processes incorporate artificial intelligence in machine vision to improve key process functions through metrology, improving dimensional accuracy and surface integrity of products. By enhancing machine vision or other suitable forms of optical metrology, it is possible to identify different wear types and their corresponding causative mechanisms. In this study, the flank wear region was identified and classified using deep learning features and transfer learning by pre-trained CNN models. Tool wear mechanism’s features extracted by Alexnet and VggNet16, have been used to train a Support Vector Machine (SVM) for classification. A comparison of fine-tuned CNN and CNN-SVM models has been made. The fine-tuned models employed backpropagation (BP) and stochastic gradient descent (SGD) to optimise the weights for performance improvement. The fine-tuned CNN models accomplished a higher accuracy compared to a CNN-SVM with an average validation accuracy of at least 95%. Fine-tuned Alexnet had a better performance than VggNet16 with an average validation accuracy of 96.43% and classification time of 0.244 s. With high accuracy and minimum time complexity, fine-tuned Alexnet can be used for online tool wear mechanisms classification. This implies that fine-tuned CNNs are effective and reliable in performing classification of tool wear.

Recently, porous magnesium and its alloys are receiving great consideration as biocompatible and biodegradable scaffolds for bone tissue engineering application. However, they presented poor antibacterial performance and corrosion resistance which limited their clinical applications. In this study, Mg-Zn (MZ) scaffold containing different concentrations of tetracycline (MZ-xTC, x = 1, 5 and 10%) were fabricated by space holder technique to meet the desirable antibacterial activity and corrosion resistance properties. The MZ-TC contains total porosity of 63–65% with pore sizes in the range of 600–800 μm in order to accommodate bone cells. The MZ scaffold presented higher compressive strength and corrosion resistance compared to pure Mg scaffold. However, tetracycline incorporation has less significant effect on the mechanical and corrosion properties of the scaffolds. Moreover, MZ-xTC scaffolds drug release profiles show an initial immediate release which is followed by more stable release patterns. The bioactivity test reveals that the MZ-xTC scaffolds are capable of developing the formation of HA layers in simulated body fluid (SBF). Next, Staphylococcus aureus and Escherichia coli bacteria were utilized to assess the antimicrobial activity of the MZ-xTC scaffolds. The findings indicate that those scaffolds that incorporate a high level concentration of tetracycline are tougher against bacterial organization than MZ scaffolds. However, the MTT assay demonstrates that the MZ scaffolds containing 1 to 5% tetracycline are more effective to sustain cell viability, whereas MZ-10TC shows some toxicity. The alkaline phosphatase (ALP) activity of the MZ-(1-5)TC was considerably higher than that of MZ-10TC on the 3 and 7 days, implying higher osteoblastic differentiation. All the findings suggest that the MZ-xTC scaffolds containing 1 to 5% tetracycline is a promising candidate for bone tissue healing due to excellent antibacterial activity and biocompatibility.

In the machining process, heat generation and saturation on the cutting zone due to friction is one of the root causes of premature tool failure during dry cutting of hard-to-machine aerospace materials. Measuring and predicting thermal distribution is challenging because the tool and the workpiece are always in contact during the machining process. In this research, Finite Element Analysis (FEA) was employed to model the thermal distribution of titanium (Ti-6Al-4V), Inconel 718, and steel (AISI4340) during the machining process using three different tools: tungsten carbide, High-Speed Steel (HSS) and sintered silicon carbide. Johnson-Cook strength model and Johnson-Cook failure model were applied during the simulation using Lagrangian formulation in dry cutting. Different machining parameters i.e. cutting speed ranging from 90 to 360 m/min, depth of cut ranging from 0.5 to 2.5 mm, and rake angle ranging from 3 to 20°, were simulated and analysed. Small depth of cut of below 1 mm, low cutting speeds below 90 m/min and large rake angles above 10° are recommended for the dry cutting of these three materials to minimize the heat saturation on the cutting zone. This research provides an understanding of the relationship between material properties and heat saturation in the cutting zone for different materials. The analysis helps in the selection of predictor variables for modelling online temperature prediction using machine learning methods.

The curvature correction factor is an important parameter in the stress calculation formulation of a helical extension spring, which describes the effect of spring wire curvature on the stress increase towards its inner radius. In this study, the parameters affecting the curvature correction factor were investigated through theoretical and numerical methods. Several finite element (FE) models of an extension spring were generated to obtain the distribution of the tensile stress in the spring. In this investigation, the hook orientation and the number of coils of the extension spring showed significant effects on the curvature correction factor. These parameters were not considered in the theoretical model for the calculation of the curvature correction factor, causing a deviation between the results of the FE model and the theoretical approach. A set of equations is proposed for the curvature correction factor, which relates both the spring index and the number of coils. These equations can be applied directly to the design of extension springs with a higher safety factor.

