Search Results (1,697)

This paper investigates the valorization of peanut shell powder (PSP), an abundant agro-industrial residue, as a biofiller for the development of sustainable 3D printable PLA-based composites for food packaging applications. A low-filled biocomposite containing 2.5 wt.% PSP was successfully processed into filament with dimensional tolerances suitable for fused deposition modeling printing. Thermal and melt flow analyses demonstrated that PSP marginally reduced the thermal stability of PLA while preserving its thermal transition temperatures and increasing the melt flow rate up to 51%. Differential scanning calorimetry revealed a slight increase in crystallinity in biocomposite filament compared to neat PLA pellets, mainly associated with thermo-mechanical processing of the extrusion, while the lower crystallinity degree relative to PLA extrudate suggested a negligible nucleating effect of PSP. To optimize print quality, different extrusion temperatures and infill flow rates were evaluated. The best mechanical performance was achieved at 200 °C and 130% flow rate, where reduced inter-filament porosity (5.2%) resulted in improved tensile strength and stiffness compared with the other printing conditions. Although mechanical properties remained lower than neat PLA, the material proved suitable for non-structural packaging applications. Prototype packaging boxes were fabricated and tested for the storage of fresh-cut melon. Compared with neat PLA packaging, the PLA-PSP system better preserved fruit firmness over 10 days, inhibited fungal growth, and delayed visible deterioration, highlighting the potential active role of PSP in food preservation. Anaerobic biodegradation tests conducted under mesophilic conditions confirmed that the addition of PSP did not hinder PLA biodegradability and slightly enhanced methane production. Overall, the results demonstrate that peanut shell waste can be effectively upcycled into functional 3D-printable biocomposites for sustainable packaging solutions. Full article

The rapid advancement of internet technology has transformed the tourism industry from traditional offline services to digital networked, and intelligent platforms. WebGIS has become critical infrastructure for tourism information retrieval and spatial decision-making. However, the growing volume and heterogeneity of multi-source tourism data expose fundamental limitations in conventional relational database architectures, particularly in handling complex spatial semantic queries. To address this, the present study proposes a WebGIS design methodology that integrates knowledge graphs with relational databases through a dual-database collaborative architecture. Using tourist attraction data from China’s Xinjiang Uyghur Autonomous Region as a case study, a prototype Xinjiang Smart Tourism WebGIS system was constructed, which consists of an asynchronous synchronization mechanism based on Change Data Capture (CDC) to ensure data consistency across heterogeneous databases. Subsequently, tourism semantic queries of varying depths were constructed and comprehensively tested across different data scales. The experimental results indicate that the proposed methodology effectively decouples business transactions and supports complex relationship computations, achieving shorter cross-domain semantic query times and higher latency stability. These findings offer practical guidance for designing high-performance regional tourism information services. Full article

This article presents the synthesis, implementation, and experimental study of a PI-based adaptive actor–critic displacement volume controller of an axial-piston pump intended for open-loop circuit hydraulic drive systems. The proposed control structure combines a conventional PI actor with an adaptive critic that estimates the infinite-horizon cost through Bellman-error minimization. By using the tracking error and its integral as actor inputs, the controller avoids the need for an accurate plant model while retaining a compact and practically implementable structure. The adaptive laws are derived using gradient-based learning, and a Lyapunov-based analysis establishes closed-loop stability for sufficiently small adaptation gains. The controller is implemented in a fixed-step Simulink^® environment and deployed on a rapid prototyping platform with real-time communication to an industrial microcontroller and proportional valve amplifier. The experimental results obtained under four fixed loading conditions and dynamic load variations demonstrate a stable operation, bounded critic behavior, and a near-zero Bellman error during learning. Comparative tests against a classical PI controller, a Lyapunov-based model reference adaptive controller, and a generic actor–critic scheme show that the proposed PI-based actor–critic achieves the lowest performance index and the shortest settling times in most cases. Full article

