A positioning error prediction method based on hybrid physical information neural networks ( Hybrid-PINNs) was proposed to solve the problem of heavy CNC lathe positioning accuracy which is difficult to reliably predict in few-shot and complex working conditions.By combining the easily obtained spatial position sensor data with the engineering approximate physical constraints (position continuity and smoothness), the data item and physical residual item were introduced into the neural network training objective at the same time, so as to improve the extrapolation and robustness of the model. Based on the actual measured data of Z-axis of a certain type of heavy lathe (Section A for augmented training, Section B/C for extrapolation test).The results show that the hybrid model demonstrates a significant improvement compared with the single model in test of Section B, Section C and the merged B C.In section B, relative to BP, PINNs reduced error by 60.4%, and Hybrid-PINNs further reduced it to 82.8%; relative to RBF, Hybrid-PINNs achieved a 70.1% reduction. In section C, relative to BP, PINNs reduced error by 82.0%, and Hybrid-PINNs further reduced it to 86.8%; relative to PINNs, Hybrid-PINNs still achieved a 76.9%reduction. In Section B and C, relative to BP, Hybrid-PINNs reduced overall error by 85.3%; relative to RBF, the reduction reached 79.0%. To ensure the engineering applicability, the article also detailed the preprocessing approach using sixth-order polynomial fitting and equidistant sampling, along with the model architecture, loss weighting, training procedure, and linear calibration workflow. The study provides a feasible technical path with both physical consistency and data-driven capability for online state monitoring and accuracy compensation of heavy machine tools.
The technique presents a simple yet efficient method for fabricating a mouth opening device designed to improve mouth opening functionality. The technique utilises a replicated metal rod, commonly employed for securing a polishing buff in a dental lathe. The fabrication procedure involves an impression with putty consistency of addition silicone impression material. The resultant sectioned putty template is securely fastened with an elastic band. The mouth-opening device can be made either by adding cold cure acrylic resin into the impression template or by producing a wax pattern, which is later processed with heat cure polymethylmethacrylate acrylic resins. The technique proves to be effortlessly simple and quick and readily adaptable in prosthodontic lab environments, distinguishing itself from alternative methods outlined in the literature.
With the growth of additive manufacturing (AM), there has been increasing demand for fabricating conformal electronics that directly integrate with larger components to enable unique functionality. However, fabrication of conformal electronics is challenging because devices must merge with host substrates regardless of curvilinearity, topography, or substrate material. In this work, we employ aerosol jet (AJ) printing, an AM method for jet printing electronics using ink-based materials, and a custom-made lathe mechanism for mounting flexible substrates and 3D objects on a rotating axis. Using this method of lathe-based AJ printing, conformal electronics are printed around the circumference of rotational bodies with 3D curvilinear surfaces through cylindrical-coordinate motion. We characterize the diverse capabilities of lathe AJ (LAJ) printing and demonstrate flexible conformal electronics including multilayer carbon nanotube transistors. Lastly, a graphene sensor is conformally printed on an inflated catheter balloon for temperature and inflation monitoring, thus highlighting the versatilities of LAJ printing.
The use of fibres applied to concrete in order to improve its properties is widely known. Nowadays, research is not only focused on improving mechanical properties but also on the environmental implications. The aim of this research was a mechanical and environmental comparison between different types of fibres. For this purpose, commercial fibres of three materials were used: low carbon steel, modified polyolefins, and glass fibre. In order to improve the sustainability of the sector, we also analysed and compared the performance of using a waste product, such as fibres from machining operations on lathes. For the evaluation of the mechanical properties, compression and flexural tests were carried out. The results show that the use of low carbon steel fibres increases the flexural strength by 4.8%. At the environmental level, and in particular for impact categories such as the Global Warming Potential (GWP), lathe waste fibres prove to be the most suitable. For instance, compared to glass fibres, CO2 emissions are reduced by 14.39%. This is equivalent to a total of 38 kg CO2 emissions per m3 of reinforced concrete. In addition to avoiding the consumption of 482 MJ/m3 of fossil fuels, the results of the research indicate the feasibility of using waste fibres as a substitute for commercial fibres, contributing to an improved environmental balance without losing mechanical performance.
