In this research, Aerosoljet printing has been investigated as a manufacturing application for depositing micro-sized strain and creep sensors onto the surface of a complex Inconel 718 rocket engine nozzle. This novel manufacturing method has been tested to generate an aerosoljet printed sensing platform integrating elements of printed electronics for condition monitoring. A high temperature platinum nano particle conductive ink has been formulated which is capable of withstanding a surface temperature of 1290°C. Microprinted creep sensors manufactured in this way were also tested to determine and enhance the printing process. The manufacturing process developed during this research can be used for a wide variety of high temperature sensor applications in rocket engine structures for the purpose of continuous condition monitoring.
The industrial interest in the patterning of polymeric surfaces at the micro/nanoscale to include new functionalities has considerably increased during the last years. Hierarchical organization of micro/nanometric surface textures yields enhanced functional properties such as hydrophobicity, hydrophilicity, antibacterial activity, and optical or chromatic effects to cite some. While high accuracy methods to pattern hierarchical surfaces at the nanoscale have been developed, only some of them have been applied for high volume manufacturing with limited success, mainly because they rely on the use of expensive machinery and moulds or complicated inserts. Therefore, a method using low cost recyclable tooling and process conditions applicable to high-volume manufacturing is currently missing. In this work, a scalable and low-cost method to replicate hierarchical micro/nanostructured surfaces on plastic films is presented, which can be latter used as inlays for injection moulded parts with standard processing conditions. This method is used to demonstrate the feasibility of replicating three level hierarchical micro/nano textured surfaces using recyclable bio-based polymers (of high relevancy in the current plastic pollution context) achieving replication ratios above 90%, comparing the replication results with those obtained in polypropylene. The presence of the micro/nanotextures substantially increases the contact angle of all the polymers tested, yielding values higher than 90° in all the cases. Also, various mechanical properties of the replicated parts for all the polymers injected are characterized one and thirty days after the samples were manufactured, showing fairly constant values. This highlights the validity of the replicated surfaces, regardless of the biopolymers special crystallization characteristics.
Composite vibration ultrasonic cutting can achieve better processing quality than one-dimensional vibration machining, effectively increase the quality of the finished surface and prolongs the service life of the tool. Due to limitations of existing cutting devices that use composite vibration processing, including large motion coupling errors, small amplitudes, complex devices, and high costs, a new symmetrical radial and transverse vibration ultrasonic cutting device is proposed in this study. The proposed device is designed with a symmetrical structure and a unique fixed position of nodes to overcome the above limitations. In this paper, realization of radial and transverse vibration is elucidated by studying the vibration forms of piezoelectric vibrators. Based on the small deflection theory of axisymmetric thin circular plate in elastic mechanics, deformation of the vibrator after radial vibration coupling to transverse vibration is analyzed. The relationship between tool tip output trajectory and excitation phase difference is also evaluated. Impedance analysis and amplitude measurement results reveal that the cutting device achieves radial vibration at 80.5 kHz, with an amplitude of up to 490 nm; achieves transverse vibration at 75.95 kHz, with an amplitude of up to 710 nm, while amplitude ratio of radial and transverse vibrations is 0.679. The quality factor Qm of transverse vibration is 705.33, proving that the device can perform ultrasonic vibration cutting for a long time. The tool tip output trajectory proves that under different phases, the cutting device can achieve variable elliptical vibration cutting.
The poor rigidity of large composite material components in the helicopter has an important impact on robotic milling stability. Based on the machining stability of robotic edge trimming process, a method for calculating the component overhang is proposed in this paper. Firstly, the stability model of robotic longitudinal-torsional ultrasonic milling component (RCUM-LT) with poor rigidity is established by machining dynamics analysis. Then, the influence mechanism of variables such as ultrasonic vibration energy, workpiece overhang, and edge thickness on the stability region of robotic edge milling is explored emphatically. The calculation results show that the intake of ultrasonic energy suppresses robotic milling chatter effectively. As a result, the stability region of RCUM-LT is increased by 361.79%. In addition, the smaller the component overhang, the better the stability of edge milling will be. The effect of component thickness on RCUM-LT stability is the combined action result of modal property and dynamic milling force. Considering the influence of three variables on the stability region comprehensively, a reasonable boundary curve of the adsorption position is achieved according to RCUM-LT stability model. It provides technical support for realizing robotic edge milling composite material with high efficiency and stability. Finally, the verification experiments are carried out for stability lobes and optimal overhang length. The results show that the experimental results of RCUM-LT stability are in good agreement with the theoretical prediction. With the adsorption method proposed by this study, the surface roughness and its consistency of machined surface are significantly improved.
In order to establish a more accurate prediction model of turning forces, this paper proposed an analytical model for cylindrical turning with the consideration of the effect of the main cutting edge angle and the nose radius. Meanwhile, the unequal division shear zone theory in orthogonal free cutting is extended and applied to the oblique non-free cutting in the interaction between the chip units. To take into account the real tool nose geometry, the tool nose involved in the cutting is discretized into a series of cutting edge units. The geometrical parameters associated with the cutting edge units are analysed by using the coordinate transformation approach. Then, the improved oblique cutting model is applied to each cutting edge unit to acquire the component forces along the tool rake face. Finally, the resultant cutting forces in the turning process are calculated by the numerical integration method. To verify the effectiveness of the proposed model, the turning force experiment of 304 stainless steel was carried out by changing the cutting conditions, the main cutting edge angle, and the nose radius. Through the comparative analysis between the measured results and the calculation values of the proposed model, it was found that the analytical prediction of cutting force is in good agreement with the experiment.
Wire arc additive manufacturing (WAAM) allows for quick, large component manufacturing with fast deposition rates while leveraging readily available wire feedstock that is significantly cheaper than metal powder. However, the increased deposition rate of this process requires enhanced thermal management as failures can occur due to overheating. A common strategy to mitigate overheating is to dwell, or pause, between individual layers; however, this can significantly increase build times and eliminate the advantage of additive manufacturing being able to manufacture components quickly. To help mitigate this issue, this study explores the use of active cooling to maintain process control and to decrease overall build time. Conductive cooling applied to either the bottom or side of the print substrate was explored. Results from this study showed that bottom build plate active cooling can be used to decrease dwell times by up to 50% and decrease cool-down to room temperature after the building process by up to 75%. Results from this study demonstrate that the use of active cooling strategies for WAAM can be used for better thermal control over the process and should be further investigated.