In engineer-to-order (ETO) manufacturing environments, the high variability of final product configurations makes it difficult to consistently estimate material consumption and, consequently, to define appropriate inventory control policies. This paper proposes a data-driven framework based on unsupervised learning to identify product typologies from historical manufacturing orders in a real industrial context. The approach employs a fuzzy k-prototypes algorithm to cluster mixed-type data, allowing the simultaneous treatment of numerical and categorical variables. In the case study, the proposed crisp-BOM-based scenario achieved a 28.67% reduction in line-side WIP and a 10.79% reduction in linear storage space, corresponding to the release of approximately two to three assembly stations. From the resulting fuzzy memberships, probabilistic bill of materials (BOM) structures are constructed, capturing the inherent variability of material consumption across different product configurations. A defuzzification procedure is then applied to obtain a crisp BOM representation suitable for operational decision-making. Additionally, a material versatility indicator based on entropy is introduced to quantify the dispersion of each material across product typologies. This indicator, together with the estimated consumption per cluster, is used as input for an analytical inventory model that supports the classification of materials into kanban or kitting policies. The methodology is validated using real data from a high- and medium-voltage switchgear manufacturing plant, comprising over 60,000 order–material observations. The results show that the proposed framework enables a more structured characterization of material behavior, reducing reliance on planner experience and improving the consistency of inventory policy decisions. From an industrial perspective, the approach provides a practical and scalable tool for aligning inventory strategies with the actual consumption patterns of ETO systems. Full article

This study aimed to design, develop, and evaluate a multi-axis welding positioner, designed as a laboratory simulator with 360° rotational capability and 90° tilting functionality to support outcome-based instruction in welding and fabrication technology courses. A developmental research design was employed to systematically address common challenges in instructional welding operations, such as limited workpiece maneuverability, inconsistent welding angles, operator fatigue, safety risks from manual repositioning, and the lack of affordable, adaptable positioning equipment. The study was conducted at Caraga State University–Cabadbaran Campus in Cabadbaran City, Agusan del Norte, and involved sixteen purposively selected experts in Welding and Fabrication Technology. These experts assessed the prototype during the design, development, and evaluation phases via a validated researcher-developed survey instrument. The welding positioner was evaluated based on the following criteria: design, construction and material availability, functionality, usability, safety, modularity, and ergonomics. Data were analyzed using descriptive statistics. Findings indicated that the prototype was highly functional, safe, and user-centered, enhancing welding accuracy and reducing operator fatigue. Of the evaluated parameters, Design, Construction, and Material Availability achieved the highest mean rating (3.61), reflecting strong structural quality and resource accessibility. Functionality received the lowest mean rating (3.51), signaling minor areas for improvement in responsiveness and component adjustability. The prototype, built from locally available, cost-effective materials, featured a motorized rotation system and a manual tilting mechanism that operated reliably during testing. The study concluded that the welding positioner met structural, ergonomic, and operational standards for use as a laboratory simulator in outcome-based welding instruction. Recommendations include integrating automated controls, enhancing portability, embedding digital monitoring features, and conducting extended performance evaluations in industrial settings. Full article

This paper presents a flight–attachment–crawling robot (FACR) for close-range inspection of large-scale crane structures, aiming to improve access efficiency and contact-based inspection capability in elevated and discontinuous metallic environments. The proposed robot integrates flight, magnetic attachment and crawling units. To clarify the multimodal operating mechanism, dynamic models are established for the flight, wall-supported locomotion, and wall-attachment modes. Computational fluid dynamics simulations are then conducted to analyze near-wall aerodynamic effects, including the influence of wall proximity and lateral-rotor activation on rotor wake interaction, lift variation, and wall-normal support. A prototype platform is developed, and representative staged experiments are carried out to evaluate multimodal operation. The results show that the proposed FACR can support key multimodal operating stages required for crane-oriented inspection and provides a feasible platform-level solution for combining aerial mobility, wall-surface operation, and fixed-point attachment in complex industrial environments. Full article

Harmonized laboratory methodologies, notably the CEPI recyclability laboratory test method (latest version 3, released February 2025) and the 4evergreen protocol (latest revision 1, released January 2025), are widely used to assess the recyclability of paper-based materials. However, the extent to which laboratory-scale results reflect pilot-scale behavior remains insufficiently documented. In this work, the recyclability of brown packaging paper was evaluated at both laboratory and pilot scales. Disintegration was performed under identical consistency, temperature, and duration, followed by screening, filtrate analysis, macro-stickies quantification, and paper sheet adhesion evaluation according to the CEPI methodology. In parallel, recycled paper prototypes were produced in a pilot paper machine and were mechanically characterized. The material was classified as technically recyclable in a conventional recycling mill at both scales, with closely aligned recyclability scores. Nevertheless, pilot-scale testing revealed higher dissolved and colloidal substances, increased macro-stickies content, and sheet adhesion phenomena not fully apparent at laboratory scale. These results demonstrate that while laboratory tests are robust for recyclability classification, pilot-scale trials provide essential insights into runnability and operational risks relevant for industrial implementation. Full article