The proper selection of surface topography (ST) parameters is crucial for ensuring the effective performance of machine components, including their wear and corrosion resistance. In the literature, research on the ST of hardened stainless steels (SSs) after finish turning using cubic boron nitride (CBN) inserts, as well as comparisons with cemented carbide (CC) inserts depending on cutting parameters, is still limited. In this study, the ST of X20Cr13 martensitic hardened SS under dry finish turning with various cutting speeds and feed rates was investigated. Experiments were conducted using a CNC lathe with CBN and CC inserts. A Sensofar S Neox 3D optical profilometer was employed to characterize the ST features, including height surface roughness (SR) parameters, SR profiles, and 2D and 3D surface images. The Parameter Space Investigation method was used to design the experimental plan. For both CBN and CC inserts, the feed rate was the dominant factor influencing the overall SR, described by the Sa and Sq parameters. The extreme parameters Sp, Sv, and Sz were determined by the relationship between feed rate and cutting speed. With appropriately selected turning parameters, it is possible to obtain low Sa values (0.4-0.6 µm), which can eliminate the need for grinding operations. CBN inserts ensured a more regular shape of the ST, while CC inserts contributed to a wavy surface characteristic, associated with more intense plastic deformation. However, low Sa values may be accompanied by isolated peaks, indicating that this parameter does not always fully reflect the presence of extreme micro-irregularities. On the machined surfaces, adhesive bonds of chips and cutting tool material were observed. In addition, micro-scratches were registered for CBN inserts, and a side flow phenomenon for CC inserts. The results confirm that dry turning of hardened SSs can be effectively performed using both CC and CBN inserts.
The purpose of this study is to investigate the influence of copper content and cutting parameters on the microstructure, hardness, machinability, and cutting-force behavior of sand-cast Al–Cu alloys under minimum quantity lubrication (MQL) conditions. In this study, workpieces obtained using the sand mold casting method were tested using the minimum quantity lubrication (MQL) method on a lathe. Five different test specimens were produced by adding copper to aluminum. The microstructures were examined via optical microscope, and hardness values were determined using Brinell hardness. Due to significant production and energy costs, the MQL method was preferred for metal cutting. Cutting forces generated during the process were measured using a dynamometer and analyzed in terms of feed rate, cutting velocity, and workpiece material using a full factorial analysis. Additionally, wear mechanisms on the cutting tool were determined using scanning electron microscope (SEM) images and Energy Dispersive Spectrum (EDS) analysis. The lowest hardness value was 34 HB in pure aluminum, while the highest was 95 HB in Al-8Cu alloy. Cutting forces increased with feed rate across all samples and decreased with higher cutting velocity. The highest cutting force (216.03 N) and feed force (26.90 N) were found in the Al-8Cu alloy, whereas the lowest cutting force (54 N) and feed force (6.07 N) were in pure aluminum. SEM and EDS analysis revealed flank wear and adhered aluminum on the cutting tools. Regression analysis verified that cutting velocity is the most critical factor influencing cutting and feed forces, with material type and feed rate also playing significant roles. Regression and ANOVA analyses consistently identified cutting velocity as the dominant factor affecting cutting and feed forces, followed by material type and feed rate.
The band saw blade is distinguished by its multi-point and flexible cutting capability when sawing materials. Its wear form is significantly more intricate than that of traditional cutting tools, such as the lathe tool and the milling cutter. Preliminary experimental observations suggest a close correlation between the wear of band saw blades and the motor current of the driving wheel. Therefore, this study evaluates the wear condition of band saw blades using current signals. A mathematical correlation model was established between the driving wheel motor current signals and the load on the band saw. A comprehensive experimental study was conducted on the band saw blade, encompassing the entire lifecycle of sawing operations. The average wear width of the tooth tip was utilized as an indicator of tooth wear, and an investigation was conducted into the correlation between the driving wheel motor current signals and the wear state. The findings indicated that the driving wheel motor current signals could be utilized to assess the blade wear state with high precision, which would facilitate proactive maintenance and replacement strategies to optimize band saw performance and service life.
Surface roughness is a critical parameter in machining, as it affects the corrosion resistance and fatigue properties of the finished workpiece. For difficult-to-machine materials such as Inconel-625, ensuring desired levels of surface roughness is even more challenging. Accurate surface roughness estimation for such expensive alloys can help in reducing material wastage and enhancing machining efficiency. In this paper, machining data collected during the turning of a particularly difficult-to-machine alloy, Inconel-625, is presented. Inconel is widely used in aerospace applications and is difficult to machine, as unlike other materials, Inconel does not get softer with increasing temperature. This dataset comprises twenty-seven sets of vibration data collected using a triaxial accelerometer and corresponding force and moment data collected using a dynamometer, resulting in 382,189,197 samples in total, acquired during the dry turning of Inconel-625 on a Kirloskar Turnmaster 40 Lathe. A Mitutoyo Surface Roughness Tester was used to measure the surface roughness after each turning operation. This publicly available dataset will be of help to the scientific community in developing machine learning/deep learning based on-line surface roughness estimation models for turning processes.
