Recent Patents on Mechanical Engineering - Volume 18, Issue 4, 2025

The aerospace industry has been gradually adopting Industry 4.0 technologies, such as the Internet of Things (IoT), big data analytics, and cyber-physical systems, to enhance aircraft maintenance, repair, and overhaul (MRO) operations. These technologies have the potential to improve operational efficiency, reduce costs, and enhance safety in the MRO sector.

This study aims to analyze the current state of Industry 4.0 integration in aircraft maintenance/MRO operations by examining relevant use cases and conducting a patent landscape analysis. The primary objectives are to identify the key players, emerging trends, and technological hotspots in this field, as well as to understand the challenges and opportunities associated with the integration of Industry 4.0 in aircraft MRO.

The research methodology involves a comprehensive literature review to identify and analyze use cases of Industry 4.0 technologies in aircraft manufacturing and MRO operations. A systematic approach was adopted to collect and analyze relevant patent data from various patent databases. The search strategy involved the use of specific keywords related to Industry 4.0 technologies and aircraft MRO. The retrieved patent documents were then subjected to rigorous analysis, including bibliometric analysis, technological categorization, and patent landscape mapping.

The patent landscape analysis revealed a steadily increasing trend in patent filings related to Industry 4.0 technologies in aircraft MRO. The major players in this field were identified, and their patent portfolios were analyzed. The analysis of use cases also highlighted that key technological areas, such as 3-D printing and digital twin technology, are attracting significant attention from aircraft industry stakeholders.

The analysis of patent landscapes in the field of aircraft maintenance, repair, and overhaul (MRO) provides valuable insights into the current state, emerging trends, and future directions within the industry. These insights are crucial for industry stakeholders, researchers, and policymakers to make informed decisions regarding technology adoption, investment strategies, and regulatory frameworks. In conclusion, the examination of patent landscapes serves as a foundational tool for enhancing transparency, standardization, and reproducibility in research, enabling stakeholders to navigate the complex landscape of Industry 4.0 in aircraft MRO effectively.

Spur gears are crucial for power transmission but often fail due to fatigue-induced stresses and design challenges at the tooth root.

This study aims to address spur gear design challenges through comprehensive stress analysis, using modeling and FEM to assess bending stresses and explore strategies to reduce stress concentrations at the tooth root.

The research uses SolidWorks and ANSYS for FEM analysis, focusing on bending stresses and exploring modifications in gear design using various materials for optimization.

The analysis shows strategic modifications to the gear's fillet radius and addendum can reduce stress at the tooth root by 38.26%, with stainless steel being the optimal material for enhanced gear strength.

The study emphasizes strategic adjustments in fillet radius and addendum to reduce stress in spur gears, highlighting stainless steel's superior performance for optimized design and enhanced strength.

Since flexible robotic arms generate free vibration during operation due to the special characteristics of the material, vibration suppression and control are the primary problems in this field.

The research objective of this paper is to design an improved controller for a single-link flexible robotic arm system that utilizes a new control method to achieve more accurate tracking accuracy and less end vibration during the movement of the robotic arm.

An adaptive robust sliding mode controller is designed for the slow time scale model, a linear quadratic (LQR) controller is designed for the fast time scale model, and the weight matrix Q in the LQR is autonomously optimised by an improved particle swarm algorithm, which combines the control rates of the two to control the trajectory tracking of the flexible robotic arm while suppressing the end vibration.

Experimental and comparative studies show that the method proposed in this paper substantially improves the trajectory tracking accuracy of the flexible robotic arm and reduces the end vibration to a large extent with obvious advantages, which verifies the reasonableness of the improved controller.

The method proposed in this paper has more prominent advantages in trajectory tracking of flexible robotic arms, which is reflected in its smaller trajectory tracking error and relatively shorter time to track the target curve. At the same time, the search speed and convergence accuracy of the optimal value are improved to make the end vibration smaller, which largely reduces the end vibration of the flexible robotic arm and reduces the mechanical fatigue damage of the flexible robotic arm, which is of great significance for the research and development in this field.

On-orbit servicing of spacecraft is mainly aimed at repairing failed spacecraft, maintaining and upgrading normally operating spacecraft to extend their life in order to reduce the increase of space debris and maintain the space environment.

In performing on-orbit servicing, the spacecraft typically requires continuous control force to hover for a long period of time in order to maintain a relatively stationary state towards the target.

