Search Results (148)

Background. Physicomechanical properties and clinical service of bulk-fill composites depend on their adequate polymerization and depth of cure. Some manufacturers claim that these composites can be adequately cured when used in bulks exceeding 4 mm. Objective. The aim of this study was to compare Vickers microhardness (VMH) and depth of cure (DOC) of six contemporary bulk-fill resin composites at depths of 4 mm and 6 mm. Material and methods. Six bulk-fill composites were evaluated in this study: 1. Tetric EvoCeram Bulk (Ivoclar Vivadent, Schaan, Liechtenstein), (TEC); 2. Filtek Bulk Fill Posterior (3M ESPE Dental Products Division, St. Paul, MN, USA), (FBF); 3. Filtek One Bulk Fill (3M ESPE Dental Products Division, St. Paul, MN, USA, (FOB); 4. SonicFill 2 (Kerr, Orange, CA, USA), (SF2); 5. Admira Fusion X-tra (Voco, GmbH, Cuxhaven, Germany), (AFX); 6. GrandioSO X-tra (Voco, GmbH, Cuxhaven, Germany), (GSX). The 18 specimens (3 of each composite) were prepared in split Teflon moulds of 4 mm diameter and 6 mm thickness. All composites were cured in standard mode for 20 s using LED LCU (D-Light Duo, RF-Pharmaceuticals Sarl, Geneva, Switzerland; 1200–1300 mW/cm). The VMH was measured using a digital Micro Hardness Tester Shimadzu (HMV-2T E, Shimadzu Corporation, Kyoto, Japan). A 50 g (0.5 N) load force was applied for 30 s. Each specimen was measured at five places selected by chance at each level (N = 15). The hardness ratio or DOC was calculated for all samples as the ratio of bottom and surface microhardness at levels of 4 and 6 mm. Data were analysed using one-way ANOVA and Tukey’s post hoc test. Results. Significant reduction in VMH was observed for all tested materials when comparing top surface and bottom (p < 0.01). The highest VMH was obtained for GSX and AFX, and the lowest for TEC. The results show that the degree of polymerization was adequate for all tested materials at a depth of 6 mm, since the hardness ratio exceeded 0.80 in all cases. The hardness ratio at 4 mm was high for all tested composites ranging from 0.91 for TEC to 0.98 for GSX. All composites showed adequate DOC at the bottom of the 6 mm bulk samples. However, the hardness ratio was the highest for Admira Fusion X-tra (0.96) and GrandioSO X-tra (0.97). Conclusions. All tested materials showed a significant decrease in microhardness from the top surface to the bottom. The DOC was adequate for all bulk-fill composites at a depth of 6 mm cured under standard mode for 20 s. All bulk-fill resin composites evaluated in this study can be used in bulk, up to 6 mm. Full article

Material Extrusion (MEX) process is increasingly used to fabricate components for structural applications, driven by the availability of advanced materials and greater industrial adoption. In these contexts, understanding the mechanical performance of printed parts is crucial. However, conventional methods for assessing anisotropic elastic behavior often rely on expensive equipment and time-consuming procedures. The aim of this study is to evaluate the applicability of the impulse excitation of vibration (IEV) in characterizing the dynamic mechanical properties of a 3D-printed composite material. Tensile tests were also performed to compare quasi-static properties with the dynamic ones obtained through IEV. The tested material, Nylon 12CF, contains 35% short carbon fibers by weight and is commercially available from Stratasys. It is used in the fused deposition modeling (FDM) process, a Material Extrusion technology, and exhibits anisotropic mechanical properties. This is further reinforced by the filament deposition process, which affects the mechanical response of printed parts. Young’s modulus obtained in the direction perpendicular to the deposition plane (E₃₃), obtained via IEV, was 14.77% higher than the value in the technical datasheet. Comparing methods, the Young’s modulus obtained in the deposition plane, in an inclined direction of 45 degrees in relation to the deposition direction (E₄₅), showed a 22.95% difference between IEV and tensile tests, while Poisson’s ratio in the deposition plane (v₁₂) differed by 6.78%. This data is critical for designing parts subject to demanding service conditions, and the results obtained (orthotropic elastic properties) can be used in finite element simulation software. Ultimately, this work reinforces the potential of the IEV method as an accessible and consistent alternative for characterizing the anisotropic properties of components produced through additive manufacturing (AM). Full article