There is a lack of evidence of possible implant fracture after implantoplasty due to decreased implant diameter. To compare narrow diameter titanium dental implants fracture resistance after implantoplasty performed by computer numerical control (CNC) lathe machine which helped to standardize study setting. Twelve (n=12) narrow diameter (3.6×11.0 mm) endosteal screw-shaped bone-level dental implants with an internal connection which are made from grade IV titanium were randomly divided into 2 groups containing six (n=6) implants each. The test group was exposed to implantoplasty using a computer numerical control (CNC) lathe-turning machine. Implantoplasty was performed removing 5.5 mm of implant threads from the implant coronal part downwards towards the apical part, which resulted in a 0.2 mm coronal diameter reduction. Implants from both groups were positioned on metal pipes using three-dimensional (3D) printed guides. The space inside the pipe was filled with epoxy resin. Every sample had an individually 3D-printed chrome-cobalt (Cr-Co) alloy crown, which distributed forces during the test. Implants were compressed in a universal testing machine. Statistical analysis was performed using IBM SPSS 29.0 software. Performing implantoplasty with CNC lathe-turning machine was a success, which helped to standardize study settings. The control group showed average resistance to a maximum compressive force of 443.76 N, while the test group showed average resistance to a maximum compressive force of 409.42 N. No statistical significance was found between groups on the compressive force aspect. This in vitro study shows that implantoplasty does not have a significant effect on decreasing fracture resistance of narrow diameter titanium dental implants.
Laser ultrasound (LU) is a technique that uses a pump laser and a probe laser to optically generate and detect elastic waves in a material. Despite its advantages over traditional contact transducer-based ultrasound, industrial adoption has been limited by complex optical setups and the inability of multi-mode fibers to deliver a stable Gaussian profile for the pump laser. Here, we report a fully fiber-coupled thermoelastic LU system that uses an anti-resonant hollow-core single-mode fiber to deliver 1mJ nanosecond pulses of 1064nm light, while preserving the fundamental Gaussian mode (pump laser). When combined with a fiber-coupled interferometer (probe laser), a small, flexible, and environmentally robust sensor capable of optically generating and detecting high frequency broadband ultrasound is realized. We demonstrate such an LU system implemented in situ on a four-axis precision lathe. High-resolution thickness gauging is performed, before and after precision cutting, by exciting and measuring a zero-group velocity guided wave mode. The measurements are verified with ex-situ traceable coordinate measuring machine data. Mean absolute deviations of 0.1%, of nominal thickness, before cutting, and 0.2% and 0.3%, after stepped and tapered cuts, respectively, are reported. A theoretical background for thermoelastic ultrasound generation in an elastic waveguide is also presented. Attention is given to the effect of the pump laser profile on wave generation to elucidate the importance of using single-mode laser light. The fiber-coupled system demonstrated is well-suited for use in scientific and engineering sensing applications and facilitates the adoption of LU for industrial non-destructive testing.
The aim of this paper is to present an approach to condition monitoring of an actuated mechanical system operating in a steady-state regime. The state signals generated by the sensors placed on the mechanical system (a lathe headstock gearbox) operating in a steady-state regime contain a sum of periodic components, sometimes mixed with a small amount of noise. It is assumed that the state of a rotating part placed inside a mechanical system can be characterized by the shape of a periodic component within the state signal. This paper proposes a method to find the time domain description for the significant periodic components within these state signals, as patterns, based on the arithmetic averaging of signal samples selected at constant time regular intervals. This averaging has the same effect as a numerical filter with multiple narrow pass bands. The availability of this method for condition monitoring has been fully demonstrated experimentally. It has been applied to three different state signals: the active electrical power absorbed by an asynchronous AC electric motor driving a lathe headstock gearbox, the vibration of this gearbox, and the instantaneous angular speed of the output spindle. The paper presents some relevant patterns describing the behavior of different rotating parts within this gearbox, extracted from these state signals.
