Workpiece Surface Research Articles

Tool life assessment of high strength cast iron alloys in dry face milling operations

The advancement in cast iron alloy properties has led to more efficient materials, especially in the automotive industry. However, this progress has also increased the demand for more durable tools with greater resistance to cutting operations. Conducting an in-depth investigation into the impact of these materials on tool lifespan is crucial, as it directly affects productivity. The main objective of this study was to analyze the lifespan of uncoated cemented carbide tools during milling operations using four high-strength cast iron alloys under various dry cutting conditions. A full factorial Design of Experiment (DoE) (23) was employed. The input variables included cutting speed (vc) of 230 and 350 m/min, tool feed (fz) of 0.1 and 0.2 mm/tooth, and materials, namely cast irons (FC 250, FC 300(Mo), FC300(Mo+RG), and FV 450). Additionally, material tests were conducted on billets without holes to simulate mild cutting conditions and with holes for more severe machining conditions. The established machining operation was face milling without cutting fluid, with the axial depth of cut (ap) and radial depth of cut (ae) maintained constant at 1 mm and 60 mm, respectively. The results showed that FV 450 had the shortest tool life, as expected for the hardest and resistant material, with a maximum lifetime difference of 83 % less when compared to FC 250, the softest one that had the longest tool lifespan. The introduction of holes also significantly reduced the overall tool life by about 57 %. The findings highlight the importance of factors such as cutting speed, feed per tooth, material composition, impact, and workpiece surface quality, which significantly influence tool performance.

Toward Optimal Robot Machining Considering the Workpiece Surface Geometry in a Task-Oriented Approach

Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot’s task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments.

Force servo nano-precision diamond cutting of freeform surfaces on a micro-precision machine

This paper presents force servo single point diamond cutting of freeform surfaces with nano-precision on a micro-precision machine. For nanometric machining accuracy, traditional diamond cutting based on position servo, requires accurate machine axial motions by ultra-precision machine with high cost, or utilizes a fast tool servo to compensate for machine slide vibration and motion error of common machines that is a complicated procedure. In this paper, nanometric machining accuracy was achieved on a micro-precision machine by force servo diamond cutting, in which the tool can be driven to trace the workpiece surface to compensate for the machine slide vibration, machine motion errors and workpiece incline errors accurately and automatically. For highly sensitive and stable force controlling, force servo nanocutting mechanism (FSNM) based on flexible structures was designed with force sensing resolution down to submillinewton level, and a damping controller was developed to suppress the resonant vibration of the FSNM. For extending application of force servo cutting from fabrication of only discontinuous microstructures to continuous freeform surfaces, referring force maps were developed by considering the real material removal volume of each cutting point. Force servo cutting was then validated by fabricating freeform surfaces with surface form errors of less than 10 nm on silicon spherical surfaces based on the micro-precision machine. The works discussed in this paper provide an effective technique for the fabrication of complex and continuous microstructured and freeform surfaces with nano-precision by common machines only with micron even tens of microns precision.

A Method for Measuring Shaft Diameter Based on Light Stripe Image Enhancement.

When the workpiece surface exhibits strong reflectivity, it becomes challenging to obtain accurate key measurements using non-contact, visual measurement techniques due to poor image quality. In this paper, we propose a high-precision measurement method shaft diameter based on an enhanced quality stripe image. By capturing two stripe images with different exposure times, we leverage their different characteristics. The results extracted from the low-exposure image are used to perform grayscale correction on the high-exposure image, improving the distribution of stripe grayscale and resulting in more accurate extraction results for the center points. The incorporation of different measurement positions and angles further enhanced measurement precision and robustness. Additionally, ellipse fitting is employed to derive shaft diameter. This method was applied to the profiles of different cross-sections and angles within the same shaft segment. To reduce the shape error of the shaft measurement, the average of these measurements was taken as the estimate of the average diameter for the shaft segment. In the experiments, the average shaft diameters determined by averaging elliptical estimations were compared with shaft diameters obtained using a coordinate measuring machine (CMM) the maximum error and the minimum error were respectively 18 μm and 7 μm; the average error was 11 μm; and the root mean squared error of the multiple measurement results was 10.98 μm. The measurement accuracy achieved is six times higher than that obtained from the unprocessed stripe images.

