Fused filament fabrication (FFF) has evolved from a technology for prototyping into a functional manufacturing method; however, its industrial viability is often hindered by challenges in process predictability and part fidelity, particularly during high-speed cornering motions. Traditional trajectory planning relies on linear segments (G1 commands), where sudden directional changes necessitate abrupt decelerations to avoid exceeding mechanical limits, can result in local over-extrusion, dimensional inaccuracies, and increased print times. To address these limitations, this study proposes a path smoothening approach using quintic Pythagorean-Hodograph (PH) curves to replace abrupt direction changes with smooth, curvature-continuous ( G^2 ) blends. Unlike established polynomial interpolations, PH curves allow for exact arc-length calculation, enabling precise synchronization between nozzle motion and material extrusion without the need for numerical approximation. The proposed method blends curvature-continuous corner smoothing with a hybrid feed rate scheduling strategy that keeps the commanded acceleration continuous while keeping the jerk bounded and maintaining uniform deposition in corner regions. The methodology was validated through experiments conducted on an industrial machine tool benchmark and a retrofitted, screw-driven FFF system, utilizing test trajectories with varying corner angles. Experimental results demonstrate that the PH-based blending strategy significantly reduces acceleration peaks at trajectory junctions compared to sharp corner trajectories. This capability allows the machine kinematics to maintain higher non-zero velocities through corners, while reducing mechanical vibrations and preventing the instantaneous acceleration and deceleration demands associated with unoptimized transitions. Capabilities of the PH curves allow to increase the quality and fidelity of the parts printed with fused filament fabrication method for end use applications.
In this study, silicon carbide (SiC) powder was used to reinforce AlSi10Mg powder for fabricating the aluminum matrix composites (AMCs) via the laser powder bed fusion (PBF-L) process. The study investigated the effects of different SiC contents on the porosity, microstructure, microhardness, wear performance, and tensile properties of the AMCs. The cellular/dendritic microstructure became finer after SiC addition. XRD analysis revealed low-intensity diffraction peaks corresponding to Al4SiC4, while SEM/EDS observations showed needle-like Al-Si–C-rich features in the composite microstructure. The AMC containing 10 wt.
The increasing adoption of Industry 4.0 paradigms has highlighted the need for real-time, high-resolution data acquisition in manufacturing systems, particularly regarding human operator activities, which remain one of the least digitized elements in assembly environments. Traditional time measurement approaches are often manual, intrusive, and difficult to scale, limiting their applicability in dynamic production settings. This paper proposes a UHF RFID-based framework for non-intrusive, real-time monitoring of operator loop times in assembly lines. The approach enables continuous and automated data acquisition without disrupting normal operations, contributing to enhanced visibility of human-centric processes within manufacturing systems. The framework integrates optimized antenna configurations and tag placement strategies to ensure robust performance under industrial conditions. The proposed system is validated in a real assembly environment, and its performance is assessed through a comprehensive statistical analysis, including correlation and Bland-Altman methods. Escrita. Additionally, the two one-sided tests (TOST) procedure is used to assess statistical equivalence between UHF RFID-based and manual time measurements, using an equivalence margin of ± 0.5 s. The results indicate strong correlation and statistical equivalence between UHF RFID-based and manual time measurements, supporting the feasibility of the proposed approach under the tested production conditions. Beyond cycle-time measurement, the framework offers a basis for data-driven decision-making, with potential applications in line balancing, bottleneck identification, and the development of digital manufacturing systems.
Brushless DC motors are employed in wide variety of applications including aerospace, robotics, healthcare and so on due to their advantages such as high operating life, high efficiency, high dynamic response. This paper describes speed control system of BLDC motor in Automatic Guided Vehicle using Fuzzy PID controller. The signal obtained from Hall-effect sensor of the motor can be analyzed to measure velocity of the robot. Fuzzy PID controller with high speed response characteristic and robustness is designed to maintain velocity of the robot. Thus workpieces on the robot don’t fall down under the several conditions such as setting off and stopping of the robot and sudden load variation. Using designed FPID controller, we can calculate output voltage and drive BLDC motor by using Pulse Width Modulation method. Several simulations using MATLAB are taken to assessment the advantages of the proposed method. This control system reveals high speed response characteristics and reliability in running operation especially under the varying load condition.
Machine-tool spindle digital twins require dynamically consistent, traceable parameterisation across numerical simulation, reduced-order modelling, experimental characterisation, and operational deployment. This work presents a hybrid characterisation and digital-twin initialisation framework for an integrated motor spindle, systematically reconciling free–free finite element analysis (FEA), a physics-based 3-DOF/six-state state-space (SS) model, and suspended experimental modal analysis (EMA). Boundary-condition harmonisation, Gramian-based model balancing, analytical treatment of closed-loop speed diagnostics, and parameter-provenance tracking establish a physically interpretable, auditable digital-twin parameter vector θ̂ . Within the 20–80 Hz validation band, the dominant axial mode is identified at 38.09 Hz from FEA, 38.32 Hz from the SS model, and 37.55 Hz from EMA, with axial frequency-response assurance criterion (FRAC) values of 0.961–0.996, confirming resonance-frequency and FRF-shape consistency across FEA, the state-space model, and EMA. Radial and torsional responses provide complementary cross-domain consistency evidence within the available excitation and measurement resolution. Parametric stiffness-retention studies confirm the framework’s physical consistency, reproducing the expected square-root resonance softening and reciprocal compliance growth through a model-based fault-injection layer for controlled degradation studies. The reconciled digital twin is deployed on an edge-computing platform interfaced with OPC-UA supervisory data over the 500–3000 RPM edge-deployment range considered in this study, within which the higher-speed results are interpreted as low-bandwidth operational-consistency evidence rather than validated high-speed FRF behaviour, consistent with the non-gyroscopic reduced-order formulation adopted here. Model-conditioned bearing-health indicators and remaining-useful-life (RUL) trajectories are then evaluated, demonstrating how experimentally reconciled structural parameters can support operational health assessment under defined degradation assumptions. The framework thus provides a traceable, physically grounded pathway from structural characterisation to edge-deployed spindle digital twins, and establishes the experimental and calibration basis for the seeded-fault, run-to-failure, and independently validated prognostic studies that follow.