Considering the limited amount of fuel carried, the Lorentz force is introduced into on-orbit servicing to assist spacecraft in hovering. In order to demonstrate the feasibility of using Lorentz force as spacecraft thrust, many related patents have been provided.

Firstly, the velocity of the spacecraft's orbital motion and the variation of the geomagnetic field were given, and the specific expression of the Lorentz force in the relative dynamics model of the spacecraft was deduced. When studying the auxiliary effect of Lorentz force, a critical angle was defined. The relation between the critical angle and the Lorentz force on the auxiliary effect of spacecraft hovering was analyzed through numerical examples.

Furthermore, based on the influence of the charge-to-mass ratio on the critical angle, the variation law of the Lorentz force-assisted spacecraft hovering area with different charge-to-mass ratios was derived.

In recent years, patents have shown that upper-limb rehabilitation robots play a significant role in home-based rehabilitation training for stroke hemiplegia patients. Changes in muscle tension during the flaccid paralysis phase cause the rehabilitation robot to deviate from the predetermined motion trajectory. This poses a challenge to the mathematical modeling of the rehabilitation robot and the design of the nonlinear extended state observer (NESO).

To address the problem of trajectory tracking errors caused by changes in the patient's muscle tension, a method based on optimizing the nonlinear function within the NESO is proposed.

First, a mathematical model of the upper-limb rehabilitation robot is established to obtain the dynamic relationship between the robot's velocity and the input voltage. Second, the nonlinear function of the NESO is optimized by adjusting the gain values of the sine and tangent functions to effectively estimate muscle tension and reduce the problem of accumulative error due to changes in muscle tension. Finally, comparative simulations of trajectory tracking including the optimized nonlinear function as well as the sine, tangent and power functions are performed on the MATLAB platform.

The NESO is constructed to estimate changes in muscle tension based on sine, tangent, and power functions, as well as optimized nonlinear functions. The equivalent gain values of each function and the muscle tension estimation curves of the NESO are compared. The simulation results show that the equivalent gain value of the optimized nonlinear function acting in NESO is increased to more than 8 and the convergence time is reduced by 11.9% accordingly. This conclusion is validated by simulations and practical tests.

The optimized nonlinear function shortens the estimation time of the NESO for changes in muscle tension, which can provide a reference value for the design of observers for upper-limb rehabilitation robots of patients in the flaccid paralysis stage.

Defects in casting related to the stage of the process, like filling or solidification and related to many parameters (process, geometric, and material). In the casting field, extreme temperatures refer to the high heat necessary to melt and maintain metals or other materials in a liquid state, enabling them to be shaped into desired forms using molds. Extreme temperature and other factors, such as die rotation speed play an important role in the formation of defects, as their significant increase leads to excessive viscosity or instability in the flowing metal. The effective method that takes the least time and cost to explore this defect is simulation, and such patent-based approaches have gained attention for their potential in industrial application.

This study aims to predict the porosity defect for the 3D pattern in vertical centrifugal casting during filling of A413 and A356.

A three-dimensional transient simulation was done for flowing mode in five molds having various aspects ratio from 1 to 2 in step 0.25 with change in pouring temperature and mold rotation speed (700 - 800°C and 50 - 150 rpm with step 25°C, 25 rpm) considering the existance of air phase with fluid inside the mold.

The study's findings reveal that when the pouring temperature exceeds 750°C and the mold rotation speed surpasses 100 RPM, porosity significantly decreases. Generally, increasing the rotation speed from 50 to 150 RPM reduces defects, except when the pouring temperature is low, specifically less than 725°C. Additionally, porosity decreases with an increase in the aspect ratio up to 2, accompanied by the lowest interface heat transfer coefficients observed at 6867.62 W/(m²·K) for A413 and 7703.89 W/(m²·K) for A356.

Determining the interface’s heat transfer coefficient at each moment ensures accuracy and reliability in the obtained results. By following these simulations for any alloy, the quality of the castings can be improved.

The recent development of new and advanced materials has led to industry experiments, innovation, and patents. As a result, various alloys were developed and implanted for multiple applications in the space, automobile, chemical, steel, and manufacturing industries. Cobalt- and nickel-based alloys have been designed to cater to high-temperature and oxidation-resistance alloys.

Here, various literature reviews are investigated, and the machining of Haynes-25 is done using an electrical discharge machine with an optimization technique of the L27 orthogonal selection of Taguchi. The controllable input procedure constraints are Pulse On time (Ton), Duty factor (Df), Current (I), Gap voltage (Vg), and Flushing pressure (Fp).

