Search Results (1,132)

Background: Intervertebral disc degeneration is a prevalent condition and a major risk factor for disc herniation. Mechanical overload, aging, injury, and disease contribute to the annulus fibrosus’ structural failure, which allows nucleus pulposus material to escape and reduces the capacity to absorb shock. This study builds on previous investigations by evaluating additional thermoplastic polyurethane (TPU) filaments as potential materials for additively manufactured intervertebral disc replacements. Materials and Methods: Disc-shaped specimens (Ø50 × 10 mm) were fabricated using fused deposition modeling (FDM). A gyroid infill structure was employed with unit cell sizes ranging from 4 to 10 mm³ and wall thicknesses between 0.5 and 1.0 mm. The outer wall thickness varied from 0.4 to 0.8 mm. Four TPU filaments (Extrudr FlexSemiSoft, GEEE-TECH TPU, SUNLU TPU, and OVERTURE TPU) were tested, resulting in 36 parameter combinations per filament. Printed discs were examined via stereomicroscopy. Tensile testing was conducted according to DIN EN ISO 527-1 using Type 5A specimens. Mechanical performance under physiological loading was assessed through uniaxial compression tests, in which samples were compressed to 50% of their height while force–deformation curves were recorded. Target forces were defined as 4000–7500 N to maintain comparability with prior studies. Results: Across all filaments, a maximum of three parameter combinations per material achieved forces within the target range. Microscopy confirmed the dimensional accuracy of wall thicknesses with minimal deviation. Tensile strength values for GEEE-TECH, SUNLU, and FlexSemiSoft were comparable (10–11 MPa), while OVERTURE showed significantly lower strength (approximately 9 MPa). Tensile modulus values followed a similar trend: 25–30 MPa for three filaments and 17.5 MPa for OVERTURE. Conclusions: All four TPU filaments could be used to fabricate discs that met the mechanical requirements for compression. These results confirm that both the tested TPU materials and gyroid structures are suitable for potential intervertebral disc replacement applications. Full article

In high-precision optical systems such as laser optics, astronomical observation, and semiconductor lithography, anti-reflection coatings are crucial for light transmittance, imaging quality, and stability, but traditional designs face modeling challenges in balancing ultralow reflectivity, high wavefront quality, and manufacturability amid multi-dimensional parameter coupling and multi-objective constraints. This study addresses these by proposing a unified mathematical modeling framework integrating a Symmetric five-layer high-low refractive index alternating structure (V-H-V-H-V) with dual-scale nanostructures, employing a constrained quasi-Newton optimization algorithm (L-BFGS-B) to minimize reflectivity, wavefront root-mean-square (RMS) error, and surface roughness root-mean-square (RMS) in a six-dimensional parameter space. The Sellmeier equation is adopted to calculate wavelength-dependent material refractive indices, the model uses the transfer matrix method for the Symmetric five-layer high-low refractive index alternating structure’s reflectivity, incorporates nano-surface height function gradient correction, sub-wavelength modulation, and radial optimization, applies Zernike polynomials for low-order aberration correction, quantifies surface roughness via curvature proxies, and optimizes via a weighted objective function prioritizing low reflectivity. Numerical results show the spatial average reflectivity at 632.8 nm reduced to 0.13%, the weighted average reflectivity across five representative wavelengths in the 550–720 nm range to 0.037%, the reflectivity uniformity to 10.7%, the post-correction wavefront RMS to 11.6 milliwavelengths, and the surface height standard deviation to 7.7 nm. This framework enhances design accuracy and efficiency, suits UV nanoimprinting and electron beam evaporation, and offers significant value for high-power lasers, lithography, and space-borne radars. Full article

In autonomous manufacturing systems, the performance of time-series-based anomaly detection and fault diagnosis is highly sensitive to window size selection. Conventional approaches rely on empirical rules or fixed window settings, which often fail to capture the diverse temporal characteristics of anomalies and lead to performance degradation. This study systematically addresses the window size selection problem by categorizing anomaly patterns into three representative types: variability, cycle, and local spike. Each pattern is associated with a distinct temporal scale and underlying physical mechanism. Based on this insight, an Anomaly Deviation-Based Window Size Selection (ADW) method is proposed, which quantitatively evaluates anomaly deviation as a function of window size. Unlike traditional preprocessing-oriented approaches, the proposed method redefines window size as a core design variable that directly governs anomaly representation and diagnostic sensitivity. The effectiveness of the ADW method is validated using tension data from a roll-to-roll continuous manufacturing process and vibration data from a rotating bearing fault dataset. Experimental results demonstrate that the proposed approach consistently identifies optimized window sizes tailored to different anomaly types, leading to improved fault classification accuracy and diagnostic robustness. The proposed framework provides a physically interpretable and data-driven guideline for adaptive window size selection in long-term autonomous manufacturing systems. Full article