Variations in running conditions cause fluctuation in the temperature field of precision machine tools, which inevitably results in thermal errors. To meet the demands of dynamic and time-varying temperature control capability, an active temperature control (ATC) method based on time grating principle is proposed, and the ATC system is developed. The ATC system contains main-loop and sub-loops. The oil target temperature in the sub-loop is determined according to the running parameters and the matching principle of the generalized heat generation–dissipation power. In accordance with the time grating principle, dynamic and differential oil temperature control of each sub-loop is achieved via the inlet time regulation of high-temperature (H-t) or low-temperature (L-t) oil in the main-loop. The main-loop H-t and L-t oil target temperatures are determined by the target range of the sub-loop temperature. The dynamic distribution of the refrigeration capacity and proportional heating mode is adopted to control the temperatures of H-t and L-t oil. By focusing on the feed system of precision machine tool, we carry out both dynamic simulation study and verification experiments, and the results show that the ATC method and system can effectively regulate the temperature field of precision machine tools, thus improving the thermal accuracy of the precision machine tool.
In recent years, the glass molding process (GMP), as an alternative technology of traditional glass processes, has been widely used in curved glass production industry. However, the high energy consumption issue that resulted in the strong thermo-mechanical coupling and high temperature (more than 700 ∘C) in GMP has now emerged as one of the factors impeding the further advancement of it. This study models and examines the energy usage in smartphone covers using various heating methodologies. Numerical model of heat flow between heating plates, heat-conducting plates and molds is established to investigate the energy flow and energy consumption in GMP. The effects of heating rate and heat flux density on energy consumption are studied, respectively. In addition, different strategies are adopted to estimate the effectiveness, and the desired energy consumption of GMP can be reduced from 614 to 594.4 kJ (reduce 3.19%) by the proposed model under the desired optimized process parameters. The molding time is reduced from 148.8s to 139.2 s, with a reduction rate of 6.45%. The verification experiment confirms that the predicted error is less than 15%. Finally, this paper analyzes the impact of energy consumption and carbon emissions on energy sustainability and environment in GMP.
The study considers a method for forming stiffened monolithic panels by local deformation of the panel ribs. The local deformation is caused by bending moments along the rib towards each other. The goal of the study is to numerically model the forming process of the stiffened monolithic panel utilizing the designed local-impact tool and analyze its effects on the panel, obtaining which experimentally is challenging. The finite element method (FEM) modeling is performed in ANSYS and validated by the experimental forming of a panel made of an aluminum alloy analogous to Al 2024. Simulation results provide deformation, stress, and strain distributions along the panel in loaded and unloaded states for various study cases. Furthermore, the effects of finite panel length, width, and forming process parameters such as applied force couples and single versus successive deformation are numerically investigated and discussed. Performed modeling demonstrates the advantages of the forming with the designed tool in terms of low residual stresses and their distribution. Finally, the analysis suggests future modification of the tool, particularly the shape of its grips, to minimize local residual stress concentrations.
Diamond is an important material in today and future industry, for its relatively advantages in hardness, optics, heat, and electricity. Strongly impeted by the synthetic low-cost and large-scale manufacturing feasibility, applications of diamond material quickly developed to optical windows, heat transfer, electronic semiconductors, and other high-tech fields, from the traditional field of cutting tools and jewelry. However, these applied fields require for superior surface quality, while great difficulties in the polishing and smooth processing are brought by the excellent physical and chemical characteristics of the diamond. In this paper, the research status of diamond mainstream polishing methods and dynamic friction polishing is summarized and analyzed, which proved that dynamic friction polishing is superior to other polishing methods in cost, efficiency, and precision. The progress of dynamic friction polishing technology was discussed from the aspects of equipment innovation, process parameter optimization, and material removal mechanism exploration. Dynamic friction polishing possesses vividly considerable application prospects, for its simple equipment, low cost of the processing, and can realize micro/nanoscale polishing at room temperature and no protective gas conditions. More strikingly, it can quickly reduce the surface roughness from microlevel to nanolevel.
Data fusion enables characterisation of an object using multiple datasets collected by various sensors. To improve optical coordinate measurement using data fusion, researchers have proposed numerous algorithmic solutions and methods. The most popular examples are Gaussian process (GP) and weighted least-squares (WLS) algorithms, which depend on user-defined mathematical models describing the geometric characteristics of the measured object. Existing research on GP and WLS algorithms indicate that GP algorithms have been widely applied in both academia and industry, despite their use being limited to applications on relatively simple geometries. Research on WLS algorithms is less common than research on GP algorithms, as the mathematical tools used in the WLS cases are too simple to be applied with complex geometries. Machine learning is a new technology that is increasingly being applied to data fusion applications. Research on this technology is relatively scarce, but recent work has highlighted the potential of machine learning methods with significant results. Unlike GP and WLS algorithms, machine learning algorithms can autonomously learn the geometrical features of an object. To understand existing research in depth and explore a path for future work, a new taxonomy of data fusion algorithms is proposed, covering the mathematical background and existing research surrounding each algorithm type. To conclude, the advantages and limitations of the existing methods are reviewed, highlighting the issues related to data quality and the types of test artefacts.
With the on-machine measurement (OMM) technology, the quality of curved workpieces can be measured directly on the machine after computer numerical control machining. Aiming at the problem that the complexity of surface measurement in traditional methods is only judged by subjective experience and is difficult to calculate, an image-based surface measurement complexity (SMC) quantitative model is proposed. First, according to the curved surfaces’ characteristics during the OMM process, the concept of SMC is introduced by analyzing several key factors. Then, the curvature and smoothness information of three-dimensional surfaces is converted into two-dimensional images’ information by using the conformal mapping with dimensionality reduction. Next, based on the image color and texture complexity calculation, a mathematical model combined with the area and profile correction coefficients is established. Finally, the SMC model’s validity is verified by a set of design-machining-inspection experiments on curved surfaces, and the relevant laws between the SMC and measurement efficiency and measurement accuracy are presented.
Everyday millions of people perform office work with long sitting in front of computers. This results in a poor posture in the spinal which is normally called Kyphosis. This problem becomes significant when the upper back of the spine crosses the angle of 5 degrees. Among the types of poor postures, there is one as slouching. Slouching for a longer duration of time with more frequency may result in spine bends on the upper region and becomes noticeable in the personality, especially during walking and sitting on the couch. When the spine angle in the upper back region reaches 50°, it starts giving pain to the patient which leads to spine surgery. Commonly orthopedics recommends spinal fusion surgery at this angle. Therefore, this article presents a novel design of a device with an automatic system for avoiding the slouch and retracting the angle of the spine for a good posture. In this device, there is a novel skeleton system, shoulder pads, a controller unit, and a McKibben actuator-based forcing mechanism. The complete system of this device is manufactured in a 3D printer using FDM technology. Pressurized water is pumped into the McKibben actuators in control conditions for generating the back force to retract the spine angle as well as to position the shoulders for avoiding the slouch. With the change in the angle of posture gives a shift in the values of water pressure. That results in the generation of back force in the actuators for correcting the posture. The skeleton is tested on people with a posture problem in the range of 20° to 45°. Results show that the pressure variation from 160 to 190 kPa in the water triggers the signal to generate a force between 19 and 34 N that is decreasing the posture angle up to 25°. The force produced by McKibben actuators is evaluated theoretically as well as experimentally, and the plots give harmonious behavior as well. The experiments illustrate that the proposed skeleton produces a nominal backward force to correct the posture automatically.
