Workpiece Profile Research Articles

INFLUENCIA DE UNA VIBRACIÓN SIMPLE EN EL PERFIL DE ONDULACIÓN DE PIEZAS TORNEADAS

The generation of the surface topography in machining is a complex process whereby the dynamics of the machine-tool and the kinematics of the cutting process are combined. The purpose of developing a surface topography simulation model in turning is to predict the combined effect of the tool geometry, process parameters, and relative tool-workpiece vibration. The simulations demonstrate that a single vibration frequency can generate multiple wavelengths on the workpiece profile. The correlation between machine-tool vibrations and surface topography is applied to accurately diagnose the machine defect that results in poor surface quality in a cylindrical turning process. Key words: surface topography, tool-workpiece vibration, waviness profile

Geometric analysis and design of circular form tools

Abstract Supposing serial or quantity production of cylindrical workpieces having complex geometry the application of circular form tool is applicable. This type of cutting tool has complex geometry as a consequence the geometric and the manufacturing design take a lot of time and cost but it is economical since the cutting process is quite fast. In addition, the tool usage is feasible on conventional or CNC controlled machines and the process is independent from the workers’ facility. The tool profile is the conjugated pair of the workpiece profile. This tool geometry has high resharpening area that is advantageous comparing other form tools. The goal of this study is the manufacturing analysis and the geometric design of those tools. The geometric design process will be determined detailedly in constructional and mathematical way. After them a concrete tool generation process including CAD design will be shown.

Uncertainty propagation from probe spacing to Fourier 3-probe straightness measurement

Reliable and precise straightness profile measurements are crucial for manufacturing ultra-precision components and are capable of further enhancing their accuracy. The Fourier three-probe (F3P) straightness measurement allows for precise assessment of the workpiece profile on the machine by eliminating the harmful influence of the error motion of the sliding table. However, the probe spacing uncertainty deteriorates the measurement accuracy remarkably; and, the affecting mechanism behind this phenomenon has not yet been studied in detail. In this context, this paper thoroughly investigated the propagation of the probe spacing uncertainty in the F3P measurement. First, the influence of the probe spacing deviation is analyzed. Next, by calculating the partial differential of Laplace transform of the workpiece profile, we algebraically deduce the probe spacing uncertainty propagation law, especially in the harmonic domain. Subsequently, Monte Carlo simulations are carried out to confirm the derived propagation law. To reduce uncertainty propagation, a hybrid approach is presented: (I) F3P measurements are carried out under changing probe spacings to produce several sets of Fourier coefficients; (II) optimal harmonic estimates are selected individually according to the harmonic uncertainty. Finally, simulations and experimental measurements are performed for verification.

Effect of Vibration Direction on Vibration-Assisted Fixed Abrasive Polishing

In order to study the effect of vibration direction on vibration-assisted fixed abrasive polishing and explore the influence rule of vibration direction on material removal rate and workpiece surface quality, a single abrasive particle vibration-assisted fixed abrasive polishing model was established to study the effect of axial and radial vibration on workpiece profile depth, surface morphology, etc. And the experiments of vibration-assisted fixed abrasive polishing in different vibration directions were carried out. The results show that axial vibration auxiliary polishing can greatly advance the processing efficiency, and improve the workpiece material removal rate by 27.6%; radial vibration auxiliary polishing can achieve better surface quality, and reduces the surface roughness by 59.8%.

A High-Precision Multi-Beam Optical Measurement Method for Cylindrical Surface Profile.

To automatically measure the surface profile of a cylindrical workpiece, a high-precision multi-beam optical method is proposed in this paper. First, some successive images for the cylindrical workpiece's surface are acquired by a multi-beam angle sensor under different light directions. Then, the light directions are estimated based on the feature regions in the images to calculate surface normal vectors. Finally, according to the relationship of the surface normal vector and the vertical section of the workpiece's surface, a depth map is reconstructed to achieve the curvature surface, which can be employed to measure the curvature radius of the cylindrical workpiece's surface. Experimental results indicate that the proposed measurement method can achieve good measurement precision with a mean error of the curvature radius of a workpiece's surface of 0.89% at a reasonable speed of 10.226 s, which is superior to some existing methods.