This paper presents the design, manufacturing, instrumentation and validation by tests (ground and icing wind tunnel) of a full-scale Hybrid Laminar Flow Control (HLFC) leading-edge demonstrator based on Airbus A330 outer wing plan-form. The Ground-Based Demonstrator (GBD) was developed to reproduce a full-scale, realistic wing section integrating into the leading-edge three key systems: micro-perforated skin for the hybrid laminar flow control suction system (HLFC), the hot-air Wing Ice Protection System (WIPS) and a folding “bull nose” Krueger high-lift device. The demonstrator combines a superplastic-formed and diffusion-bonded (SPF/DB) perforated titanium skin mounted on aluminum ribs jointed with a carbon-fiber-reinforced polymer (CFRP) wing box. Titanium internal ducts were designed to ensure uniform hot-air distribution and structural compatibility with composite components. Manufacturing employed advanced aeronautical processes and precision assembly under INCAS coordination. Ground tests were performed using a dedicated hot-air and vacuum rig delivering up to 200 °C and 1.6 bar, thermocouples and pressure sensors. The results confirmed uniform heating (±2 °C deviation) and stable operation of the WIPS without structural distortion. Relevant tests were performed in the CIRA Icing Wind Tunnel facility, verifying the anti-ice protection system and Krueger device. The successful design, fabrication, testing and validation of this multifunctional leading edge—featuring integrated HLFC, WIPS and Krueger systems—demonstrates the readiness of the concept for subsequent aerodynamic testing. Full article

A combined numerical simulation and experimental validation approach was employed to investigate the phenomena of screw adhesion and nozzle clogging, which occur frequently during material conveying and extrusion of high-viscosity, high-solid-content multi-component energetic materials in additive manufacturing. First, conical and cylindrical screws were designed. Through simulation calculations of the energetic material extrusion process, patterns in the variation in internal pressure and shear rate within the screw were analyzed, providing guidance for the design of the printing equipment. Second, a Z-shaped stirring paddle kneading device and a dual-nozzle printing device featuring horizontally and vertically arranged two-stage screws were designed. Through extrusion experiments with PBX (polymer-bonded explosive) slurry, the optimal matching relationship between the kneading rate and the extrusion rates of the horizontal and vertical screws was obtained. Finally, additive manufacturing of complex-shaped PBX charges using high-viscosity energetic materials was successfully accomplished. This confirms the further optimization of the additive manufacturing equipment in terms of safety control, precision control, and adaptability to complex structures under extreme operating conditions. The results indicate that the cylindrical screw outperforms the conical screw, and with a screw clearance of 3mm, it represents the optimal design solution. During the kneading process, a screw rotational speed of 25 rpm was used. After kneading for 3 h, the slurry exhibited good uniformity, with a solid content of approximately 70% and relatively small deviation. During the extrusion process, a nozzle diameter of 1.55 mm combined with a rotational speed of 5 rpm for the horizontal screw (feeding screw) and 7 rpm for the vertical screw (extrusion screw) can satisfy the requirements of the “starved feeding” mode, thus achieving continuous and stable filament formation of the slurry. Full article

In the context of manufacturing logistics, this study sheds light on the difficult task of concurrently optimizing cost, time, influence on sustainability, and spatial efficiency. Specifically, this addresses the integrated challenge of material handling equipment selection and facility space allocation, a crucial decision-making domain where conventional single-objective methodologies frequently overlook vital considerations. While recent research predominantly relies on meta-heuristics and simulation-based solution methodologies, they do not guarantee a global optimum solution space. To effectively address this multifaceted decision environment, a Mixed-Integer Linear Programming (MILP) model is developed and resolved utilizing two distinct scalarization methodologies: the conventional ϵ-constraint method and the augmented ϵ-constraint method (AUGMECON2). The comparative analysis indicates that although both methods effectively identify the Pareto front, the AUGMECON2 approach offers a more robust assurance of solution efficiency by incorporating slack variables. The results illustrate a convex trade-off between capital expenditure and operational flow time, indicating that substantial reductions in time necessitate strategic investments in higher-capacity equipment fleets. Furthermore, the analysis underscores a significant conflict between achieving extreme operational efficiency and adhering to facility design standards, as reducing time or energy consumption beyond a specific point requires deviations from optimal space allocation policies. Ultimately, a “Best Compromise Solution” is determined that harmonizes near-optimal operational efficiency with strict compliance to spatial constraints, providing a resilient framework for sustainable manufacturing logistical planning. Full article