Immune checkpoint inhibitors (ICI) have shown limited efficacy in unselected patients with metastatic castration-resistant prostate cancer (mCRPC). However, ICIs are approved for biomarker-defined subsets: microsatellite instability-high (MSI-H) and/or high tumor mutational burden (TMB-H). The efficacy of ICIs in TMB-H but not MSI-H disease remains unclear, and limited data exist evaluating ICI outcomes associated with blood-based MSI (bMSI) in mCRPC. This study used the United States-based deidentified Flatiron Health-Foundation Medicine prostate cancer Clinico-Genomic Database. Patients with tissue-assessed MSI (tMSI) and TMB (tTMB) status by an algorithm supporting an FDA-approved CDx for pembrolizumab were included if treated with single-agent ICI. Separately, outcomes on ICI associated with bMSI were assessed, including if treated with single-agent ICI or taxane. Among 2,965 patients with mCRPC, tMSI-H (3.2%) was nearly always also tTMB ≥10 mut/Mb (4.7%). In 84 ICI-treated patients, time to next treatment (TTNT) and overall survival (OS) were more favorable in tMSI-H with any TMB [TTNT HR, 0.18; 95% confidence interval (CI), 0.09-0.37 and OS HR, 0.32; 95% CI, 0.15-0.66] and tTMB ≥10 without tMSI-H (TTNT HR, 0.18; 95% CI, 0.04-0.48 and OS HR, 0.20; 95% CI, 0.05-0.77) compared with tTMB <10 without tMSI-H group. In intrapatient assessments, patients with tTMB ≥10 had more favorable TTNT with subsequent ICI versus prior taxane. Detection of bMSI-H was associated with more favorable TTNT on ICI (HR, 0.34; 95% CI, 0.14-0.83) and OS (HR, 0.21; 95% CI, 0.06-0.75) when tumor fraction ≥1%. These findings add support for tTMB and tMSI in predicting ICI monotherapy benefit in mCRPC and provide evidence supporting bMSI testing when tissue is unavailable.
The growing demand for lightweight, high-strength materials in the aerospace and automotive industries has brought aluminium alloys such as AA2024-T351 into the spotlight due to their outstanding strength-to-weight ratio. However, achieving reliable joints in such alloys remains a significant challenge, particularly when using conventional welding techniques. To address this, the present study focuses on optimizing process parameters in Direct Drive Friction Welding (DDFW) for AA2024-T351. A novel drilled-to-bossed geometry, inspired by the traditional mortise-and-tenon joint, is introduced to enhance mechanical interlocking and improve weld integrity. Experimental trials were systematically designed using an L18 orthogonal array to evaluate both tensile and torsional strength. The experiments were conducted on a customized engine lathe, with friction pressure, forging pressure, spindle speed, faying surface geometry, and friction time selected as the controllable process parameters. In parallel, advanced deep learning models, including an ensemble residual network, a compact attention network, and an adaptive multiscale network, were implemented to predict ultimate tensile strength based on the welding conditions. The results revealed that the optimal parameter combination of 30 MPa friction pressure, 70 MPa forging pressure, 2200 rpm spindle speed, drilled-to-bossed geometry, and 4 min of friction time yielded exceptional mechanical performance, achieving a tensile strength of 538 MPa and torsional strength of 325 MPa. The drilled-to-bossed configuration demonstrated significantly higher joint strength compared to conventional flat-to-flat joints. Moreover, among the deep learning models, the ensemble residual network achieved the highest predictive accuracy with an R² value of approximately 0.81, effectively capturing the complex relationship between process parameters and weld strength.
In the slow tool servo (STS) turning technology for optical lenses, the D-shaped toolpath can improve the quality of the optical surfaces of off-axis aspheric and cylindrical microlens arrays. However, the traditional D-shaped toolpath has the problem of excessive servo following error in the X-axis. To address this issue, the projection of the D-shaped toolpath in the XZ plane is divided into a cutting zone and a transition zone. In the transition zone, an equation system based on continuity constraints (surface height, feed-rate, acceleration) is established. By solving this system of equations, a toolpath can be obtained along which the feed-rate of the X-axis varies smoothly. An example shows that the acceleration of the X-axis of the lathe is reduced by 84% compared to the traditional D-shaped toolpath. In the XZC interpolation mode, the spindle velocity of the C-axis changes smoothly. An off-axis spherical surface and an integral mirror have been machined using the optimized D-shaped toolpath. The X-axis servo following error of the lathe during processing is within 7 nm, and the surface shape accuracy reaches 0.361λ at 632.8 nm. This method enables high-precision processing of off-axis curved surfaces and cylindrical arrays.