The paper presents a novel process of micro-cutting wherein the material removal is achieved by applying a constant penetration force of the cutting tool into the workpiece. Penetration force is achieved by a specially designed moving assembly comprising a tool and toolholder. Micro-cutting with constant cutting force is performed on conventional machine tools, using conventional cutting tools. The design of the tool and toolholder assembly enables the regulation of the penetration force intensity, i.e. the regulation of cutting depth. The regulation is achieved by changing the mass, eccentricity, and angular velocity of the moving assembly. The obtained results indicate that the applied method provides small cutting depths, a reduction of circularity deviation and roughness, and a more favourable distribution of the material in the surface layer.
The machining process of Blisk blades poses multiple challenges due to high requirements on surface quality and precision combined with high dynamic compliance of the thin-walled blades. Avoidance of chatter is thus of high priority in Blisk blade machining. However, the geometry of the Blisk blade array where the tool must fit between individual blades significantly limits the possibilities of controlling stability through the relative orientation of the tool and workpiece. Thus, the main parameters that can be used to control the stability of the process are the distribution of stock allowance and the spindle speed. Due to the effect of material removal on the blade’s dynamic properties, spindle speed needs to be adjusted throughout the machining process to keep it within the continuously changing stability gaps. This paper describes in detail an optimization procedure for the design of stock allowance distribution in such a way that a continuous spindle speed modulation is possible that avoids chatter throughout the machining process by maintaining spindle speeds within stability gaps. The presented algorithm uses finite element analysis software to simulate the effects of stock allowance distribution and material removal on workpiece dynamical properties. This information is then coupled with a stability model based on the Jacobian of the cutting force with respect to the regenerative deflection to identify the varying stability gaps throughout the machining process. The proposed method was experimentally verified.
The realm of 3D printing has been a valuable aspect of manufacturing and mechanical engineering to which complex geometries have been made that might be otherwise highly costly or not feasible by other manufacturing methods. This is where volumetric 3D printing has been advantageous by generating complex geometry with no defects on the surface. The problem with the research done so far is that the material used uses photoinitiators that photo-synthesize using ultraviolet (UV) light. The problem with this material is that it is attached to the destructive issues brought on by interacting with UV light, making some additives useless. To solve part of this problem, a solution to the material problem must be shown that a resin can be cured using visible light. This study has investigated the feasibility of a novel manufacturing process termed, the visible light–induced–volumetric 3D printing (VLI-V3DP) process that resulted in successfully finding resin that can be cured using visible light in the 470 and 530 nm range. By curing simple geometry using visible light, one can formulate a resin that can sustain just about any additives that can meet any goal, whether it is organic or not.
Ultrasonic vibration–assisted core drilling has achieved some beneficial results in carbon fiber–reinforced plastics (CFRP) hole machining. Among them, longitudinal-torsional ultrasonic-assisted core drilling (LTUACD) shows more significant advantages in decreasing cutting force and reducing delamination defects and other aspects compared to longitudinal ultrasonic-assisted core drilling (LUACD). However, the reduction mechanism of cutting force and delamination defects in LTUACD is still not clear enough. Therefore, this paper researched the machining performance of LTUACD of CFRP. Specifically, the cutting force in LTUACD of CFRP is analyzed based on hertz contact theory and indentation depth theory. Then, a series of experiments were conducted to verify the analysis. And delamination suppression mechanism was discussed from the aspects of surface morphology of hole wall, exit morphology of hole, and bottom surface morphology of blind hole. The results show that the cutting force is significantly reduced in LTUACD compared to conventional core drilling (CCD) and LUACD due to the additional torsional vibration of tool, which changes the contact state between abrasive grain and material. Therefore, the exit delamination is further suppressed. In addition, the adhesion phenomenon of chips on the tool is also reduced, which enhances the tool cutting ability to obtain even fiber fracture surfaces and greatly improves hole quality.
Industry 4.0 involves major changes in manufacturing process management. Both the Internet of Things and cloud computing allow online interactions between third parties, such as providers, customers and suppliers, with the traceability system of a factory. Several blockchain-based approaches have been proposed to increase confidence in traceability data and reinforce trust. However, the transparency brought may be at the cost of risks to factory’s confidential data exposure. This paper investigates the way these critical data, which are necessary to post-assembly audit, could be included into traceability data, and validated through the related transactions by the third parties, without compromising their confidentiality. Accordingly, this proposal includes the description of a blockchain-based traceability system and its implementation using the Multichain platform. In addition to its confidentiality-preserving feature, we discuss the way energy consumption and storage volume induced could be managed so as to favor its effective adoption by manufacturing factories.
Nano-cutting fluids technology proved its effectiveness to enhance the quality of the machining processes’ performance, especially for difficult-to-cut materials, as these materials have potential applications in different industries, including automotive, gas turbine, and aerospace. Thus, the development, understanding, and investigation of the nano-cutting-fluid mechanisms are highly essential. The main objective of this work is to study and analyze the nano-cutting fluid heat transfer mechanisms. A proposed heat transfer model has been developed in this work to provide a solid physical understanding of heat dissipation when machining with nanofluids. In addition, a comparative performance analysis between multi-walled carbon nanotubes (MWCNTs) and alumina (Al2O3) nano-cutting fluids has been presented, discussed, and validated throughout the current study. The proposed model findings offer physical explanations that justify the tool performance results presented in a previous work since MWCNTs nanofluid offered better heat transfer performance (in terms of heat convection coefficient and thermal diffusivity) compared to Al2O3 nano-cutting fluid when cutting nickel-based alloys.