The shift toward Industry 5.0 places human-centred and digitally integrated metrology at the core of modern manufacturing, particularly in the automotive sector, where portable Laser Line Triangulation (LLT) systems must combine accuracy with operator usability. This study addresses the challenge of operator-induced variability by evaluating how algorithmic strategies and mechanical support features jointly influence the performance of a portable LLT device derived from the G3F sensor. A comprehensive Measurement System Analysis was performed to compare three feature extraction algorithms—GC, FIR, and Steger—and to assess the effect of a masking device designed to improve mechanical alignment during manual measurements. The results highlight distinct algorithm-dependent behaviours in terms of repeatability, reproducibility, and computational efficiency. More sophisticated algorithms demonstrate improved sensitivity and feature localisation under controlled conditions, whereas simpler gradient-based strategies provide more stable performance and shorter processing times when measurement conditions deviate from the ideal. These differences indicate a trade-off between algorithmic complexity and operational robustness that is particularly relevant for portable, operator-assisted metrology. The presence of mechanical alignment aids was found to contribute to improved measurement consistency across all algorithms. Overall, the findings highlight the need for an integrated co-design of algorithms, calibration procedures, and ergonomic aids to enhance repeatability and support operator-friendly LLT systems aligned with Industry 5.0 principles. Full article

Rolling steel rings is a key manufacturing process for producing components with high strength and dimensional accuracy, used, among others, in the automotive, aerospace, and energy industries. The quality of the products depends on the process parameters that affect their mechanical and geometric properties. One significant quality issue is ovalization, i.e., deviation from the ideal circular shape, which can complicate further processing or assembly. Therefore, analyzing the influence of rolling parameters on ovalization is crucial for ensuring high product quality and minimizing material losses. The aim of the research presented in this article was to determine the influence of the most important parameters of the ring rolling process—namely, billet temperature, forming tool speed, and the position of the calibrating rollers—on the ovalization of the rings produced. The results indicate that, among the parameters studied, the position of the calibrating roller engaged by the rolled ring has the greatest impact on ovality. Ovalization of the forging decreases with an increase in feed speed and a decrease in billet temperature. Higher feed speeds provide a more stable rolling process, which promotes the achievement of a more circular ring geometry. Lower billet temperatures are associated with better material strength properties, making it less susceptible to deformation under inertial forces compared to higher initial billet temperatures. The study of the influence of calibrating roller positions on ovalization showed that it is possible to determine an optimal configuration in which deviation from the ideal circular shape is minimized. Determining the optimal process parameters allows for producing components without the need for large-dimensional tolerances. Based on the results obtained, conclusions were formulated regarding the influence of the investigated process parameters on the ovalization of the finished ring. Full article

This study investigates the technological and chemical causes of early zinc-coating degradation on cold-formed steel sections produced from DX51D+Z140 galvanized coils. Commercially manufactured products exhibiting early corrosion symptoms were used in this study. The entire processing route, which included strip preparation, cold rolling, hot-dip galvanizing, passivation, multi-roll forming, storage, and transportation to customers, was analyzed with respect to the residual surface chemistry and process-related deviations that affect the coating integrity. Thirty-three specimens were examined using electromagnetic measurements of coating thickness. Statistical analysis based on the Cochran’s and Fisher’s criteria confirmed that the increased variability in zinc coating thickness is associated with a higher susceptibility to localized corrosion. Surface and chemical analysis revealed chloride contamination on the outer surface, absence of detectable Cr(VI) residues indicative of insufficient passivation, iron oxide inclusions beneath the zinc coating originating from the strip preparation, traces of organic emulsion residues impairing wetting and adhesion, and micro-defects related to deformation during roll forming. Early zinc coating degradation was shown to result from the cumulative action of multiple technological (surface damage during rolling, variation in the coating thickness) and environmental (moisture during storage and transportation) parameters. On the basis of the obtained results, a methodology was proposed to prevent steel product corrosion in industrial conditions. Full article