The fashion industry generates a major environmental impact, requiring integrated sustainable approaches. This study integrates six thematic axes—sustainability, modular design, natural materials, eco-friendly dyeing, multidimensional comfort and consumer perception, and radial composition—into an integrative framework for sustainable design. The mixed-methods methodology comprises four stages: (I) a quantitative stage (questionnaire, n = 150); (II) an experimental stage (testing of comfort characteristics of linen fabrics according to ISO standards, and indigo dyeing through three techniques: uniform, tie-dye, and shibori); (III) a digital design stage in CLO3D and physical fabrication of the prototype; (IV) a prototype testing and validation stage (panel, n = 20). The prototype provides functional adaptability through 8 design configurations, versatility through reversibility, and aesthetic diversity through the radial composition, yielding 16 distinct wearing modes within a single product. Panel evaluation confirms high prototype acceptance (M = 4.81–4.95), and physical interaction with the prototype significantly increases purchase intention compared with conceptual evaluation (M_pre = 3.54; M_post = 4.60; d = 2.04; p < 0.001). The contribution validates a framework that integrates six dimensions of sustainable fashion into a coherent clothing design model, demonstrating design’s role as a practical instrument in the sustainability transition, with applied implications for designers and researchers. Full article

The study introduces a portable sliding sand sieve, transforming traditional stationary systems into an innovative solution for sand separation in the construction industry. This innovative tool offers improved mobility, durability, and operational efficiency, particularly for construction workers, civil technology students, and educators in areas with limited access to advanced equipment. Utilizing a developmental research design, the study involved the conceptualization, fabrication, and evaluation of the prototype. The design incorporated locally available materials, including phenolic boards, mesh screens, steel tubing, and a sliding mechanism supported by bearings and brackets. The Input–Process–Output (IPO) model guided the development, ensuring focus on functionality, affordability, and user safety. To address this gap, the researchers aimed to design, develop, and evaluate a portable sliding sand sieve to enhance sand sieving in construction settings. Expert and student evaluators highly rated the portable sliding sand sieve for its design simplicity, functionality, durability, modularity, and ergonomics. It was praised for its ease of use, time-saving capability, and adaptability to various work environments. The sliding feature enabled continuous sand flow, enhancing productivity and reducing physical strain. Full article

The ongoing evolution of Industry 4.0 technologies necessitates novel and effective modes of human–machine interaction within production environments. This work presents a modular approach to the design and implementation of graphical user interfaces (GUI) in mixed reality, leveraging the Asset Administration Shell (AAS) standard. The proposed method enables the dynamic rendering of GUI elements in a Mixed Reality setting based on structured data retrieved from an AAS server. Developed for the Microsoft HoloLens 2 using the Unity engine and the Microsoft Reality Toolkit 3 (MRTK3), the system allows for the spatial placement of interface components either at predefined coordinates or in relation to specific elements of a production line model. Additionally, it incorporates a real-time distributed architecture utilizing OPC UA PubSub and MQTT protocols for processing and visualising live data. The prototype demonstrates the viability of using AAS as a flexible framework for defining and generating GUI components in immersive environments and lays the groundwork for further research into standardised, easily deployable user interface solutions for industrial applications. Full article

This paper presents a methodology for synthesizing static state feedback controllers utilizing a Fractional-Order Performance Index. Linear Quadratic Regulators are designed using integer-order integral weighting functions. In the proposed approach, fractional-order calculus is utilized to introduce an additional degree of freedom in controller synthesis, enabling enhanced shaping of the plant’s dynamic properties. The controller gains are obtained by solving a fractional Riccati-like equation, through which the temporal weighting properties inherent to fractional integration are embedded into a static feedback matrix. This formulation is a minimalist control structure suitable for implementation on resource-constrained hardware. The proposed method is validated via rapid control prototyping on an industrial NI PXIe platform and an analog third-order plant. Performance evaluation using Integral Absolute Error and Integral Absolute Control metrics demonstrates that the fractional order serves as a flexible tuning parameter, providing an alternative trade-off between settling time and control effort. Furthermore, frequency domain sensitivity analysis demonstrates the absence of resonant peaks and inherent attenuation of high-frequency measurement noise. As a result, the presented framework bridges fractional-order optimization techniques with industrial control platforms. Full article