Machine learning coupled with acoustic emission signal features for tool wear estimation during ultrasonic machining of Inconel 718

The material removal in the ultrasonic machining process is due to the fracture of the workpiece material. The fracture is due to energy transfer by vibrating abrasive particles. The vibration energy is induced by a tool oscillating at a frequency of more than 20 kHz. The vibrating particles not only impact the workpiece surface but also impact the oscillating tool, and it leads to the fracture of the tool, which is of interest to understand to guarantee efficient machining with accuracy and precision. In the current investigation, the tool wear during the ultrasonic machining of Inconel 718 super alloy is attempted. An acoustic emission sensor is integrated with the machining setup, and signal information is extracted in the time and time-frequency domains. The features and process parameters are input to a support vector regression model to estimate tool wear. The model developed for tool wear prediction yields an accuracy of 96.13% compared to the model developed with only process parameters, which delivers an accuracy of 84.89%. The developed model can be beneficial for the real-time monitoring of tool wear during the ultrasonic machining process for industrial and remote applications.

Reluctance Based Actuator for Discrete Machine Hammer Peening

In machine hammer peening, an actuator system moves a ram in oscillating motion, which is oriented in angular position, preferably perpendicular, to a workpiece surface. On the tip of the ram, a hammer head with application specific shapes can be mounted. The hammer head is moved across the targeted workpiece surface area by means of a machine tool or an industrial robot. The impacts in defined patterns enable modifications of the surface integrity like smoothing the surface roughness or increasing fatigue strength by induced compressive residual stresses. This paper presents a novel DC-driven actuator system using a highly dynamic short-stroke linear reluctance motor to provide a time or trigger controlled hammer head movement including a system for process monitoring. In contrast to conventional systems, Deterministic Impact Peening (DIP) can be realized by position or speed related triggering of the impacts. The reluctance-based actuator with its geometrically optimized mechatronic system design provides performance characteristics favorable to known machine hammer peening systems. The position-controlled triggering of the hammer head is able to achieve uniform or defined local elastoplastic deformations on the workpiece surface, thus resulting in deterministic residual stress distributions.

A model based material removal simulation for vacuum suction blasting of composites

Automated scarfing of carbon reinforced plastic (CFRP) layers is on its way to support commercial aircraft repair. In the industry, still, the manual scarfing operation is the qualified method. However, automated techniques as milling, laser removal and water jet cutting are in development and showed already good results. Another promising method is vacuum suction blasting (VSB) that was until now in particular used for the roughening of surfaces before adhesive bonding. To find the right adjustment for the parameters many experiments would be necessary accordingly to different CFRP parts with changing layer thicknesses. Simulation is a way to avoid this and to predict the removal result and the settings for the machining parameters. The VSB model uses a pixel method dividing the simulated part surface into smaller volume elements. Experimental data of VSB static blasting spots are the basic for the source matrix. The simulation feeds the matrix with the blasted depth and removal volume for different blasting times. A shifting of columns of the source matrix in the blasting movement direction simulates the movement of the blasting nozzle on the work piece surface. With this, the model can also predict the nozzle feed to remove exactly one complete layer for each scarfing step. In addition, it visualizes the seamless overlapping distance between two blasted tracks. With further adjustments, the model will predict the dynamic removal for varying input parameters such as negative pressure and nozzle distance or blasting agent.

Self-lubricating performance of a grinding wheel filled with CNTs@T304 nano-capsules

This paper introduces a new grinding wheel which lubricates the grinding area directly. This is achieved by filling a resin grinding wheel with nano-capsules comprised of carbon nanotubes (CNTs) and di-n-butyl phosphite (T304) (CNTs@T304). The CNTs@T304 nano-capsules filled grinding wheel reduces the grinding force, lowers the grinding temperature, and improves the workpiece surface quality. The T304 lubricant is first filled into the CNT cavity to prepare nano-capsules, which exhibit better friction and wear quality than CNTs. Then the paper analyzes the configuration of the nano-capsules in the grinding wheel, together with the investigation of how the filling content impacts the mechanical properties. Additionally, the effects of nano-capsule filling content and grinding parameters on grinding force, grinding temperature, grinding ratio, as well as workpiece surface roughness are studied and the self-lubricating mechanism of the nano-capsules is assessed. According to the experimental results, nano-capsules maintain stable under thermal condition and resist the curing temperature. Moreover, the tensile strength and hardness exhibited by the grinding wheel still meet the application requirements at a filling content <16 wt%. Compared with the grinding wheel without fillers, the nano-capsule filled wheel exhibits superior grinding performance, with a 33 % reduction in the grinding force. Also, the grinding temperature is 28 % lower, there is a 30 % improvement in the grinding ratio, and the workpiece surface quality increases by 35 % under the same conditions. The T304 in the nano-capsules is continually released onto the grinding interface with the wear of the wheel in the grinding process, which forms a self-lubricating layer along with the friction products of the CNTs. This exerts an outstanding anti-friction and anti-wear effect, thereby improving the grinding performance.