Reverse engineering (RE) has been increasingly adopted in metal manufacturing to digitize legacy parts, connect “as-is” geometry to mechanical performance, and enable agile repair and remanufacturing. This review consolidates scan-to-simulation workflows that transform 3D measurement data (optical/laser scanning and X-ray computed tomography) into simulation-ready models for structural assessment and manufacturing decisions, with an explicit focus on sustainability. Key steps are reviewed, from acquisition planning and metrological error sources to point-cloud/mesh processing, CAD/feature reconstruction, and geometry preparation for finite-element analysis (watertightness, defeaturing, meshing strategies, and boundary condition transfer). Special attention is given to uncertainty quantification and the propagation of geometric deviations into stress, stiffness, and fatigue predictions, enabling robust accept/reject and repair/replace choices. Sustainability is addressed through a lightweight reporting framework covering material losses, energy use, rework, and lead time across the scan–model–simulate–manufacture chain, clarifying when digitalization reduces scrap and over-processing. Industrial use cases are discussed for high-value metal components (e.g., molds, turbine blades, and marine/energy parts) where scan-informed simulation supports faster and more reliable decision making. Open challenges are summarized, including benchmark datasets, standardized reporting, automation of feature recognition, and integration with repair process simulation (DED/WAAM) and life-cycle metrics. A checklist is proposed to improve reproducibility and comparability across RE studies. Full article

Industrial aluminum-block heating processes exhibit nonlinear dynamics, substantial time delays, and stringent requirements for fault detection and diagnosis, especially in semiconductor manufacturing and other high-precision electronic processes, where slight temperature deviations can accelerate device degradation or even cause catastrophic failures. To address these challenges, this study presents a digital twin-based intelligent heating platform for aluminum blocks with a dual-artificial-intelligence framework (dual-AI) for control and diagnosis, which is applicable to multi-port aluminum-block heating systems. The system enables real-time observation and simulation of high-temperature operational conditions via virtual-real interaction. The platform precisely regulates a nonlinear temperature control system with a prolonged time delay by integrating a conventional proportional–integral–derivative (PID) controller with a Levenberg–Marquardt-optimized backpropagation (LM-optimized BP) neural network. Simultaneously, a relay is employed to sever the connection to the heater, thereby simulating an open-circuit fault. Throughout this procedure, sensor data are gathered simultaneously, facilitating the creation of a spatiotemporal time-series dataset under both normal and fault conditions. A one-dimensional convolutional neural network (1D-CNN) is trained to attain high-accuracy fault detection and localization. PID+LM-BP achieves a response time of about 200 s in simulation. In the 100 °C to 105 °C step experiment, it reaches a settling time of 6 min with a 3 °C overshoot. Fault detection uses a 0.38 °C threshold defined based on the absolute minute-to-minute change of the 1-min mean temperature. Full article

Thin-walled parts are widely used in the automotive manufacturing industry due to their lightweight characteristics and high structural efficiency. However, it is difficult to accurately measure machining errors in key regions due to the feature deformation. To improve the online measurement accuracy of complex thin-walled parts, a machining error measurement approach based on multi-constraint point cloud registration is proposed. To address the low overlap and complex geometric features among multi-segment measured point clouds, a point cloud stitching method based on hole boundary features is developed to acquire complete measured point clouds. Meanwhile, a point cloud surface extraction method based on normal neighborhood searching is developed to acquire model point clouds. Since different regions of thin-walled parts require different geometric tolerances, a registration model integrating multiple locating and assembly constraints is proposed to satisfy the requirements for optimal point cloud registration. A measurement system composed of a line-structured light sensor and a six-axis robotic arm is developed to validate the proposed method. Experimental results show that the proposed approach reduces the overall dimensional error of point cloud stitching by approximately 70–86% and decreases the point number deviation between upper and lower surfaces by more than 98%. Furthermore, the measurement accuracy in locating holes and key assembly regions is improved to 0.05 mm and 2 mm, representing improvements of approximately 96.3% and 23.9% compared with registration methods without multi-constraint conditions, and approximately 95.3% and 14.5% compared with commonly used multi-constraint registration methods. Full article