Nowadays, numerical simulation methods are advanced and widely used in industry, enabling the modeling of complex systems from printed circuit boards (PCBs) to full power converters. Among many isolated topologies, the phase-shift full-bridge (PSFB) topology is a well-established solution for isolated DC–DC conversion in electric vehicles. Therefore, this paper proposes a broadband electromagnetic compatibility (EMC) modeling methodology for a custom-designed 1 kW gallium nitride (GaN)-based PSFB converter intended for an electric vehicle (EV) DC powertrain. Moreover, the approach combines full-wave electromagnetic simulation with circuit-level simulation, including parasitic effects from PCB layout, power harnesses, and discrete components. Thus, the virtual prototype is assessed within a complete virtual test bench compliant with the standard Comité International Spécial des Perturbations Radioélectriques (CISPR) 25 over the 150 kHz–108 MHz range to capture common-mode (CM) and differential-mode (DM) conducted electromagnetic interference (EMI). Results show that the converter achieves efficiencies of 97.26% in standalone mode and 97.03% when integrated into the full DC powertrain. However, the conducted EMI assessment reveals that both CM and DM emissions exceed CISPR 25 Class 2 limits across the entire spectrum, with excess levels reaching up to 72 dBµV. Therefore, power harnesses significantly increase EMI levels at low frequencies due to the distributed inductance and stray capacitance. Finally, this study demonstrates the value of virtual prototyping for simulation-based EMI prediction in early-stage power converter design. Full article

This study designed and developed a Portable Drill and Grinder Holder with an Integrated Measurement Guide to improve stability, safety, and accuracy in hand-held power tool operations. Addressing workshop challenges like excessive vibration and uncontrolled tool movement, the project employed a developmental research design involving sixteen (16) welding experts. The prototype was constructed using durable, locally available materials to ensure affordability. Evaluation results showed significant improvements in operator control, with Safety receiving the highest rating (M = 3.66). The findings confirm that the tool meets industry standards for instructional and workshop use. Full article

Ultra-High Molecular Weight Polyethylene (UHMWPE), the standard base material in ski manufacturing, offers excellent gliding performance but exhibits limited mechanical and scratch resistance on hard and icy snow conditions. In this work, stainless steel is proposed as a mechanically robust alternative, and its inherently higher friction against snow is addressed through surface engineering. The snow friction behavior of 301H stainless steel surfaces decorated with fishbone-like microstructures combined with Laser-Induced Periodic Surface Structures (LIPSSs) was investigated using a custom-built snow tribometer. Several pattern designs, with different pitch distances and depths, were engraved using femtosecond laser pulse irradiation. We conducted morphological, physical, and chemical investigations through microscopy, static contact angle measurements, and X-ray Photoelectron Spectroscopy analyses. Results indicate that the gliding performance is not directly related to the modifications in surface chemistry and wetting behavior of the samples but is affected by the geometry and orientation with respect to the sliding direction of the specific micro- and nano-features. Overall, we achieved friction coefficient values comparable to those found in UHMWPE with a fast and economically sustainable single-step laser-texturing process. This approach allows the industrial up-scaling of the fishbone-texture design to real-size alpine ski prototypes. Full article

Autoencoders (AEs) have been widely used for industrial process fault detection owing to their ability to learn nonlinear representations from normal operating data. However, conventional AE methods rely heavily on reconstruction errors and may miss weak faults due to overgeneralization. In addition, insufficient modeling of temporal evolution and operating condition variations may reduce their sensitivity to dynamic faults. To address these issues, this study proposes a memory-enhanced and prediction-assisted conditional variational autoencoder named MI-CVAE for unsupervised fault detection. In the proposed framework, statistical features extracted from sliding windows are used as condition information to describe variable operating states. A memory module stores representative normal prototypes to constrain reconstruction and reduce overgeneralization to faulty samples. Meanwhile, an Informer branch captures temporal dependencies and provides complementary prediction residuals. Reconstruction and prediction residuals are fused to construct squared prediction error and squared Mahalanobis distance statistics, with control limits determined by kernel density estimation. The proposed method is validated on the Benchmark Simulation Model No. 1 wastewater treatment benchmark and a real papermaking process dataset. The results show that MI-CVAE outperforms the evaluated comparison methods, particularly in detecting weak and dynamic faults, while maintaining a low false alarm rate. Full article