This study aimed to examine the possibility of using insulin orally with gelatin encapsulation to enhance the usefulness of the drug and increase the lifespan of insulin in the body using polylactic-co-glycolic acid (PLGA) nanoparticles alongside gelatin encapsulation. In this regard, PLGA was synthesized

Applying cutting tool with longer functioning time is a vital issue in machining of the nickel-based super alloys. However, the experimental analysis of this problem is quite expensive. Thus, three-dimensional numerical simulation of tool wear propagation in turning of Inconel 625 super alloy is taken into account, in this study. The cutting insert with complex geometry is modeled by using a reverse engineering method. Based on the cutting tool and workpiece material, Usui wear rate model is exerted to estimate the tool wear rate. In the first section, characterization of TiAlN-coated carbide tool, which is suggested by catalogue, on wear resistance is evaluated and then simulation results are validated with experiments. As a result, increment of depth of cut is the most effective factor on the generation of temperature and stresses on the tool faces resulting in wear rate acceleration. In the second section, different commercial coatings with multicompositions are applied in the simulation to find the best performance against wear. Finally, TiCN coating outperformed other coatings in turning of Inconel 625.

One of the major challenges in brain research is to relate the structural features of the auditory stimulus to structural features of Electroencephalogram (EEG) signal. Memory content is an important feature of EEG signal and accordingly the brain. On the other hand, the memory content can also be considered in case of stimulus. Beside all works done on analysis of the effect of stimuli on human EEG and brain memory, no work discussed about the stimulus memory and also the relationship that may exist between the memory content of stimulus and the memory content of EEG signal. For this purpose we consider the Hurst exponent as the measure of memory. This study reveals the plasticity of human EEG signals in relation to the auditory stimuli. For the first time we demonstrated that the memory content of an EEG signal shifts towards the memory content of the auditory stimulus used. The results of this analysis showed that an auditory stimulus with higher memory content causes a larger increment in the memory content of an EEG signal. For the verification of this result, we benefit from approximate entropy as indicator of time series randomness. The capability, observed in this research, can be further investigated in relation to human memory.

Determination of accurate limit of cutting condition in order to obtain broken chips for various chip breaker geometries is essential to improve the machinability. This work presents a hybrid model based on the ratio of broken chip radius to the initial radius of chip to predict the type of chip regarding the characteristics of a chip breaker geometry and cutting parameters. An analytical geometrical model was developed to calculate the initial radius of chip. After running experimental tests for four types of chip breaker geometries and calculation of their chip ratio, type of chips and tool–chip contact were selected as two criteria for classifying chip ratio into three limits representing usable, acceptable, and unacceptable chips. Finally, the normalized data were used to train a neural network model to predict the type of chip which was verified by experiments carried out on a new chip breaker geometry. The trained network could predict the type of chip accurately by providing the geometrical details of the chip breaker and cutting parameters for the network.

Examination of cutting tool wear by experimental approaches is too costly. The main objective of this work is to develop an accurate 3D finite element model to predict the tool wear of PVD-TiAlN coated carbide and ceramic inserts in turning of Inconel 625. Thus, the cutting tools with complex geometries are modeled. Usui wear rate model is used to estimate wear rate where its constant parameters are achieved based on the cutting tools and workpiece material. The verification tests showed that the predicted values are in good agreement with the experiments. Moreover, among the cutting parameters, the increase of depth of cut were found as the most effective factor on the generation of temperature and stresses on the tool faces.

Rapid tool wear is one of the major machinability aspects of nickel-based super alloys. In this article, the effect of cutting parameters on material removal rate and tool wear of a whisker ceramic insert in turning of Inconel 625 was examined. Optical microscope and scanning electron microscope were applied to measure and study tool wear mechanism. Response surface method was used to develop a mathematical model which confirmed by experimental tests. The statistical analysis done by analysis of variance showed that depth of cut is the most effective factor on the tool wear. Experiments showed that increment of feed rate had an insignificant effect on the progress of flank wear, and it is an important controlling factor when material removal rate is considered as a desired output. Finally, optimized cutting condition is presented in this work.

Improving surface integrity is an important issue to enhance wear resistance and fatigue life of the end product. Thus, a 3D elliptical vibration method is represented to evaluate its effect on the parameters of surface integrity in boring process. The operation is carried out on a titanium cylinder in two methods of conventional and 3D elliptical ultrasonic assisted boring. After the machining, surface roughness, microstructure changes, and microhardness of the cut surfaces are examined. The results show that 3D vibration causes the depth of microstructure changes to be less than conventional boring, while it increases the surface hardness, more. In addition, this method almost eliminates the effect of cutting parameters on surface roughness by producing micro-textures on the surface.