Investigation of Surface Characteristics in Magnetic Field assisted Electrical Discharge Machining

Electrical discharge machining (EDM) has demonstrated its promising potential for surface modification. The integration of materials from tool electrode or powder that is mixed into the dielectric fluid has proven to modify the workpiece surface to enhance its mechanical properties, realize antibacterial effects, or increase biocompatibility.Recent EDM studies showed that due to non-contact forces, properties of the modified surface such as roughness values and the thickness of modified layer were significantly influenced when using magnetic field assisted EDM. Consequently, in this study, an external magnetic field with a strength of 0.66 T is used to assist the material transfer from tool electrode to workpiece surfaces during the EDM process. Pure silver and copper tools with a diameter of 2 mm are used to modify surfaces of Ti6Al4V workpieces at a discharge energy of 125 µJ with different polarities. Results show that the assistance by magnetic field significantly increases the content of transferred material from tool electrode to the workpiece surface. Additionally, it increases material removal rate and reduces the modified layer thickness. Magnetic field assisted EDM is a potential technology for improving the efficacy of the EDM surface modification.

Controlled Synthesis of TiB2-TiC Composite: Substantiation of the Homogenizing Joule Thermostatting Efficiency and Improvement of SHS-Compaction Technology in a Vacuum

This research aims to improve and substantiate the efficiency of homogenization heat-stabilizing Joule heating on ceramic-matrix composites of TiB2-TiC system with a 2:1 component ratio during its synthesis. For this purpose, an improved technological approach is proposed, which is based on the known method of SHS-compacting but differs by the possibility of controlled Joule influence on the synthesis products, which is achieved by the use of a special electrothermal vacuum press-mold functioning according to a particular control algorithm. The task of controlled Joule heating is a compensation of the temperature gradient formed in the synthesized workpiece, which is solved by passing in it a direct current directed in line with the vector of propagation of the combustion wave. An indicator of assessment of the degree of compensation of the noted temperature gradient is the Seebeck effect, excited between the upper and lower surface of the SHS workpiece, which should be brought to zero in the process of Joule thermostatting. It was experimentally revealed that compensation of the noted temperature gradient with heat released predominantly by electrically conductive and Joule-heated TiC grains leads to their softening, which contributes to more uniform compaction of the workpiece due to diffusion coalescence of these grains around prism-shaped hard TiB2 crystals. Such consolidation leads to a significant increase in the quality of structural packaging and a reduction in the number and volume of micropores, as a result of which the performance properties of the composite improve on average by 10–15 %.

Assessment of the roughness of the machined surface during pendulum surface plastic deformation

The influence of pendular surface plastic deformation mode on the roughness parameters of the machined surface of a cylindrical workpiece is studied. The optimal values of the processing mode parameters are determined. Keywords surface plastic deformation, roughness parameters, experimental study, device for pendular motion

Effect of material composition on the action of surface active medium in ultra-precision microcutting

Ultra-precision diamond turning (UPDT) is an extensively adopted technology in optical applications owing to the nanometric surface finish and excellent form tolerance guaranteed on metallic materials. Coolants such as kerosene, isoparaffin etc. are broadly used in UPDT to reduce the friction at tool-workpiece interface for ultimately ensuring optical quality parts. However, the greater emphasis on sustainable manufacturing nowadays demand alternate approaches for minimizing cutting forces and improving the surface finish. The application of a surface active medium (SAM) over the workpiece surface prior to UPDT can be a befitting choice as it can induce Rehbinder effect on materials thereby minimizing cutting forces. Nevertheless, the performance of SAM in UPDT process with reference to material specific properties has not been widely explored in literature. The present study investigates the role of Rehbinder effect in controlling the material surface energy during UPDT of ductile materials. The surface integrity and force analysis indicate that the SAM action is significantly different for the parent metal (Cu) and alloy (Brass) under consideration. Moreover, the chip morphology inspection highlighted that SAM facilitates easier crack initiation and fracture in Cu unlike Brass. The results were further confirmed by conducting experiments on pure Zinc. Thus, the present study establishes the varying effectiveness of SAM towards material specific elemental composition.