Temperature homogeneity assumes a crucial role in the manufacture of asphalt mixtures due to its impact on mechanical formation and mixing homogeneity. The existence of reclaimed asphalt pavement (RAP) exacerbates its impact on temperature inhomogeneity. To address this, the RAP contents of 20%, 40%, and 60%, combined with RAP preheated temperatures of 353 K, 373 K, and 393 K, were taken into consideration to examine the thermal transition and evolution of temperature for the recycled asphalt mixtures in the mixing. Thermal images captured within the range of 30 s to 120 s were used to monitor the temperature evolution of the recycled asphalt mixtures during the mixing. To quantitatively assess the level of thermal non-uniformity, a Relative Thermal Equilibrium Temperature Index (RETI) was introduced. This index reflects the degree of deviation from ideal thermal equilibrium within the recycled mixtures. Based on the RETI calculation, complete temperature homogeneity cannot be attained until the end of the mixing of hot recycled asphalt mixtures. However, a prolongation of the mixing time or an elevation in the RAP preheated temperature can expedite the thermal equilibrium process of recycled asphalt mixtures. Additionally, the RAP contents also exerted a crucial influence on the thermal equilibrium process of the recycled asphalt mixtures. Full article

Using additive manufacturing for the design of inserts in injection moulding (IM) offers advantages in product development and customization. However, challenges related to operating temperature and mechanical resistance remain. This article presents a systematic screening methodology to evaluate the suitability of materials for specific applications. Ten commercial Material Extrusion (MEX) filaments were selected to produce test samples. Moldex3D simulation software was employed to model the IM process using two thermoplastics and to determine the temperature and pressure conditions that the printed inserts must withstand. Simulation results were critically interpreted and cross-referenced with the experimental material characterisations to evaluate material suitability. Nine of the ten MEX materials were suitable for IM with LDPE, and five with PP. Dimensional assessments revealed that six insert solutions required further post-processing for assembly, while three did not. All of the selected materials successfully survived 10 injection cycles without encountering any significant issues. The simulation results were validated by comparing temperature data from a thermal imaging camera during IM, revealing only minor deviations. The study concludes that combining targeted material characterization with CAE simulation provides an effective and low-cost strategy for selecting MEX filaments for injection moulding inserts, supporting rapid tooling applications in niche production. Full article

Maintaining color constancy in polymer extrusion processes is a key difficulty in manufacturing applications, as fluctuations in processing parameters greatly influence pigment dispersion and the quality of the finished product. Preliminary historical data mining analysis was conducted in 2009. This work concentrates on Opaque PC Grade 5, which constituted 2.43% of the pigment; it contained 10 PPH of resin2 with a Melt Flow Index (MFI) of 6.5 g/10 min and 90 PPH of resin1. It also employs a fixed resin composition with an MFI of 25 g/10 min. This research identified the significant processing parameters (PPs) contributing to the lowest color deviation. Interactions between processing parameters, for the same color formulation, were analyzed using statistical methods under various processing conditions. A principle-driven General Trends (GT) diagnostic procedure was applied, wherein each parameter was individually varied across five levels while holding others constant. Particle size distribution (PSD) and colorimetric data (CIE Lab*) were systematically measured and analyzed. To complete this, correlations for the impact of temperature (Temp) on viscosity, particle characteristics, and color quality were studied by characterizing viscosity, Digital Optical Microscopy (DOM), and particle size distribution at various speeds. The samples were characterized for viscosity at three temperatures (230, 255, 280 °C) and particle size distribution at three speeds: 700, 750, 800 rpm. This study investigates particle processing features, such as screw speed and pigment size distribution. The average pigment diameter and the fraction of small particles were influenced by the speed of 700–775 rpm. At 700 rpm, the mean particle size was 2.4 µm, with 61.3% constituting particle numbers. The mean particle size diminished to 2 µm at 775 rpm; however, the particle count proportion escalated to 66% at 800 rpm. This research ultimately quantifies the relative influence of particle size on the reaction, resulting in a color value of 1.36. The mean particle size and particle counts are positively correlated; thus, reduced pigment size at increased speed influences color response and quality. The weighted contributions of the particles, 51.4% at 700 rpm and 48.6% at 800 rpm, substantiate the hypothesis. Further studies will broaden the GT analysis to encompass multi-parameter interactions through design experiments and will test the diagnostic assessment procedure across various polymer grades and colorants to create robust models of prediction for industrial growth. The global quality of mixing polycarbonate compounding constituents ensured consistent and smooth pigment dispersion, minimizing color streaks and resulting in a significant improvement in color matching for opaque grades. Full article