Irregular Workpiece Template-Matching Algorithm Using Contour Phase

The current template-matching algorithm can match the target workpiece but cannot give the position and orientation of the irregular workpiece. Aiming at this problem, this paper proposes a template-matching algorithm for irregular workpieces based on the contour phase difference. By this, one can firstly gain the profile curve of the irregular workpiece by measuring its radius in orderly fashion and then, calculate the similarity of the template workpiece profile and the target one by phase-shifting and finally, compute the rotation measure between the two according to the number of phase movements. The experimental results showed that in this way one could not only match the shaped workpiece in the template base accurately, but also accurately calculate the rotation angle of the irregular workpiece relative to the template with the maximum error controlled within 1%.

Accurate Inner Profile Measurement of a High Aspect Ratio Aspheric Workpiece Using a Two-Probe Measuring System

This paper presents a novel method for inner profile measurement and geometric parameter evaluation, such as the radius of the bottom, steepness and straightness of the steep sidewall of a high aspect ratio aspheric workpiece, by utilizing a two-probe measuring system, which includes a lateral displacement gauge for the inner steep sidewall profile measurement and an axial displacement gauge for the inner deep underside profile measurement. To qualify the measurement accuracy, the systematic errors associated with the measurement procedure, including the miscalibration, misalignment and the roundness error of the gauge probes, as well as the slide motion error of the four-axis motion platform, are all evaluated and separated from the measurement results. A point cloud registration algorithm is employed to stitch the evaluated inner sidewall profile and the inner underside profile to form an entire inner profile of the workpiece. To verify the performance of the newly proposed method, the inner profile of a high aspect ratio aspheric workpiece, which has a tapered cone shape with a maximum inner radius of 40 mm, a maximum inner depth of 140 mm and a steep sidewall angle approaching 85°, is measured in experiments. The measurement result is compared with that of a coordinate measuring machine (CMM), and the comparison verifies the feasibility of the proposed measurement system.

Multistage centerless grinding setup via discrete mapping

This article introduces a multistage approach for the execution of plunge centerless grinding operations aimed at accelerating waviness cancellation from workpiece initial profile, while preventing the harmful consequences of geometrical process instability. It suggests decomposing the process into multiple phases characterized by different workpiece heights and/or blade angle. The best parameters combination is identified by computing and analyzing the transition matrix of the overall process after a discretization of the profile evolution equation. Choosing to apply a two stages process, a map is computed with the most critical amplification gain of the harmonic components on the workpiece profile, for different heights combination. The gain map can be used to identify the height combination that guarantees a given roundness reduction with the minimal process duration for any initial profile. The analysis result is demonstrated comparing the effectiveness of a 2-stages process with the usual single stage process of the same duration.

A grinding force model in two-dimensional ultrasonic-assisted grinding of silicon carbide

Ultrasonic-assisted grinding (UAG) is a suitable machining solution for hard and brittle materials, effectively reducing cutting forces and improving the machined surface quality. With the development of UAG system, multi-dimensional vibration devices have emerged and been applied in the machining of advanced materials. In this study, a discrete numerical model is proposed for two-dimensional ultrasonic-assisted grinding (2D-UAG) of silicon carbide (SiC) to describe the dynamic cutting behaviors and a grinding force model considering the material removal mechanism is further established. In the model development, the three-dimensional surface topography of grinding wheel is simulated and adopted to determine the cutting state of individual grit. Meanwhile, a workpiece profile update procedure and a novel approach to realize the decomposition and synthesis of grinding forces are proposed. Experimental validation demonstrates that the prediction error of this proposed model is limited within 11.14% with an average value of 8.16% under conventional machining parameters. Furthermore, the tool amplitude and workpiece amplitude affect the grinding force in a similar manner. As the ultrasonic amplitude increases from 1 µm to 9 µm, the grinding force declines first and then goes up and the inflection point appears around 5 µm. The inherent characteristics of grinding forces in 2D-UAG of hard and brittle materials can be explained by obtaining the variation trends of the average cutting depth of individual grit and the number of active grains. The modeling methodology presented in this study provides a reference for studying the 2D-UAG process of brittle materials. • This model provides a reference for studying the grinding process in grit scale. • Applying two-dimensional vibration facilitates further reduction of grinding forces. • The effects of tool amplitude and workpiece amplitude are similar. • Setting the ultrasonic amplitudes to 5 µm is beneficial to reduce the grinding force.