Control of continuous chips in turning operation is a very vital issue to enhance productivity and operator safety. A famous method to control the chip size is utilization of chip breaker. In this study, the influence of different aspects of chip breaker geometry on cutting force, chip shape, and bending moment was evaluated by using finite element and experimental approaches. Therefore, cutting tests were carried out on AISI 1045 steel using tungsten carbide inserts with various chip breaker geometries. The results indicated that the predicted cutting force and chip shape are in close agreement with the experimental ones. It is also observed that the bending moment generated by the upper level of breadth surface has the highest contribution in the development of combined and nonuniform state of stress at the root and body of deformed chip. Meanwhile, the chip breaker geometry had a significant effect on the cutting force value.

Long tool life and high material removal rate (MRR) are the two essential requirements in rough cutting of materials. The rapid rate of the flank wear propagation in machining of nickel-based superalloys has induced the utilization of low cutting parameters when the goal was set to maximize the tool life based on the machining time or cutting length. However, this method may not provide an effective rate for the material being cut. This work presents two mathematical models to find the optimum cutting parameters results for the minimum flank wear and maximum MRR. Experimental tests were carried out based on the central composite design (CCD) in rough cutting of Inconel 625 by using TiAlN-coated insert. Maximum flank wear was measured to determine the tool wear propagation. The wear mechanisms which contribute in the tool wear were analyzed by using scanning electron microscope (SEM) to evaluate the effects of cutting parameters on the flank wear propagation. The results showed that cutting speed and depth of cut had the most significant effect on the tool wear. However, optimum cutting condition was achieved by reducing the cutting speed when feed rate and depth of cut maintained at the highest level. This was associated to the interaction of cutting speed and depth of cut, and predominant of abrasion and notching at their highest levels, respectively.

Analysis of the surface quality of workpiece is one of the major works in machining operations. Variations of cutting force is an important factor that highly affects the quality of machined workpiece during operation. Therefore, investigating about the variations of cutting forces is very important in machining operation. In this paper, we employ fractal analysis in order to investigate the relation between complex structure of cutting force and surface roughness of machined surface in end milling operation. We run the machining operation in different conditions in which cutting depths, type of cutting tool (serrated versus square end mills) and machining conditions (wet and dry machining) change. Based on the obtained results, we observed the relation between complexity of cutting force and surface roughness of generated surface of machined workpiece due to engagement with the flute surface of end mill, in case of using square end mill in dry machining condition, and also in case of using serrated end mill in wet machining condition. The fractal approach that was employed in this research can be potentially examined in case of other machining operations in order to investigate the possible relation between complex structure of cutting force and surface quality of machined workpiece.

Analysis of the machined surface is one of the major issues in machining operations. On the other hand, investigating about the variations of cutting forces in machining operation has great importance. Since variations of cutting forces affect the surface quality of machined workpiece, therefore, analysis of the correlation between cutting forces and surface roughness of machined workpiece is very important. In this paper, we employ fractal analysis in order to investigate about the complex structure of cutting forces and relate them to the surface quality of machined workpiece. The experiments have been conducted in different conditions that were selected based on cutting depths, type of cutting tool (serrated versus. square end mills) and machining conditions (wet and dry machining). The result of analysis showed that among all comparisons, we could only see the correlation between complex structure of cutting force and the surface roughness of machined workpiece in case of using serrated end mill in wet machining condition. The employed methodology in this research can be widely applied to other types of machining operations to analyze the effect of variations of different parameters on variability of cutting forces and surface roughness of machined workpiece and then investigate about their correlation.

Rapid tool wear is one of the most important problems in rough turning of Inconel 625 nickel-based super alloys which is less considered as a case study in wear analysis researches. Therefore, in this study, high material removal rate and low tool wear of PVD-TiAlN coated carbide were considered as objective factors in rough turning of Inconel 625 super-alloy. By using an adaptive network-based fuzzy inference system; an input-output relationship model was developed to find the effective parameters. Furthermore, simulated annealing algorithm method was used to define an optimum cutting condition considering low flank wear and high material removal rate. The results indicate that cutting speed and depth of cut with their interaction are the most effective factors on tool wear. While, feed rate is almost ineffective on tool wear propagation which can be increased to obtain higher material removal rate.

Composite-metal stack is an ideal combination of materials which unites the advantages of each dissimilar material in a substantial weight. However, drilling dissimilar materials has been a challenge since the composite-metal stacks are at demand in industries. It is important to choose the appropriate drill geometry regarding the stacking sequence and utilize proper machining parameters in order to achieve damage free and precession holes. This experimental study was conducted on dry drilling of CFRP/Al2024/CFRP (carbon fiber-reinforced plastic). Four types of twist drills with various geometries, both coated and uncoated, were utilized to study the effect of machining parameters on hole quality. It was observed that increasing feed rate entails an increase in entrance delamination, whereas exit delaminations and fiber fraying at 2nd CFRP exit diminished with increasing feed rate. It was also found that four facet tools performed better than two facet tools in terms of fiber delamination. Most accurate hole was attained on 2nd CFRP; however, it was found that increasing feed significantly affects the hole size on 1st CFRP.