Real-time health condition monitoring of bearings plays a significant role in the functionality of the rotary machinery. Multi-channel sensor fusion can be more robust for identifying diverse bearing fault diagnosis scenarios. However, the
high-dimensional data and complex fault scenarios that can occur in the system pose significant challenges for effective fault diagnosis. State-of-the-art artificial intelligence-based bearing fault diagnosis system involves multi-channel sensor fusion, which usually leverages time–frequency analysis, feature extraction, and supervised learning. Nevertheless, those methods usually require a large training dataset for the machine learning model development. This paper proposes a new multi-channel sensor fusion methodology, named frequency-domain multilinear principal component analysis (FDMPCA), by integrating acoustics and vibration signals with different sampling rates and limited training data. Frequency analysis is firstly leveraged to transform the original signals from time to frequency domain, and the frequency responses of heterogeneous channels form a tensor structure named the frequency-domain (FD) tensor. Subsequently, the FD tensor is decomposed by multilinear principal component analysis (MPCA), resulting in low-dimensional process features for fault diagnosis. Finally, the extracted features can be used to train a Neural Network (NN) model for fault diagnosis. To validate the effectiveness of the proposed method, the bearing fault experiments were conducted on a machinery fault simulator while multiple vibration and acoustic
signals were collected. Experimental results demonstrated that the proposed approach can effectively identify the machine fault conditions and outperform the benchmark methods given the limited training data.
Vibration monitoring of CNC high-speed machining (HSM) centers under non-stationary conditions, characterized by varying operating parameters and uncertainties affected by the change of speed and load during operation currently presents a particular challenge. Therefore, bearing condition monitoring is important. Indeed, this variation has a considerable impact on the vibratory response delivered by the accelerometers and therefore can mask any fault. The change in speed causes considerable changes in the spectrum of the vibration such that defect signatures become almost undetectable with conventional tools. The order tracking method based on time–frequency representation is regarded as an effective tool for fault detection of bearings with varying rotating speeds. This study aims to propose non-stationary tools based on tachometer order tracking to detect bearing faults in high-speed milling centers during run-up and coast-down conditions. Developed tools are compared to stationary technics in this study, remaining limited to detect faults. Indeed, the speed variation would cause spectrum smearing if classic tools are used in non-stationary conditions. These latter methods are based on constant rotating speed and would fail to detect faults of bearings with variable spindle rotating speeds.
Titanium matrix composites (TMCs) reinforced with discontinuous ceramics and carbonaceous materials are increasingly attracting the attention of researchers and material engineers for applications in aerospace, defence, automotive and industrial plants owing to their exceptional heat and wear resistance, lightweight, high specific strength and stiffness. Recently, several findings related to the development of various discontinuously reinforced titanium matrix composites (DRTMCs) consolidated by spark plasma sintering (SPS) have been reported in the literature. It is imperative to summarize the significant findings of these studies to further understanding on the evolution of these new materials and serve as a guide for future works. Therefore, in this work, a detailed overview of the microstructural, mechanical, wear and oxidation characteristics of spark plasma sintered (SPSed) DRTMCs is presented, and wide-ranging information, and possible research directions on the aforementioned subjects, are provided. Determination of the critical reinforcement fractions and establishment of an appropriate processing technique that promotes uniform reinforcement dispersion and realization of innovative structural architecture that brings specialized functions to the components of the matrix have been established as a practical approach to advance the properties and widen the areas of application of SPSed DRTMCs.
Double-plane grinding plays an important role in the processing of high-precision flat parts. A double-side autonomous grinding (DSAG) method was proposed and investigated to improve the uniformity of the abrasive grains of the grinding disc on the surface of the workpiece by releasing the constraints on the workpiece. In DSAG, the main driving force of workpiece movement comes from the friction force generated by the relative movement of the upper and lower grinding pads. Experiment of dynamic friction coefficient measurement between workpiece and grinding plates is carried out to take into account the differences of dynamic friction factor under different speed and force conditions. A mathematical model of the relative motion trajectory between the particles on the upper and lower plate and the workpiece is established based on kinematics and dynamics theories. Then, the effects of the linkage mode of the lower plate, grinding pressure, and speed ratio of the upper and lower plates on the frequency and direction uniformity of the grinding trajectory of the abrasive particles on the workpiece surface are simulated and analyzed. Aiming at the trajectory uniformity, the grinding parameters are optimized through orthogonal experiment and verified on the independently developed experimental platform. The flatness and roughness of the workpiece are detected. The results show that the DSAG performs well in obtaining the better roughness and flatness of the workpiece surface than that of planetary grinding.
Industry 4.0 promotes highly automated mechanisms for setting up and operating flexible manufacturing systems, using distributed control and data-driven machine intelligence. This paper presents an approach to reconfiguring distributed production systems based on complex product requirements, combining the capabilities of the available production resources. A method for both checking the “realisability” of a product by matching required operations and capabilities, and adapting resources is introduced. The reconfiguration is handled by a multi-agent system, which reflects the distributed nature of the production system and provides an intelligent interface to the user. This is all integrated with a self-adaptation technique for learning how to improve the performance of the production system as part of a reconfiguration. This technique is based on a machine learning algorithm that generalises from past experience on adjustments. The mechanisms of the proposed approach have been evaluated on a distributed robotic manufacturing system, demonstrating their efficacy. Nevertheless, the approach is general and it can be applied to other scenarios.
The smooth particle hydrodynamics (SPH) method is advantageous in tracking a free surface and a moving interface. This paper uses the SPH method to simulate the filling process of squeeze casting. The simulated temperature field at the end of filling was input into a finite element model (FEM) program to simulate the solidification process after squeeze casting. Due to the existence of a liquid phase, a solid phase, and a two-phase mushy zone in the solidification process after squeeze casting, the deformation behavior in the solidification process was modeled with a thermoelasto–viscoplastic constitutive model representing these different phases. In the RDG thermal cracking criterion based on the principle of dendrite gap complement, there are a strain rate term, a secondary dendritic spacing term, and a pressure term. These terms accurately describe the squeeze casting process. Therefore, the RDG criterion was used to predict thermal cracking. The strain rate term in the RDG criterion was calculated by the FEM. For the calculation of the secondary dendritic spacing, the temperature field during the solidification process is locally refined by the FDM method to complete the transition from the macroscale to the mesoscale; then the refinement results are imported into the phase field method for dendritic growth simulation. The results show that the method based on multi-model coupling has satisfactory prediction accuracy for the thermal cracking in the squeeze casting process. The combination of the phase field method and the RDG criterion provides a new approach to the simulation of thermal cracking defects. The prediction results show that the thermal cracking tendency increases with an increase in strain rate. However, the local position C of the bracket sample had a higher strain rate of 7.15/s, and a lower cooling rate of 2.96 K/s offset the effect of the high strain rate. As a result, a low thermal cracking tendency level of 1.13729 was obtained.