Continuous multi-angle variation (CMAV) for faster roundness correction in centreless grinding

This paper presents a new methodology to improve roundness process of the centreless grinding based on classic stability diagrams and relative rounding mechanism. This study has shown that it is not always convenient to have a fixed setup angle. Based on simulation results, it is suggested to consider the raw workpiece profile before selecting these parameters accordingly to the type of raw workpiece roundness error (odd or even lobed). It was found that changing the setup angles from an initial appropriate point to a final point results in better simulated and experimented roundness. This changing was simulated with two methods, continuous and multistep, but the best results were achieved by the first one. Furthermore, a new support blade design for through feed centreless grinding is presented for application of the above-mentioned method.

Profile prediction in ECM using machine learning

ECM (Electrochemical Machining) with a micro-second pulsed power supply can decrease stray current corrosion and thus provide better surface quality on top of higher machining accuracy. However, the use of a pulsed power supply makes it challenging to predict the final workpiece profile based on the typical multi-physical-based FEM(Finite Element method) models. First, it is impractical to introduce high-frequency pulsed electric current (ns - µs) into a multi-physical model because of time step limitations. Second, there arise problems of compatibility of the time-steps within each physical module, as e.g. hydrogen bubbles have a lifetime of ms, the power supply would use μs, and thermal phenomena take ms. Multi-scale models have been proposed, but the prediction accuracies are rather low and computation times are very long. In this article, based on machine learning approaches, we present 3 data-driven ECM models for predicting the final workpiece profile when using pulsed-ECM: the linear regression (LR) model, the neural network (NN) model, and the convolutional neural network (CNN) model. After training this data-driven ECM model with different levels of pulse voltage and electrolyte flow conditions, predictions and experimental validation are conducted. Experiments with parameters outside the training parameter window are also carried out to show the performance and general applicability of our data-driven ECM model. The machine learning model shows a good generalizing ability, the CNN model presents a prediction MSE of 7.60. The present results also demonstrate that more accurate predictions will be achieved when using in-processing data. Hence, the prediction accuracy of data-driven models can be further improved on top of advancing in-processing monitoring systems.

An Integrated Approach of Simulation, Modeling and Computer-aided Design of Hot Abrasive Jet Machining Setup

In the past few decades, sophisticated machining industries have rapidly improved in order to achieve the required shape of a part within a specific time while also not affecting material properties. Accuracy of machined components in all industries is important. In the case of subassemblies of components, geometrical accuracy of hole is vital. The researchers updated their machinery from time to time from this perspective. In the machining process, environment and time are the vital parameters that are mainly affected, so in this case, the design of experiments that are very useful in the machining region needs to be considered to overcome these challenges. This study aims to analyze the fabrication of hot abrasive jet machining (HAJMing) with different abrasive temperatures using fluidized bed system as well as accomplishment of cutting performance in hot-abrasive jet machining concerning target surface erosion. Additionally, this research study accomplishes the experimental study and computational fluid dynamics (CFD) technique for erosive footprint prediction extent in HAJMing constraints on target surface for intricately shaped tapered holes generation. The use of hot abrasives in the HAJM process has demonstrated an interest in improving cutting performance for material erosion. Moreover, this proposed experimental work contains the manufacturing, design and fabrication of hot abrasive jet machine (HAJM) using commercially available hardware and software. So, the components are manufactured indigenously as per the designed parameters for the purpose of improving the machining performance. Simulation for material erosion mechanism of HAJMing is used to obtain the nature of produced workpiece profile. Additionally, FB-HAJMing also deals with the sustainability assessment under environmental-friendly hot abrasive-assisted machining conditions.

A calculation method for workpiece profile variation during double-sided lapping by considering workpiece elastic deformation

A calculation method for workpiece profile variation during double-sided lapping was developed in this study. In this method, shell element in FEM deformation was used to formulate elastic deformation of workpiece, and spring element was used to formulate the contact between workpiece and platens to calculate distribution of their contact pressure considering workpiece elastic deformation. First, the developed method of the contact pressure distribution was evaluated by comparing with a method using a FEM software and the existing methods, and was confirmed to be quite valuable in terms of applicable process and calculation time. Subsequently, the workpiece profile variation was calculated using the developed method for several workpiece conditions, and it was clarified that the uneven workpiece thickness can be modified by the process, but it is difficult to modify the bow shape when the workpiece is not small. Furthermore, the decrease of the load applied to the workpiece was suggested to modify the bow shape of the workpiece.