In response to the low efficiency of collaborative processing of sewing machine cases at the part level in network collaborative manufacturing, this paper proposes a sewing machine cases manufacturing service composition optimization method based on an improved multi-objective artificial hummingbird algorithm. The structure and production process of sewing machine cases are analyzed; a framework for service composition optimization in the sewing machine cases manufacturing service platform is established; the required manufacturing resource service composition is determined; and a dual-objective service composition optimization mathematical model that considers Quality of Service (QoS) indicators and flexibility indicators is constructed. Opposition-based learning strategies, roulette wheel selection strategies, and improved differential evolution strategies are embedded in the multi-objective artificial hummingbird algorithm, and the improved artificial hummingbird algorithm (ORAHA_DE) is used to solve the sewing machine cases manufacturing service composition optimization model. The experimental results show the effectiveness and superiority of this composition optimization method in solving the sewing machine cases manufacturing composition optimization problem while avoiding entrapment in a local optimum during the solution process, thereby achieving the composition optimization of sewing machine cases collaborative manufacturing services. Full article

Composite laminates are widely used in aerospace, automotive, construction, and luxury industries, owing to their superior mechanical properties and design flexibility. However, detecting manufacturing defects and in-service damage remains a vital challenge for structural safety. While traditional unsupervised machine learning methods have been used in structural health monitoring (SHM), their high false positive rates limit their reliability in real-world applications. This issue is mostly inherited from their limited ability to capture small temporal variations in Lamb wave signals and their dependence on shallow architectures that suffer with complex signal distributions, causing the misclassification of damaged signals as healthy data. To address this, we suggested an unsupervised anomaly detection framework that integrates a self-attention autoencoder with a Gaussian mixture model (SAE-GMM). The model is solely trained on healthy Lamb wave signals, including high-quality synthetic data generated via a generative adversarial network (GAN). Damages are detected through reconstruction errors and probabilistic clustering in the latent space. The self-attention mechanism enhances feature representation by capturing subtle temporal dependencies, while the GMM enables a solid separation among signals. Experimental results demonstrated that the proposed model (SAE-GMM) achieves high detection accuracy, a low false positive rate, and strong generalization under varying noise conditions, outperforming traditional and deep learning baselines. Full article

To address the growing demand for industrial software in the digital transformation of small and medium-sized enterprises (SMEs) in the manufacturing sector, and to ensure the stable integration and operation of multi-source heterogeneous industrial software under complex conditions—such as heterogeneous compatibility, component dependencies, and uncertainty disturbances—this study established a comprehensive evaluation index system for service composition and optimal selection (SCOS). The system incorporated key criteria including service time, service cost, service reputation, service delivery quality, and availability. Based on this, a bi-objective SCOS model was established with the goal of maximizing both quality of service (QoS) and availability. To efficiently solve the proposed model, a hybrid enhanced multi-objective Gray Wolf Optimizer (HEMOGWO) was developed. This algorithm integrated Tent chaotic mapping and a Levy flight-enhanced differential evolution (DE) strategy. Extensive experiments were conducted, including performance evaluation on 17 benchmark functions and case studies involving nine industrial software integration scenarios of varying scales. Comparative results against state-of-the-art, multi-objective, optimization algorithms—such as MOGWO, MOEA/D_DE, MOPSO, and NSGA-III—demonstrate the effectiveness and feasibility of the proposed approach. Full article