Polytetrafluoroethylene (PTFE) is widely used across various industrial and technological fields, including aerospace, automotive, electronics, and chemical processing. This work presents a sustainable approach to reusing PTFE waste and enhancing the limited applications of PTFE, which are constrained by its inferior mechanical properties, thermal expansion, and wear resistance. The reuse of PTFE scrap produced by lathe shops improves its previously mentioned properties by adding high-strength and high-stability ceramics. In this context, powder metallurgy technology produces PTFE-based composites reinforced with boron carbide (B4C) nanoparticles and graphene nanosheets. The phase composition and microstructure were determined using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) techniques. XRD indicated the presence of PTFE and B4C phases in the chart of the specimens and the absence of graphene nanosheets due to their small quantity. The hybrid composite PTFE/5vol.% B4C/1 vol% graphene (GB6) recorded an increase in the microhardness, compressive stress, and Young’s modulus of 138.55%, 114.86%, and 78.70%, respectively, relative to the PTFE matrix (GB0). The results also indicated that the addition of reinforcements led to a significant improvement in wear resistance and thermal stability, with the GB6 sample recording a decrease in wear rate, coefficient of friction, and thermal expansion coefficient (CTE) value of 40.73%, 42.49%, and 57.94%, respectively, compared to the CB0 sample. Moreover, the addition of reinforcements to the PTFE matrix has the positive effect of increasing the electrical conductivity.
During cartridge case comparisons, firearm examiners must distinguish between different markings found on the cartridge cases. These characteristics can be classified into class, subclass, or individual characteristics. There is potential for a false identification if firearm examiners do not assess subclass characteristics carefully and mistake them as individual characteristics. Breech faces were manufactured by three different manufacturing methods (i.e., broach, plunge mill, and lathe) and two different finishing methods (i.e., glass bead blasting and tumbling). The manufacture resulted in subclass characteristics present on these breech faces. Ten test fires were collected from each breech face at each step in the manufacturing process. A confocal microscope was used to collect the 3D topographical scans, and pairwise comparisons were performed using the National Institute of Standards and Technology congruent matching cells (CMC) algorithm. The results revealed that carryover of subclass characteristics from the broached breech faces onto the breech face impressions occurred. The breech faces manufactured by plunge milling and lathe turning transferred minimal subclass characteristics to the cartridge cases. Using the ANOVA and Kruskal-Wallis H tests determined the presence of significant differences between all finishing groups except for the turned breech faces finished by glass bead blasting versus tumbling. In addition to the comparison of the cartridge cases using CMC, they were optically evaluated by comparison microscopy. The position of the CMC cells was indicated on these comparisons. The method of determining subclass characteristics by comparing the opposing edges of the breech face impressions on primers was also used.
This study investigates the machinability of a novel LM25 aluminum alloy reinforced with vanadium carbide composite material (LM25Al/VC) using computer numerical control (CNC) lathe operation. By optimizing CNC lathe process parameters such as depth of cut, feed rate, and cutting speed, the aim is to maximize material removal rate, minimize surface roughness, reduce power consumption, and optimize costs. The study employs analytical modeling, deep neural networks (DNN), and grey relational grade (GRA) coupled with response surface methodology (RSM) for performance evaluation. The effectiveness of these methods was compared using four objective verification mechanisms. In this case, the DNN technique delivered superior results among the methods considered. Additionally, new analytical models and DNN programming were developed in this work to predict machining costs, power consumption, material removal rate, and surface finish quality. These findings contribute to creating energy-efficient, cost-effective machining techniques and promote sustainable practices in the manufacturing industry.
Ophthalmic drugs are administered to the front of the eye by eyedrops. The bioavailability of drugs delivered via eye drops is low due to tear turnover. Contact lenses can address some deficiencies of eye drops by sustaining the delivery of drugs, but commercial contact lenses have small pore sizes that cannot load biologics, which are becoming more common for treating ophthalmic diseases. This study aims to investigate novel poly(hydroxyethyl methacrylate) (pHEMA) lenses with transparent center and porous annulus for sustained release of model proteins. A novel hydrogel polymerization process was used to fabricate concentric, porous layer pHEMA hydrogel rods. The hydrogels were lathe cut into contact lenses which were explored for the delivery of proteins and gold nanoparticles. Lenses were characterized by partition coefficient and diffusivity, which was estimated by fitting experimental data to an analytical model. Transmittance measurements were made to compare transparency of porous lens centers to commercial contact lenses. Porous pHEMA lenses consisting of a concentric, porous layer made from 55% water content in precursor were successfully lathe cut into lenses with transparent center and opaque porous annulus. The porous lenses could load large model proteins of bovine serum albumin and human γ-globulin and provide sustained release. The core annular pHEMA contact lenses consisting of an outer annulus of opaque, porous pHEMA and an inner, center layer of clear, nonporous pHEMA can provide sustained delivery of biologics.
The increasing adoption of digital tools has transformed how learning and teaching are delivered in anatomy. Digital anatomy is maturing from its nascent nature and emerges as a new discipline of great importance. This article discusses topical areas in digital anatomy education pertinent to the development of the anatomical science discipline in the future.