The deflections of screw rotors under machining forces cause mismatch between the male and female rotors and, consequently, accelerated wear and suboptimal efficiency in their performance. Optimizing the machining process to minimize the generated forces and accounting for the resulting mismatch in the design of the rotor profile require accurately computing the machining forces in computer simulations. Virtual machining systems combine graphics-based computation of the cutter-workpiece engagement (CWE) with the physics-based models of machining mechanics to simulate the forces during complex machining processes. However, because of the high computational load of graphical simulations, virtual machining is not suitable for the repetitive force simulations that are required for optimizing the design and manufacturing of rotors. In this work, we present a new method that simulates screw milling forces based on process kinematics instead of graphical simulations. The semianalytical nature of the presented method allows for computing the forces with arbitrary resolution within a reasonable time. The accuracy and efficiency of the presented method are verified by comparing the simulated forces against a dexel-based virtual machining system.
Material jetting (MJT) is a recognized additive manufacturing (AM) method to combine various materials and create a wide range of designed appearances. However, the measured color of MJT objects is frequently different from the color provided in the printer software. As a result, estimating the color quality and the measured color attributes of an object before printing is vital for accurate color reproduction. This study investigates the color variation based on the texture in an object 3D-printed using the MJT method on a rotary tray. The novel radial shape of the rotary tray build platform and variation in the layers structure were targeted as the main factors that can increase the uncertainty in accurate color reproduction. The influence of the PolyJet printer setup has been examined by thickness variation of the colored layers, location on the tray (swath selection), ink color, and finish type between layers. Color quality was assessed by comparing the produced object color by calculating spectral and colorimetric differences. Spearman rank correlation coefficient and principal component analysis (PCA) methods were used to analyze the direct or indirect influence of independent categorical factors on the measured color variables. Based on the studied parameters, switching swathes did not fail printer objects for industrial color matching. In contrast, a thickness variation as small as 0.5 mm could cause CIEDE2000 above 5 for most models, resulting in unnatural color reproduction. Color differences in most objects might be discernible to inexperienced observers, depending on the 3D printing parameters.
Friction stir welding of aluminum alloys is today an essential joining technic for various industrial sectors. However, making a quality joint is relatively expensive compared to the electric arc welding processes. The aim of this work is to maximize the ultimate tensile strength (UTS) of AA3004-H32 aluminum alloy butt joint and minimize its production cost. The welding parameters are rotational speed, welding speed, and pin shape of the tool. Then, a test campaign is carried out according to the Box-Behnken design of experiments. Mathematical models of power consumption and ultimate tensile strength were developed by multiple linear regression. The analysis of variance (ANOVA) of the experimental data revealed the preponderant effect of the tool rotational speed and the pin profile on the studied responses. The bi-objective optimization problem was solved using the genetic algorithm and optimal welding parameters were presented. In terms of joint quality and electrical energy consumption, the results showed that the tool rotational speed plays a key role, and that the threaded cylindrical profile of the pin is the most preferred compared to other studied shapes. The welding speed is the most significant parameter in reducing welding costs. The approach proposed in this study can be used as a guide and recommendation to reduce FSW costs and at the same time ensure the quality of the AA3004-H32 alloy joint.
To improve the production yield rate, reliability is one of the important indicators of electronic packaging products. In past research, however, the influence of the fabrication process was rarely taken into consideration. In this thesis, mold flow analysis software Moldex3D is used to develop a series analysis procedure for IC package products. The effects of many factors, including process, structure, and materials were being taken into account. Especially for epoxy molding compound, namely EMC, is studied on its properties during the molding and post-mold cure (PMC) processes. This paper adopted P – V - T - C equations, which consider both volume shrinkage due to thermal mismatch and chemical shrinkage to predict the amount of warpage and residual stresses after the mold filling process. Next, dual shift factor model for viscoelastic analysis was used to model the PMC process and predict the amount of warpage and residual stresses after PMC. And the influence of different PMC process conditions and loading conditions on the warpage results is discussed. The residual stresses after PMC simulation are set as the initial conditions for reliability analysis and then the stress distribution after two thermal cycles is analyzed. It is observed that the deformed shape of the simulation and experiment results after PMC were consistent. Both are concave downwards. In comparison with experiment results, the error of warpage simulation results was between 10% and 50%. The biggest error was found in the short direction. During two thermal cycles, it is can be found that the maximum stress of the lead frame is 505.7 MPa and the location of the possible failure is at the top left of the die. In addition, when considering or not considering the process-induced residual stress in the thermal cycle analysis, the stress states are very different.
The increasing demands of highly precise industrial products lead to continuous seeking for the improvements in cabapility of manufacturing machines, i.e., machine tools. Machine tools include different types of manufacturing machines, i.e., turning, lathe, drilling, and milling machines whatever computerized numerical control (CNC) type or manual type. The cabaplity improvement in machine tools requires a real understanding of their productivity, accuracy, and operating parameters, i.e., their geometrical errors. These errors can be accurately identified through measurements with highly accurate measuring instruments. These machine errors have different error sources. The angular errors, horizontal and vertical straightness errors, paralleism errors, and squarness errors are clear examples for these sources. In this work, a comparative study for the determination of machine tools errors is carried out. Two main instruments of laser interferometer system and autocollimator system are used. The geometric errors are identified, measured, and analyzed.
The previous research on machined surface topography in milling processes usually focuses on simple and single machining features such as free flat and form surfaces. However, the industrial components are composed of complex machining features such as slots and grooves finished by profile milling cutters. The formation mechanism and prediction method of machined surface topography for the complex milling features are required in industrial applications. Firstly, the machined side surface topography formation mechanism in profile milling straight slot machined by single-pass processing with a solid end mill is presented. Then, the numerical prediction models for machined side surface roughness in straight slot profile end milling are proposed. The proposed model can accurately predict the surface topography, and the relative prediction errors of the surface roughness (Sa) are within 6.34% for the whole cases in this research. Finally, the effect of cutting parameters on the residual heights of the machined side surface is analyzed. The formation mechanisms of machined two side surface topographies on the straight slot are distinct, for which one side surface is machined by up milling while another is by down milling. It is shown that the different tool trajectories cause the distinction for milling each slot side. The machined side surface topography can be controlled by selecting optimized tool motion parameters and cutting parameters. The influences of tool deflection and tool wear on the surface topography are ignored in the current research, which will be considered in the future.