Investigation of the wear characteristics of microcrystal alumina abrasive wheels during the ultrasonic vibration-assisted grinding of PTMCs

As newly developed metal matrix composites, particulate-reinforced titanium matrix composites (PTMCs) have been eliciting increasing attention in the fields of aviation and aerospace due to their superior temperature durability and mechanical properties. Grinding is an important method for achieving high-efficiency and precision machining of PTMCs. However, the service life of abrasive wheels is severely affected under the action of alternating loads due to the existence of hard–brittle TiC particle reinforcements embedded into PTMCs materials. Ultrasonic vibration-assisted grinding (UVAG) is widely used at present for machining difficult-to-cut materials, particularly for improving the wear performance of abrasive wheels. In this work, comparative experiments on the conventional grinding (CG) and UVAG of PTMCs were conducted to investigate the wear properties of microcrystal alumina abrasive wheels. Moreover, characterisation of tool wear morphologies was performed. On the basis of the standard deviation of the Gaussian distribution of workpiece profile, active cutting edge density was evaluated. Lastly, grinding force and machined surface quality were analysed in detail. Results showed that CG caused severe adhesion and macrofractures, whereas UVAG produced slight adhesion and microfractures. UVAG also achieved lower grinding force and better surface quality than CG. Furthermore, UVAG provided a longer steady tool wear region than that in CG because ultrasonic vibration can enhance the self-sharpening characteristics of microcrystal alumina abrasive wheels during grinding.

Fuzzy Knowledge Base Controller to Condensate The Roundness Error in the Cylindrical Plunge Grinding.(Dept.M)

The paper describes theoretical and experimental analysis of dynamics of system: grinding wheel- workpiece external cylindrical plunge grinding process to study the effect of workpiece previous profile on the ground workpiece roundness. The study has been carried out theoretical model taking contact stiffness of system (workpiece and machine), grinding wheel and workpiece wear into consideration. The results showed that mode shape vibration errors are strongly depends on amplitude of initial workpiece profiles. The mode shape vibration errors increases with the increase of initial workpiece profiles amplitudes and workpiece length. Experiments had been carried out on identical specimens. These specimens were turned first with different cutting conditions to obtain different profiles. Then a cylindrical plunge grinding operation with the same cutting conditions was applied for the resulted specimens. The vibration signals existing during grinding were recorded. The resulted roundness error before and after grinding were compared for each specimens. The results showed the root mean square (RMS) of vibration level, roundness error and undulation number of the ground workpiece are dependent on the initial workpiece profile. The comparison between theoretical and experimental results showed as good agreements. To compensate roundness error within an acceptable range, fuzzy knowledge base controller (FKBC) was proposed. The proposed fuzzy controller predicts the work piece shape error more accurately, and reduces it by about 20%

Jet electrochemical machining simulation of intersecting line removals with adjustable nozzle diameter by a finite area element grid

Jet electrochemical machining (Jet-ECM) is a machining process which makes flexible surface structuring of metallic materials with nearly no tool wear possible. Through a nozzle cathode with an inner diameter of e.g. 100 µm a continuous electrolyte jet is applied to the workpiece surface. When an external voltage is applied, an electric charge is transported between the nozzle cathode and the anodically polarized workpiece, which causes a material removal on the workpiece based on anodic metal dissolution. By moving the nozzle cathode in x and y directions, material is removed along the contour movement of the nozzle. In the previous studies multiphysical models based on the Finite-Element-Method (FEM) or Finite-Volume-Method (FVM) were presented to simulate this removal processes. It can be derived, that the simulation of the resulting material removal for intersecting line removals is resource intensive and complex in commercially available software. Furthermore, a simulation of intersecting line removals with adjustable nozzle diameters with FVM or FEM is challenging. As a new approach a model based on a finite area element grid was built up in Python. The model applies square sections to represent resulting depth profiles of a machined workpiece. The paper explains the physical design of the model for a simulation of intersecting line removals with adjustable nozzle diameter. Such removals are shown by the help of transient calculations. The resulting depth profiles for different nozzle adjustments are discussed.