The performance characteristics output parameters considered are material removal rate, tool wear rate, and surface roughness values (Ra). Moreover, confirmation tests are conducted to determine the percentage error of the predicted model.

The confirmation tests and results showed that the duty factor and current greatly influence the M.R.R, E.W.R, and Ra machining performance. The optimized condition is obtained at the implementation of the confirmation test and using the level of significance, i.e., A3B2C3D3E3, which can be used for the patent with the value of M.R.R..R as 0.05702, E.W.R. of 0.0091, and Ra of 2.34. Furthermore, regression models are developed to predict the material removal rate, tool wear rate, and surface roughness.

It is suggested that industries use these optimum conditions to lessen unused material and raise the productivity of Haynes-25 Electrical Discharge Machining, which can be patented.

The findings of the study elucidated that as the porosity of copper foam diminished, the internal average temperature of the composite phase change material increased, concurrent with a reduction in the maximum average temperature differential and an enhancement in temperature homogeneity between the heating interface and the copper composite phase change material. Patent methods and models were applied to investigate this effect.

Under the filling rate of this experiment, the heat transfer mechanism of copper composite phase change materials (CPCMs) was mainly heat conduction.

With the increase of porosity, the melting time of phase change materials shortened, and the change of natural convection ratio was more obvious. At the same melting time, the porosity decreased, and the pressure drop increased.

When the porosity was 94% and 96%, the pressure drop was 1425.34 Pa/m and 1222.65 Pa/m, respectively, which was 37.01% and 17.53% higher than that when the porosity was 98%.

The main purpose of this research work is to examine the free vibration performance of a Smart Functionally Graded (SFG) porous composite beam having non-uniform porosity distribution (PD) with non-linear elastic moduli and mass density along the direction of thickness considering symmetric as well as asymmetric PD. This research work addresses the lack of literature regarding the analysis and the effect of variation of the slenderness Ratio (SR), Porosity Coefficient (PC), and Voltage levels on the free vibration properties of the SFG porous beam considering different boundary conditions and porosity distribution, which may lead to new patent applications in material design and vibration control.

The Smart Functionally Graded (SFG) porous beam is a Functionally Graded (FG) Porous beam integrated with the PZT-4 piezoelectric material on the top layer. The free vibration properties of the considered beam have been examined and analyzed using the ANSYS software.

The objectives of this work are:-

To analyze the impact of variations of voltage levels and slenderness ratios on the free vibration properties of the SFG beam.

To showcase the effect of variation in the porosity coefficient on the dimensionless fundamental frequencies of the SFG considering 4 boundary conditions at different porosity distributions and voltage levels.

The research work studies and analyzes the performance of the SFG porous beam considering the equations of Timoshenko beam theory. To simulate the results and analyze the various effects, the ANSYS software has been utilized in this paper.

Experimental data demonstrates that:

• (1) Among all 4 boundary conditions considered in this research work, C-C has the highest fundamental frequency while C-F gives the lowest value of fundamental frequency.
• (2) An increase in PC causes an increase in Dimensionless Fundamental Frequency (DFF) of SFG beams with PD1 whereas it decreases for beams with PD2.
• (3) As the SR of the beam increases, the DFF of the beams with both PD1 and PD2 decreases for both voltage levels V=20 V and V=100 V.
• (4) The natural frequency of the SFG beam increases as the voltage level is increased from 20 V to 100 V.

The free vibration of the SFG porous beam (made up of PZT-4 piezoelectric material) has been examined and analyzed using the ANSYS software. Various results were obtained from the simulation and these have been showcased in different Tables and Figures. The performance of the considered SFG porous beam has been investigated for 2 different Porosity Distributions (PD1 and PD2) by varying PC and SR.

This research work also analyzes the impact of variation of PC, voltage levels, and SR on the free vibration properties of the SFG beam.

In order to meet the requirements of high performance of centrifugal pump, the influence of the size and position of the impeller opening on the external characteristics of the pump was studied.

In recent years, patents and technologies have provided favorable conditions for the research of centrifugal pumps. The method of numerical simulation and experimental comparison was used to improve the performance of the high-speed TPE centrifugal pump by perforation of the impeller.

In the case of a large inlet void fraction, opening can improve the performance of high-speed centrifugal pump.

The pump performance is subject to two non-linearly related variables-the diameter of the hole and its radial position. In the process of affecting the pump efficiency, it is necessary to take into account their effects on the hydraulic loss and the gas volume distribution in the impeller to achieve the optimal balance.