The micro-groove structure has attracted extensive attention in mechanical seals and cutting tools as an effective surface modification method. Electrochemical machining (ECM) is a non-contact machining method that can fabricate a large area of micro-grooves on difficult-to-cut metal materials. However, there are significant differences in the dissolution rate in different processing areas when multiple micro-grooves are processed simultaneously, resulting in poor machining accuracy and consistency of micro-grooves. In this work, a pulse-vibration ECM method was given to enhance the machining localization of parallel micro-grooves. The variation laws of flow velocity, void fraction, temperature rise, conductivity, and dissolution rate in different ECM methods were studied through the coupling simulation of the gas–liquid two-phase flow field, temperature field, and electric field. In addition, the effects of different flow modes and different ECM methods on the changes in groove width, groove depth, and cross-sectional profile of the micro-groove were studied based on experimental research. The results verified that combining a pulse-vibration ECM method and a flow-direction switching mode could significantly improve micro-grooves machining accuracy and consistency, the average groove width of micro-grooves processed by the combined method was 587 μm, and the groove width deviation was 8 μm. Moreover, compared with the die-sinking ECM, the average groove width of micro-grooves processed by pulse-vibration ECM was reduced by 13%, and the groove width deviation was reduced by 47%. Besides, the cross-sectional shape of the micro-groove contour gradually changed from a circular arc to a trapezoid.
Galvannealed (GA) steel sheet is applied to the chassis parts of automobiles with fatigue durability important through gas metal arc welding (GMAW). However, the pores due to zinc vaporization and gaps of the weld deteriorate their fatigue performance. In this study, the tensile shear strength and fatigue behavior of the welds were evaluated considering the porosity and gap size. A GA 590 MPa grade steel sheet with a thickness of 2.3 mm was considered as the base material. GMAW was performed under cold metal transfer (CMT) same welding conditions with a wire feed and welding speed of 7.0 m/min (220 A/16.7 V) and 60 cm/min, respectively, in lap fillet joints with gaps of 0, 0.2, 0.5, and 1.0 mm. The weld porosity was investigated through radiography tests (RT). The tensile shear strength and fatigue properties of the weld were evaluated. For the weld sample without a gap, porosity of 1.4, 4.0, and 6.4 % was detected in the tensile shear specimens through RT, and the tensile shear strength of the weld at RT was reduced 613, 565, and 345 MPa, respectively. For the weld with a gap of 0.2 mm or more, pores were not observed, and their tensile shear strength was maintained at 610 MPa or more. The welds with gaps of 0 and 0.2 mm had a fatigue strength of 91 MPa, whereas those with gaps of 0.5 and 1.0 mm had 62 and 47 MPa, respectively. Thus, the fatigue strength decreased as the gap size in the weld joint increased.
Ultrasonic elliptical vibration cutting (UEVC) has been successfully applied to precision machining of difficult-to-machine materials with its advantages of low machined surface roughness and low tool wear. In this study, an eccentric cone UEVC tool is proposed based on the mechanical vibration theory, with the idea of combining longitudinal vibration and bending vibration. The preliminary dimensions of the UEVC tool are obtained by theoretical calculations. Then, the dimensions of the tool are optimized through finite element analysis (FEA) to meet the requirements of vibration modes and resonant frequencies. Finally, a prototype of the eccentric cone UEVC tool is developed, and the vibration performance tests and cutting experiments are conducted on the designed tool to verify its cutting trajectory and cutting performance. According to the results, the new developed eccentric cone UEVC tool can achieve the elliptical vibration trajectory at the tool tip; the resonant frequency of the tool is 28019 Hz; and the longitudinal and the bending amplitude are 6.2 μm and 4.9 μm, respectively. The new developed eccentric cone UEVC tool can obtain workpieces with the surface roughness about 0.337 μm and reduced the tool wear.
The ultra-precision flycutting machining is usually used to machine large-size planer optical elements used in laser systems. Due to the comprehensive influence of different factors, the ripples on the optical surface will reduce the laser damage threshold, thus affecting the application of the laser system. A simulation model of the surface stripes in ultra-precision flycutting machining is built in this paper, which utilizes the advantages of simplicity and accuracy. The influences of cutting parameters, cutting interference phenomenon, relative vibration between the tool tip and the workpiece, workpiece shape, rotation speed fluctuation, and workpiece offset are analyzed. The formation mechanism of the ripples along the cutting direction and the feed direction is thoroughly explained. The ultra-precision flycutting machining test verified that the simulated and the experimental surface ripples agree well, which verifies the accuracy of the simulation model. The simulation model can be used to optimize the cutting process of the ultra-precision flycutting machining, which avoids the time and money consuming in cutting experiments and can also provide new ideas for tracing the source of the waviness on the surface topography.
A major problem in the high-speed cutting process of machine tools is tool wear. Tool wear directly affects the surface quality and machining accuracy of the workpiece. However, the limits of fusing multiple sensing signals to indirectly monitor tool wear are rarely concerned in real manufacturing environments. In this paper, a tool wear identification method based on a single sensor signal is proposed. To solve the limits of less obtained information and poor anti-interference ability of single sensor, multi-domain feature fusion strategy is established. By establishing a hybrid model of deep convolutional neural network and stacked long short-term memory network, the complex mapping relationship between fusion features and tool wear is constructed. Specifically, the spatial features of the input data set are extracted by the convolution kernel of the deep convolutional neural network. Then, a stacked double-layer long short-term memory neural network is established to capture sequence features with long-term dependence, thereby identifying tool wear. Finally, the superiority of the developed method is verified by tool wear experiments. The results show that the method can be effectively applied to tool wear identification from single sensor signals, and the mean RMSE and MAE of the identification results are 9.43 and 7.15, respectively. Compared with four other traditional multiple regression methods, RMSE and MAE are reduced by 73.0% and 78.7% on average. This study provides a reference value for the industrial implementation of tool wear monitoring system.
The flexible circuit pattern is the key component of flexible electronics. A near-field electrohydrodynamic direct-writing (NFEDW) method was proposed to fabricate the flexible circuit pattern. The prepared poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate)/graphene/single-walled carbon nanotubes mixed solution was deposited on the flexible substrate to fabricate the flexible circuit patterns, which could improve the fabricated quality of flexible circuit patterns. The influence of the multi-parameters on the pattern width of flexible circuit was analysed by the direct-writing experiment method. In order to explore the mapping law of multi-field coupling parameters on the pattern width of the direct-writing flexible circuit, a multivariable grey regulation method with a small number of test sample data was proposed by combining a small number of experiments and optimization design, and a multi-field coupling parameter regulation model of the NFEDW method was constructed. The multi-parameters with the expected width of the flexible electronic pattern could be effectively controlled. The experimental results show that the average correlation error between the actual measured pattern width and the predicted width of the prediction model is 4.04%. The proposed optimization method can effectively improve the fabrication efficiency and reduce the manufacturing cost of the flexible circuit with the expected pattern width.