Experimental Investigation on the Surface Integrity in Micromilling AISI H11 Tool Steel

The surface integrity of machined components affects their fatigue performance and service life. Thus, with a view to sustainability and resource efficiency, aspects that influence the nature of the workpiece surface and sub-surface are increasingly considered in the process design, such as the resulting microhardness or the residual stress state. In this context, micromilling offers the possibility to positively influence the sub-surface properties due to the low thermal impact as well as concentrated mechanical load during machining. In order to gain a deeper understanding of the potential of micromilling for surface conditioning, experimental investigations were carried out on samples of the hot work tool steel AISI H11 in hardened condition. Cutting forces and surface topography were measured at different feed per tooth. The depth-dependent microhardness and residual stresses were determined after machining and analyzed taking into account the engagement situation and cutting forces. As the results show, micromilling can induce high compressive residual stresses as well as increase surficial microhardness while achieving low roughness topographies. This represents a great potential for improving component properties regarding tribological performance as well as fatigue behavior.

Multi-material additive manufacturing through electrostatic metal powder attraction and laser-induced forward transfer

The possibility to produce multi-materials and functionally graded materials opens new opportunities within material development, not only to explore new possibilities for combinations of different materials, but also to develop entirely new materials. Materials that are customized for individual applications and purposes down to the level of a single product. Here a process is described, where applied voltage onto a machine element results in an electrostatic attraction of powder. The machine element has certain electrical abilities and is transparent to certain wavelengths of light. The powder attraction is relatively uncomplex using a high DC voltage source with low amperage. The attracted powder on the machine element is selectively transferred to the workpiece by using laser-induced forward transfer (LIFT). The final goal is to melt the transferred powder onto the workpiece with the laser from LIFT. This part of the process and its developments are discussed in detail. Thereby, the powder is selectively added to the workpiece surface, making it possible to apply a combination of different materials without contaminating the powder stock.

Touch-trigger probe error compensation for nonvertical on-machine measurement of freeform surface workpieces

Touch-trigger probe error compensation for nonvertical on-machine measurement of freeform surface workpieces

CONTROL SYSTEM FOR WATERJET CUTTING PROCESS WITH SWIRLING WORKING FLUID JET

In mechanical engineering, the procurement process is one of the most important in the life cycle stage of manufacturing products from metal materials. In this regard, there are disadvantages in the manufacture of parts: low productivity, complexity and high cost of cutting tools, and the impossibility of cutting. The work proposes an approach to increase the productivity of using the cutting properties of abrasive grains and expanding the contact area of a waterjet jet with the workpiece surface being processed by twisting the jet and adjusting the values of the jet oscillation frequency to the thickness of the workpiece. As a result of research verification, the approach showed good prediction accuracy.

Adaptive Ultrasonic Full Matrix Capture Process for the Global Imaging of Complex Components with Curved Surfaces.

This work proposes a new global FD-RTM method to solve the problem of ultrasonic inspection of parts with complex geometric shapes. With this method, the frequency domain reverse time migration (FD-RTM) algorithm is used to adapt to the complex refraction of ultrasonic waves by the surface, while an interface solution algorithm based on tangent fitting is used to solve the interface position with high precision through the full matrix reception data. Based on high-precision interface information, a hybrid extrapolation algorithm and a situation-specific probe movement strategy are used to enable the probe to find the next sampling point according to the direction of the workpiece surface, allowing complex surface topography features to be identified without relying on the workpiece CAD drawing. This makes it possible to achieve the automated inspection of workpieces. To verify the proposed method's effectiveness, an aluminum alloy model with side-drilled holes (SDH) is used. The geometry of the model consists of multiple convex and concave surfaces. By comparing the local FD-RTM imaging with images synthesized using the entire scan path, it is shown that gFD-RTM improved the imaging performance. Compared with FD-RTM, the average signal-to-noise ratio of gFD-RTM was increased by 20%, and the array performance index (API) was reduced by 70%, indicating effective detection coverage.

Stress Distribution in Wear Analysis of Nano-Y2O3 Dispersion Strengthened Ni-Based μm-WC Composite Material Laser Coating.