Plasma spraying, a surface modification technology, was performed to deposit Inconel718 and CNT-reinforced Inconel718 coatings on T91 boiler steels. The coatings were expected to improve the corrosion resistance of boiler steels, thus extending their service life at high temperatures. The deposited coatings were characterized in terms of microstructure, porosity, microhardness, SEM, and EDAX.

Through this representative patent method, the deposited coatings brought about a considerable porosity reduction and had an impact on the microhardness. Moreover, it was observed that in Inconel718 coatings reinforced by CNTs, the carbon nanotubes were homogeneously distributed, increasing the uniformity of the coatings, as well as their strength. Additionally, the uniformity of the coating represents a testimony to its enhanced resistance to corrosion.

Based on the testing results, the thickness of the coating achieved was 215 ± 5 microns. The addition of CNTs to Inconel718 coatings had reduced the porosity of the coatings to 2.2% from 3.8% and improved the microhardness of the coatings to 968 Hv from 679 Hv. This further improved the corrosion protection of T91 boiler steels. A uniform distribution of CNTs throughout the coating matrix was observed.

Therefore, based on the analysis conducted, it possible to ascertain that the plasma-sprayed CNT-reinforced Inconel718 coatings have a veritable impact on promoting the corrosion resistance of boiler steels. It follows that such technology reduces the dormant functionality of boilers in industries and facilitates efficient service and industry development for a variety of industries.

Bone external fixation technology is an important therapeutic approach for limb correction, primarily involving a class of external fixation correction mechanisms. It has achieved good results in limb lengthening and correcting deformities to restore limb function. In clinical practice, existing correction mechanisms face challenges such as high resistance between components, complex installation procedures, and high precision requirements for installation, requiring manual adjustment by physicians, which limits precise control and quantification of correction parameters.

To address these issues, an automated correction bone external fixation robot was designed based on traditional Ilizarov external fixation devices (TIEFD).

By increasing the number of unidirectional hinge connections, the robot can effectively reduce motion resistance. Subsequently, the robot was combined with the tibia for correction motion simulation, obtaining the motion parameters θ of the deformed bones during the correction process based on the trajectory of the tibia's point mass. Finally, correction motion experiments and finite element analysis (FEA) were conducted on the robot combined with a control system.

The results showed that the robot could precisely control correction parameters, with the error range for rotational correction not exceeding 0.5 radians and the error range for traction correction not exceeding 0.2 mm. FAE, based on corrective force data, concluded that compared to (TIEFD), the robot could reduce bone stress by 16 MPa during the correction process.

The robot effectively reduces patient discomfort, this provides a reliable theoretical basis for bone external fixation technology and holds positive significance for the treatment of skeletal deformities. The application of patent-worthy robotic design represents a forward step in orthopedic corrective systems.

The electricity demand is continuously increasing. However, various institutions, enterprises, and individuals exhibit many irregularities in their electricity usage, leading to significant wastage of electricity. To achieve effective energy management, researchers are attempting to analyze and regulate users' electricity demands by monitoring their load usage through Non-Intrusive Load Monitoring (NILM) technology. The accuracy of load identification in this technology will greatly impact the results of load monitoring. Although there are currently many articles and patents related to NILM, they utilize a large amount of computational resources and require high sampling rates from devices, yet the results are still unsatisfactory. Therefore, it is necessary to improve the accuracy of load identification in data with relatively low sampling frequencies.

To improve the accuracy of load identification with low sampling frequency data, this paper proposes a typical scenario load identification method based on feature fusion and transfer learning.

This method adopts the fusion of current and power factor angles to provide abundant identification information for NILM, effectively reducing the situation of single-feature overlap of different loads. By inputting the fused feature data into GoogLeNet and utilizing transfer learning for training, not only is the accuracy improved, but also the training time and the requirement for the sampling rate of training data are greatly reduced. In addition, selecting typical scenario loads can monitor loads in a targeted manner, reduce the waste of computing resources caused by irrelevant loads, and more effectively guide electricity usage strategies.

The proposed load identification method was tested on the low sampling frequency dataset used in this paper. It achieved an overall load identification accuracy of 94.61% across three scenarios, improving accuracy by 3% to 7% compared to other models.

The simulation results indicate that this method achieves high load identification accuracy at low sampling frequencies. It also exhibits good generalization ability. This method not only reduces the performance requirements for monitoring equipment but also enhances monitoring efficiency.