Zirconium is a prospective metal to replace stainless steel in nuclear energy, aerospace, medicine, and chemical fields owing to its excellent comprehensive properties. However, microfabrication of zirconium metal by existing machining methods suffers from severe tool wear, low machining efficiency, and poor machining quality. Electrochemical machining has advantages for processing zirconium metal microstructures, but related studies have been rarely reported due to superpassivation of zirconium. The aim of this study was to evaluate the feasibility and processing trends of masked jet electrochemical machining of Zr702 sheet microdimple array. The dissolution behavior of Zr702 was analyzed in different concentrations of sodium nitrate and polyaluminum chloride electrolytes. The electrolyte was optimized, and the electrochemical corrosion mechanism of Zr702 was explained. Then, the effect of main processing parameters, including the mask aperture, machining gap, electrolyte pressure, jet scan speed, and pulse voltage, on machining performance was investigated in detail. After optimizing the parameters, a good synthesized quality of microdimple array was obtained with an average diameter of 157.60 μm, an average depth of 79.25 μm, a depth/diameter ratio of 0.503, a lateral corrosion coefficient of 2.043, a diameter variable coefficient of 1.72, and a depth variable coefficient of 2.90.
Wire arc additive manufacturing (WAAM) of titanium parts shows promising potential for aerospace application due to its high deposition rates allowing a fast and economical production of large components. The cost savings are high, especially for expensive alloys like Ti-6Al-4V. However, due to high oxygen affinity of Ti-6Al-4V at elevated temperatures an excellent shielding gas coverage seems necessary to prevent embrittlement of the material during the welding process. Regarding the future development of local shielding gas coverage set-ups for gas metal arc welding (GMAW) based WAAM, this study investigates the influence of the oxygen content in the shielding gas chamber on mechanical properties of Ti-6Al-4V during the welding process. Samples are welded at different oxygen contents in the shielding gas chamber and stress-relief heat treated afterwards. Inert gas milling and hot gas extraction are used to determine the material oxygen content at different deposition heights. Metallographic methods are used to show macroscopic grain structure, evaluate possible α-case thickness and its dissolution by the subsequent layer. Hardness testing is used to investigate possible material inhomogeneities in the deposit and tensile properties of the material welded at different chamber oxygen contents are displayed. It is concluded, that even at high chamber oxygen levels of 6000 ppm the welding process is stable, the forming α-case at top of the layer dissolves in the melt pool of the subsequent layer and that the aerospace requirements on tensile properties can be reached.
Efficient and productive manufacturing of freeform shapes requires a suitable three-dimensional CAD model at the entrance to the CAM system. The paper deals with the impact of NURBS or B-spline CAD model geometric continuity on the accuracy and productivity of 5-axis ball-end milling of freeform surfaces. The relationship between a different order of CAD model geometric continuity and the quality of the toolpath generated in CAM system is analysed and demonstrated on an example of a Blisk blade profile. In order to reveal the effect of CAD geometry on the quality of the machined surface, linear interpolation of cutter location points, i.e. piecewise linear discrete toolpath, is considered. Also, no further smoothing of the toolpath is applied. The distance of the cutter location points is commonly used as the indicator of toolpath quality. In addition, the discrete curvature of a linear discrete toolpath is introduced here, and its dependence on the curvature and continuity of the underlying CAD model is demonstrated. In this paper, it is shown that increasing the order of CAD model geometric continuity significantly eliminates sharp changes in the distance of cutter location points, and smoothes the discrete curvature of the toolpath. Finally, it is experimentally verified that increasing the continuity of the CAD model from G⁰ to G³, while maintaining the same cutting conditions, leads to an increase in workpiece accuracy and a reduction in machining time, without the need to smooth the toolpath generated in the CAM system.
To solve the problems of high cutting forces, severe tool wear, and poor surface integrity faced by advanced materials in aerospace manufacturing, multi-dimensional vibration machining (MDVM) is receiving unprecedented attention. MDVM utilizes workpiece and/or tool vibration excited in different directions to achieve high quality and efficient machining of aeronautical hard-to-cut materials. This paper covered typical MDVM hardware systems based on different vibration mechanisms, vibration application methods, and control methods, discussed the machining mechanisms such as friction reversal and contact-separation, and displayed the application effects in extending tool life, improving surface integrity, and manufacturing functional surfaces. The diversity of vibration mechanisms and the complexity of vibration modes of the MDVM system made it difficult to develop a unified design method for vibration systems and to demonstrate the machining mechanism under the coupling of different ultrasonic-induced effects. Therefore, it is an important development direction for future research to investigate the vibration and machining characteristics of MDVM systems and reveal the unified law.
Phononic crystal (PnCs) is one of the metamaterials focusing on the wave controls. The fabrication of this metamaterial is the key for its further industrial applications. Due to the advantage on the direct combination of computer-aided design, additive manufacturing (AM) is one of the most efficient manufacturing technologies for the fabrication of this wave controlling metamaterial. Here we reviewed the recent applications of AM on the fabrication of the wave-controlling metamaterials. The new features generated from the printing of the metallic parts like quick temperature changes in heating and cooling and re-melting and reheating were introduced. The theoretical and numerical developments on the printing of alloys were combined with the existing knowledge on metallurgy for the explanations of the changes of mechanical properties. The variations of mechanical properties, the residual distortions, and the property-oriented design of AM were introduced with the focus on the shift of band gap characteristics from the theoretical design in the wave-controlling metamaterials. The relationship between the process parameters and the structural performance of the wave-controlling metamaterials and the mechanical properties of the AM objects were mainly summarized.
In the milling process, it is easy to produce chatter due to the low rigidity of the thin-walled structure, which leads to the deterioration of workpiece surface quality and reduces the service life of cutting tools and machine tools. Therefore, a new chatter detection method for thin-walled parts based on optimal variational mode decomposition (OVMD) and refined composite multi-scale dispersion entropy (RCMDE) is proposed in this paper. Firstly, to solve the problem that the decomposition effect of the variational mode decomposition (VMD) algorithm is greatly affected by its parameter, a genetic algorithm (GA) is used to iteratively optimize the parameter of the VMD algorithm, and a new index, square envelope spectral correlated kurtosis (SE-SCK), is introduced as the fitness function of the genetic algorithm. Then, the energy ratio of the decomposed signal is calculated as the principle of selecting sub-components, and the sub-components with rich chatter information are selected for signal reconstruction. To solve the problem that the multi-scale dispersion entropy (MDE) will miss some information in the multi-scale process, RCMDE is introduced to detect milling chatter. Finally, the experiment of the variable cutting depth in side milling of titanium alloy thin-walled parts is carried out. The experimental results show that the OVMD algorithm proposed can solve the problem of difficult separation of chatter frequency bands caused by mode aliasing and lay a foundation for subsequent chatter feature extraction. RCMDE is more conducive to chatter detection than the single-scale DE when the scale factor is 4. The distinguishing effect of RCMDE on the machining state is more than 50% higher than that of MDE when the scale factor is 4.