This article focuses on the possibility of using biodegradable polymer-composite materials in additive manufacturing via fused deposition modelling (FDM) 3D printing. The main objective was to experimentally verify the technical feasibility of the repeated use of recycled PLA and PLA composites containing 10% natural coffee-ground (CG) filler in a print–degradation–recycling–print cycle. Special attention was paid to simulated ultraviolet radiation as a degradation factor affecting the materials’ mechanical properties. Pure PLA and PLA_CG were compared at four levels of degradation time and after subsequent recycling. The results show that the inclusion of coffee-ground filler slightly reduces the initial strength but enhances the 3D-printed material’s resistance to UV degradation and thus extends its functional service life. Unlike pure PLA, which loses its processability after 12 weeks, PLA_CG retains structural integrity and mechanical functionality. The research confirms the potential of recycled PLA composites with natural fillers for sustainable manufacturing and supports their use within a circular economy framework. Full article

Ni–P–WC–BN(h) nanocomposite coatings were fabricated on 20CrMnTi substrates using ultrasonic-assisted pulsed electrodeposition. 20CrMnTi is a low-carbon steel that is commonly used in the manufacturing gears and shaft components. To enhance the wear resistance and extend the service life of such mechanical parts, ultrasonic-assisted pulsed electrodeposition was employed as an effective surface modification technique. The microhardness, phase structure, surface morphology, and wear behavior of the coating were also characterized. An orthogonal experimental design was employed to examine the effects of current density, bath temperature, ultrasonic power, and pulse duty cycle on the microhardness and wear behavior of the coatings, aiming to optimize the deposition parameters. The optimal process combination was identified as a current density of 3 A·dm⁻², a bath temperature of 55 °C, an ultrasonic power of 210 W, and a duty cycle of 0.7. Under these conditions, the coatings exhibited enhanced hardness and wear resistance. Based on the optimized parameters, additional tribological tests were conducted under various operating conditions to further evaluate wear performance. The results showed that the dominant wear mechanisms were chemical wear and adhesive wear. This study offers new insights into the fabrication of high-performance nanocomposite coatings and expands the application scope of ultrasonic-assisted pulsed electrodeposition in multiphase composite systems. Full article

The escalating demands of industrial applications, particularly those involving severe wear, temperature, and corrosive environments, present significant challenges for the long-term strength of critical components, often fabricated from high-value materials such as super duplex stainless steel alloys. Super duplex can withstand the corrosive environment (in particular, crevice corrosion and pitting damage) and maintain mechanical integrity sufficient for high-pressure pumping applications such as seawater injection and crude oil. Conventional repair methodologies frequently result in component rejection due to process-induced distortions or detrimental phase transformations, contributing to substantial material waste and hindering the adoption of circular economy principles. This research addresses this issue by developing and validating a novel repair process utilizing laser metal deposition (LMD) additive manufacturing. The research focuses on establishing optimized process parameters to ensure the salvaging and restoration of damaged super duplex components while preserving their requisite mechanical integrity and corrosion resistance, in accordance with industry standards. Comprehensive characterization, including microstructural analysis, chemical composition verification, hardness profiling, and mechanical fatigue testing, confirms the efficacy of the LMD repair process. This work demonstrates the potential for extending the service life of critical components, thereby promoting resource efficiency and contributing to a more sustainable and resilient industrial paradigm. Full article

Aiming at the problem of the low collaborative efficiency of outsourced processing of coating machine oven parts under the network collaborative manufacturing mode, this paper proposes a composition optimization method for coating machine oven-manufacturing services based on an improved sparrow search algorithm. We establish a framework for the service composition optimization problem on the oven manufacturing service platform; complete an evaluation of the manufacturing service quality of service indicators (QoS) and energy consumption indicators; construct a dual-objective service composition optimization mathematical model considering the QoS and energy consumption indicators; and embed the Tent chaotic mapping, elite reverse learning, and Lévy flight improvement differential evolution strategies into the sparrow search algorithm. We named this algorithm the LCSSA_DE algorithm, using it to solve the mathematical model of the manufacturing service combination problem of coating machine ovens, and obtain the optimal manufacturing service combination recommendation scheme. The experimental results demonstrate that this algorithm can effectively improve the convergence speed compared with the suboptimal multi-objective artificial vulture optimization algorithm (MOAVOA), with the average convergence time improved by 7.26%, avoiding falling into the local optimum during the search, while 69%–77% of the test points are more in line with the preference criteria of the Pareto frontier, and can be adapted to the optimization of the coating machine oven manufacturing service composition optimization problem at different scales. Full article