Oxide-dispersion- and hard-particle-strengthened (ODS) laser-cladded single-layer multi-tracks with a Ni-based alloy composition with 20 wt.% μm-WC particles and 1.2 wt.% nano-Y2O3 addition were produced on ultra-high-strength steel in this study. The investigation of the composite coating designed in this study focused on the reciprocating friction and wear workpiece surface under heavy load conditions. The coating specimens were divided into four groups: (i) Ni-based alloy, nano-Y2O3, and 2 μm-WC (2 μm WC-Y/Ni); (ii) Ni-based alloy with added 2 μm-WC (2 μmWC/Ni); (iii) Ni-based alloy with added 80 μm-WC (80 μmWC/Ni); and (iv) base metal ultra-high-strength alloy steel 30CrMnSiNi2A. Four conclusions were reached: (1) Nano-Y2O3 could effectively inhibit the dissolution of 2 μm-WC. (2) It can be seen from the semi-space dimensionless simulation results that the von Mises stress distribution of the metal laser composite coating prepared with a 2 μm-WC particle additive was very uniform and it had better resistance to normal impact and tangential loads than the laser coating prepared with the 80 μm-WC particle additive. (3) The inherent WC initial crack and dense stress concentration in the 80 μm-WC laser coating could easily cause dislocations to accumulate, as shown both quantitatively and qualitatively, resulting in the formation of micro-crack nucleation. After the end of the running-in phase, the COF of the 2 μm-WC-Y2O3/Ni component samples stabilized at the minimum of the COF of the four samples. The numerical order of the four COF curves was stable from small to large as follows: 2 μm-WC-Y2O3/Ni, 2 μm-WC/Ni, 80 μm-WC/Ni, and 30CrMnSiNi2A. (4) The frictional volume loss rate of 2 μm-WC-Y2O3/Ni was 1.3, which was significantly lower than the corresponding values of the other three components: 2.4, 3.5, and 13.

Kinematics and trajectory analysis of swinging fixed abrasive plane lapping: Effect of swinging mode on the lapping uniformity

The relative motion between the workpiece and the fixed abrasive pad (FAP) determines the abrasive trajectories and the distribution of abrasives' sliding distance (ASD), and further affects the surface accuracy of the lapping process. To improve the surface accuracy of the swinging fixed abrasive plane lapping (SFAPL), the influence of the workpiece's swinging modes on the lapping uniformity was studied in this paper. The kinematics model of SFAPL was established by the coordinate transformation method based on the kinematical principle of the crank-rocker mechanism. The numerical simulation method was adopted to investigate the abrasive trajectories and the ASD on the workpiece surface in different swinging modes. Furthermore, the regional meshing and statistical methods were applied to visualize the simulation results, and the non-uniformity coefficient (NUC) and root mean square (rms) were employed to quantitatively evaluate the lapping uniformity. Finally, the verification experiments were carried out. Results indicated that the additional swinging could avoid the periodic distribution of material removal on the workpiece surface. The swinging mode significantly affected the lapping efficiency and lapping uniformity. Compared with the traditional lapping method, the lapping uniformity was optimal when the workpiece swung out of the FAP from the bottom and inner sides, and the lapping uniformity could be improved by 44.3 %; The lapping efficiency was the highest when the workpiece swung out of the FAP from the bottom side, and the material removal rate could be increased by 45.23 %. The appropriate swinging mode should be selected based on different processing requirements in SFAPL.

Slender defect segmentation network of workpiece surface based on deep learning

As a key part of the workpiece production process, workpiece surface defect segmentation detection plays an important role in the quality assurance of the workpiece. Aiming at the problem of low accuracy of workpiece surface slender defect segmentation, we propose a slender defect segmentation network based on feature enhancement module (FEM) and feature fusion module (FFM). Firstly, the ConvNeXt is improved and used as the backbone network. Then, the FEM is designed to obtain rich defect features. Finally, the FFM is designed to expand the receptive field and fuse shallow features with deep features to enhance the features of slender defects. The proposed method improves the segmentation accuracy of slender defects. The mean pixel accuracy) of slender defect segmentation on the self-built diode glass shell dataset and public magnetic sheet dataset is 97.87% and 94.86%, respectively. The mean Intersection over Union of slender defect segmentation is 94.32% and 83.89%, respectively. The segmentation speed reaches 43FPS, and the parameter is 7.12 M, which balances the segmentation accuracy, speed and model size.