As a promising surface modification method, nanosecond pulsed laser nitriding has been widely employed in enhancing the surface hardness and chemical corrosion of Zr-based metallic glass (MG). However, laser nitriding generally leads to poor finished surface quality, limiting its potential applications. For flattening the laser-nitrided surface, the most common methods, i.e., mechanical polishing (MP) and a novel proposed flattening approach, laser polishing (LP), were comparatively studied. A systematical comparison between MP and LP on three types of laser-nitrided surfaces was performed to evaluate the surface roughness, surface hardness, and plastic deformation. The experimental results indicate that the surface roughness of these three laser-nitrided surfaces is reduced by 56.4%, 58.1%, and 44.6% by MP. In contrast, a remarkable improvement in the surface quality is achieved with a maximum reduction in surface roughness by 80.4%, 81.5%, and 74.2% by LP, respectively. While in terms of the surface mechanical properties, the LP surfaces exhibit slightly lower hardness than the corresponding MP surfaces, which are both enhanced in hardness compared with as-cast MG. Additionally, no matter on the MP or LP surfaces, the shear bands and serrated flows have been significantly suppressed compared with as-cast MG, demonstrating that the micro-scale plastic deformation of as-cast MG has been modified. Although the obtained results indicate that the surface roughness of the laser-nitrided surface could be improved by both MP and LP, in terms of environmental friendliness, flexibility, and controllability, the LP shows dominant advantages and enormous potential in industry and consumer products.
A recent trend in micro-EDM is the addition of powders into the dielectric. The presence of powders helps to lower the dielectric breakdown voltage and, therefore, the discharge occurs early. As a result, the discharge energy is better distributed, resulting in a greater number of discharges, each with less energy. The main advantage of using this method is the improvement of both the process performance and surface finishing of the workpiece. In general, a critical aspect of the implementation of this technology is the management of the powder. In fact, to obtain advantages during the machining, the powders should be maintained dispersed into the dielectric to avoid their aggregation. This paper aims to study the concentration of the powder and the surfactant in the dielectric fluid on micro-EDM drilling performance. Titanium alloy was used as workpiece material, hydrocarbon oil as dielectric, graphite as powder, and 4-dodecylbenzenesulfonic acid as surfactant. The performance was evaluated considering the material removal rate, the tool wear ratio, and the geometrical characteristics of the holes (overcut and taper rate). Graphite content positively affected both material removal rate and tool wear ratio; a larger spark gap was observed as well. The use of surfactant is required for mix stability, but increasing its percentage generally reduces the effects of graphite and increases data dispersion as well.
As the first study in the field regarding CB, this paper investigates the implications of interchanging between RDB and CB through manufacturing bends with various angles and investigates the difference between the two methods in form of springback, cross section compression and widening, cross section shape and wall thinning/thickening. The experiments conducted consists of aluminum alloy 6060-T4 round tubes of 60 mm diameter and 3 mm wall thickness, bent around 222 mm radius tooling with various bend angles. In this case, we have found that CB is capable of manufacturing bends with quality near those manufactured by RDB with less springback, however with a dimensional penalty regarding increased deformation of the cross section.
In mirror milling of thin-walled parts, the machining path and change in tool axis vector will affect the surface quality of the workpiece and machining efficiency. Reasonable planning of the tool axis vector can avoid the occurrence of overcutting and undercutting and prevent a collision between the tool and the workpiece and damage of the spindle. At the same time, the rapid change in tool axis vector will also affect the machining quality, so optimization of the tool axis vector is very important in mirror milling. In this paper, the optimization of the tool axis vector for titanium alloy skin processing is divided into two steps. The first optimization is carried out on the basis of the planning of the machining path. First, the machining path is obtained according to constraints of mirror milling, and the iterative algorithm of the tool position is used. The tool location point is obtained, and then the tool location point is projected onto the parameter plane to optimize the tool axis vector. The second optimization is to optimize the tool axis vector based on kinematic constraints. The rotation axis of the machine tool needs to meet the constraints of the maximum angular velocity, the maximum angular acceleration, and the maximum angular jerk. First, the optimal feed rate of the mirror milling machine tool is obtained. The tool axis vector is optimized for optimization goals with minimum motion fluctuation stop and minimum adjacent machining time. Subsequently, the optimized machining path and the tool axis vector were simulated and tested. Finally, the simulation and experimental results were determined by an analysis that proved the feasibility of the optimized model proposed in this paper. At the same time, the results of the experimental measurements also showed that the optimized machining path had been greatly improved in terms of quality and efficiency.
In order to study the influence of machining methods and parameters on the surface quality of carbon fiber reinforced composites (CFRP) in the cutting process, the finite element simulation model of ultrasonic-assisted cutting CFRP was established, the simulation results show that the introduction of ultrasonic reduces the damage degree of CFRP in the cutting process, and the tool attached torsional ultrasonic vibration effect is the most significant. The ultrasonic-assisted torsion and longitudinal cutting tests of CFRP disc were carried out respectively, and compared with the ordinary cutting process, the experimental results show that the introduction of ultrasonic changes the fracture mode of fiber and effectively reduces the surface roughness. The fiber cutting angle (the angle between the cutting speed direction and the fiber direction) is the main factor affecting the surface roughness of CFRP, the effect of ultrasonic is better in the low-speed area, and the direction of fiber can be weakened by high-speed processing. When the amplitude is in the range of 0 ~ 6 μm, with the increase of amplitude, the advantage of ultrasonic is more obvious, and the inhibition of the influence of fiber directivity is more obvious. The results show that large amplitude and small cutting speed can achieve better ultrasonic machining effect; large vibration amplitude and high cutting speed can effectively suppress the influence of fiber directivity. The results are helpful for the high-quality processing of CFRP and other composite materials.
This study quantifies the in situ powder bed density variations and the statistical significance of the impact of these variations on the number of defects and fatigue performance for additive manufacturing Ti–6Al–4 V components. This study shows that the in situ powder bed density may vary up to 2–3% by varying the location on the build plate, recoater type/speed, and layer thickness when the standard gas-atomized Ti–6Al–4 V powders are used. These variations result in considerable changes in the number of lack of fusion defects. However, the impact of the change in the number of lack of fusion defects on the fatigue performance is statistically insignificant (p-value > 0.05) despite showing changes in the obtained mean values.