As an emerging development field, in recent years, emergency industrial parks in China have faced increasingly complex and high-risk challenges. This article proposes the establishment of a scientific safety risk assessment and grading model to help improve the safety management level of emergency industrial parks, in response to the problems of the multi-source heterogeneity of fire risks in emergency industrial parks and the difficulty of comprehensive assessment using traditional methods. This approach combines enterprise type classification with multi-level assessment for the first time, effectively identifying high-risk links such as fires and explosions and playing an effective role in preventing accidents such as fires in the park. Enterprises within the park are categorized into seven distinct groups based on their characteristics and associated safety risks: medical and healthcare, new energy storage, composite materials and new materials, intelligent manufacturing, mechanical manufacturing, consulting and technical services, and construction and installation. The following models are constructed: (1) a risk assessment model based on AHP-FCE, which can assess the safety risk levels of individual enterprises and the industrial park at a macro level; (2) a risk grading model based on the risk matrix method, which can inspect and control specific risk sources at a micro level. The integration of these two methods establishes a comprehensive model for safety risk assessment and grading in emergency industrial parks, significantly improving both the accuracy and the systematic nature of risk management processes. Full article

As an advanced high-temperature structural material, TiAl alloy, is often used in the manufacturing of hot-end components of aviation and aerospace engines. However, it is difficult to increase the strength at high temperature, which limits its wider application. Adopting composite material technology is one of the effective ways to improve the comprehensive mechanical properties of TiAl alloy. In this work, by adding 3 wt.% SiC micro-particles to Ti-47.5Al-7Nb-0.4W-0.1B (at.%) pre-alloyed powder, a core-shell structure dual-MAX-phase high-temperature strengthened TiAl matrix composite (also known as TiAl-SiC composite) was prepared by combining powder metallurgy and hot forging. The microstructure and high-temperature compressive properties of the prepared TiAl-SiC composites were studied and compared with TiAl alloy prepared by the same process, and the microstructural characteristics of the TiAl-SiC composite and its microstructure evolution during processing were revealed. The results show that the matrix of as-sintered TiAl-SiC composites was mainly composed of γ phase and a small amount of Ti₂AlC particles, while the reinforcement phase was a dual-MAX-phase core-shell structure, which was mainly composed of core Ti₂AlC phase, shell Ti₃SiC₂ phase, and small Ti₂AlC particles distributed in the outer layer. After hot forging, the microstructure of TiAl-SiC composite became more compact, finer, and more uniform; the phase composition was almost not changed, but the content of Ti₂AlC, Ti₃SiC₂, and TiB₂ phases increased significantly; the content of C in each constituent phase decreased obviously, and a granular Si-rich phase was generated in the core of the reinforcement phase. The yield strength of the as-forged TiAl-SiC composite was significantly higher than that of the as-forged TiAl alloy at temperature higher than 859 °C. This is because the core-shell structure dual MAX phases can effectively reduce the softening rate of TiAl alloy in the range of 800–900 °C, thus playing a strengthening role and increasing the service temperature of TiAl alloy. Full article

Aiming at the problem of the low collaborative efficiency of outsourced processing of wallboard parts of a coating machine under a network collaborative manufacturing mode, this paper proposes a wallboard manufacturing resource composition optimization method based on the Improved Polar Bear Optimization (IPBO) algorithm. The processing process of the wallboard is analyzed, and the process-level splitting of the wallboard manufacturing task is completed; the required manufacturing resource service portfolio is determined, and the resource evaluation indicator system for key performance indicators of wallboard manufacturing resources is established; non-cooperative game decision-making is used to construct a wallboard manufacturing resource composition optimization model from two aspects, namely, quality indicators and flexibility indicators; an adaptive vision and mutation strategy is introduced to carry out the Polar Bear Optimization (PBO) algorithm. Finally, the improved algorithm is used to solve the wallboard manufacturing resource composition optimization model. The experimental results show that the IPBO algorithm reduces the average convergence time by 6.51% and the optimal convergence time by 9.26% compared with the suboptimal Dung Beetle Optimization (DBO) algorithm, and 65%–72% of the test points of the IPBO algorithm are more in line with the preference criteria of the Pareto frontier. Meanwhile, it demonstrates both validity and superiority in solving the problem of expanding the size of wallboards for coating machines. Full article