Evaluation of the tool wear in the turning process of INCONEL 718 using PCD tools

The use of nickel-based alloys (superalloys) has an ever-growing demand because of the combination of mechanical properties and corrosion resistance even at relatively high temperatures. Those same properties, however, increase the challenge to increase the cost-benefit of the machining operations. Nickel superalloys are usually machined using coated cemented carbide inserts at relatively lower cutting speeds or ceramic inserts at higher cutting speeds. The use of PCD tools, despite widespread at the machining process of titanium alloys, regarding the machining of nickel-based alloys has almost no research data, especially for Inconel. This happens mostly because of the alloys’ iron content leading to graphitization of the diamond at the tool. This paper presents a study about the viability of PCD tools in the turning process of Inconel 718 in finishing conditions. The machinability was assessed under different tool rake angles, cutting speeds, feed rates, and minimum lubrication flow rates. The results were compared regarding the specific cutting pressure, average workpiece profile roughness, tool wear and wear mechanisms observed through electronic microscopy. The results indicate that the rake angle did not have a statistically significant influence for the evaluated machining conditions and the feed rate was the most significant parameter, as it is linked with the specific cutting pressure and workpiece roughness. Adhered material seemed to have protected the rake surface from attrition, which reduced the amount of wear particles that promote abrasion of the flank surface. However, the increase in MQL flow seems to destabilize the adhered material and promote more severe wear. Overall, microchipping and adhesion were the most important wear mechanisms.

Improved measure of workpiece surface deterioration during turning using non-contact vision method

The surface finish quality of a machined workpiece is commonly measured using the average roughness parameter, Ra. This parameter, however, is insensitive to the lateral changes undergone by the surface in the feed direction as a consequence of tool wear. In this work, the effectiveness of four methods of workpiece surface analysis, namely autocorrelation, cross-correlation, and two new methods, called lateral material shift (LMS) ratio and profile slope ratio (PSR) analyses are investigated. Dry machining experiments were carried out on 316 stainless steel. Images of tool nose and workpiece profiles were captured using digital camera, and the edges were extracted using sub-pixel edge detection. In the autocorrelation approach, each workpiece profile was correlated with a shifted version of the same profile. In the cross-correlation approach, the workpiece profiles at different stages of machining were correlated with a reference profile generated using the unworn tool edge. In the LMS ratio method, the material shift ratios were determined from each waveform on the workpiece profile at various stages of tool wear, while in the PSR method the slopes at the right and left part of the waveform were compared. Among the four methods, the LMS ratio method produced the best correlation with tool flank wear with the maximum R-squared value of 0.9461, while average roughness Ra showed no correlation at all with both major and nose flank wear.

Roundness prediction in centreless grinding using physics-enhanced machine learning techniques

This work proposes a model for suggesting optimal process configuration in plunge centreless grinding operations. Seven different approaches were implemented and compared: first principles model, neural network model with one hidden layer, support vector regression model with polynomial kernel function, Gaussian process regression model and hybrid versions of those three models. The first approach is based on an enhancement of the well-known numerical process simulation of geometrical instability. The model takes into account raw workpiece profile and possible wheel-workpiece loss of contact, which introduces an inherent limitation on the resulting profile waviness. Physical models, because of epistemic errors due to neglected or oversimplified functional relationships, can be too approximated for being considered in industrial applications. Moreover, in deterministic models, uncertainties affecting the various parameters are not explicitly considered. Complexity in centreless grinding models arises from phenomena like contact length dependency on local compliance, contact force and grinding wheel roughness, unpredicted material properties of the grinding wheel and workpiece, precision of the manual setup done by the operator, wheel wear and nature of wheel wear. In order to improve the overall model prediction accuracy and allow automated continuous learning, several machine learning techniques have been investigated: a Bayesian regularized neural network, an SVR model and a GPR model. To exploit the a priori knowledge embedded in physical models, hybrid models are proposed, where neural network, SVR and GPR models are fed by the nominal process parameters enriched with the roundness predicted by the first principle model. Those hybrid models result in an improved prediction capability.

Effect of Vibration on Surface Roughness in Finish Turning: Simulation Study

This paper presents the results of simulation analyses carried out to investigate the effect of adding controlled vibration of varying amplitudes and frequencies onto simulated workpiece profiles on surface roughness. The surface profiles were generated using the nose edge image of a real cutting tool insert at various stages of wear. The invariant moment sub-pixel edge detection method was used to extract the precise tool nose profile. The extracted nose profile was duplicated 20 times to generate the simulated workpiece profile. Vibration signals in the form of sine waves of amplitudes 0 to 50 % of the peak-to-valley height of the original workpiece profile and various frequencies were added to the simulated profile. Noise signals emanating from real machining were also added to the original profile to investigate their effect on roughness. The simulation study has shown that average roughness may increase continuously or fluctuate randomly depending on the magnitude of vibration added to the vibration-free workpiece profile. In the absence of vibration, the surface roughness of the workpiece decreases due to flattening effect of the tool nose during early stages of tool wear.