Nanojoining, which utilizes nanoparticles for joining applications, is an interesting method that stands out from conventional processes by combining relatively low joining temperatures with high service temperatures. To use the nanoparticles for this purpose, it has proven useful to process them as a paste. The chemical composition of such a nanopaste has a certain influence on the properties ultimately achieved by the joint. While nickel nanoparticles represent the metal content of the here investigated nanopastes, a variety of substances can be utilized as organic components to form the actual paste-like suspension. Derived from the literature on nanoparticle synthesis, a variety of candidates were identified from which numerous paste compositions were developed for this work. So, high metal content (70 wt.%) nickel nanopastes were prepared from these solvent–stabilizer systems by ultrasound-enhanced mixing. The study evaluates the pastes in terms of manufacturability and handleability. The findings reveal insights into the effects of different chemical substances. Additionally, joining tests using the mild steel DC01 are presented, demonstrating the impact of the paste composition on the joining strength and the microstructure of the joint as well. Within this study, a paste consisting of terpineol and KD4 was the most favorable. Full article

Plasma nitriding (PN) is often used to enhance the mechanical properties (surface hardness, wear and corrosion resistance) of bulk alloys. High-quality AlCrN hard coatings were obtained using high-power pulsed magnetron sputtering (HiPIMS) technology. This study proposes a combination of two surface treatment methods (plasma nitriding and hard coating deposition) in a continuous plasma process to optimize the application and service life of cutting tools. The main feature of this study is to verify the mechanical properties and adhesion strength of nitride tungsten carbide (WC-Co) bulk at a lower temperature (∼300 °C) and shorter time (0.5 to 1.5 h) of PN treatment. After 1.5 h of PN treatment on the WC-Co substrate without subsequent coating, the ultra-thin WN_x diffusion interlayer (thickness ∼11.5 nm) on the subsurface was directly observed via TEM analysis, and the types of chemical bonding were confirmed by XPS analysis. Vickers analysis indicated that the surface hardness of the nitrided WC-Co substrate was enhanced by PN treatment from 1534 to 2034 Hv. The AlCrN coating deposited on the nitrided WC-Co substrate significantly enhances the surface mechanical properties, including adhesion strength (increasing from 70 to 150 N), hardness (rising from 2257 to 2568 HV), and wear resistance (with the wear rate decreasing from 14.5 to 3.4 × 10⁻⁸ mm³/Nm). Composite surface technology has a high commercial application value because it enhances the value of products under the existing equipment of manufacturers. Full article

Wood–plastic composites (WPCs) have emerged as a sustainable and cost-effective material for construction, particularly in low-cost housing solutions. However, designing WPC panels that meet structural, serviceability, and manufacturing constraints remains a challenge. This study focused on optimizing the cross-sectional shape of WPC roof panels using evolutionary algorithms to minimize material usage while ensuring compliance with deflection and stress constraints. Two evolutionary algorithms—the genetic algorithm (GA) and particle swarm optimization (PSO)—were employed to optimize sinusoidal and trapezoidal panel profiles. The optimization framework integrated finite element analysis (FEA) to evaluate structural performance under uniformly distributed loads and self-weight. The modulus of elasticity of the WPC material was determined experimentally through three-point bending tests, ensuring accurate material representation in the simulations. The trapezoidal profile proved to be the most optimal, exhibiting superior deflection performance compared with the sinusoidal profile. A comparative analysis of GA and PSO revealed that PSO outperformed GA in both solution optimality and convergence speed, demonstrating its superior efficiency in navigating the design space and identifying high-performance solutions. The findings highlight the potential of WPCs in low-cost housing applications and offer insights into the selection of optimization algorithms for similar engineering design problems. Full article