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ŠKODA VÝZKUM s.r.o. (now Výzkumný a zkušební ústav Plzeň s.r.o.) cooperated on the development of the NEOPLAN DMA low-floor articulated trolleybus intended for the Boston city (the United States). Multibody models and finite element models of the trolleybus were utilized in the stage of the vehicle design. The multibody models of the trolleybus were created in the Alaska simulation tool and the simulations (running over a large road unevenness, start, braking and driving through a bend) were aimed at determining forces acting in the trolleybus suspension elements and radius rods. Time histories of the forces calculated using multibody models were used as the input data of the trolleybus finite element models. Utilizing the finite element models the critical places of the trolleybus body structure from the point of view of high stresses were determined. At the measurement with the real trolleybus prototype these places were provided with strain gauges.

In this paper, the electric discharge perforation technology is used to preset surface texture, which effectively suppresses the generation of large cutting forces in the hard cutting process, avoids the aggravation of tool wear, and improves the service life of the tool. Use CBN tools to hard-cut GCr15 hardened steel, design three-factor non-textured orthogonal cutting simulation and experiment about cutting depth, cutting speed, and feed rate, and use range, variance and signal-to-noise ratio methods to simulate and experiment data is analyzed to determine the best combination of cutting parameters and the degree of influence of each parameter on the cutting force generated in the hard cutting process. Use the best combination of cutting parameters to hard-cut GCr15 hardened steel with a preset surface texture, observe the tool wear, measure the cutting force, compare and analyze the results under the same cutting conditions without texture to verify the preset surface texture can effectively reduce tool wear and increase tool life.

This paper describes experimental measurements of travel rollers on a polyurethane thread. This exper-iment took place at the CTU Faculty of Mechanical Engineering in the laboratory of the Department of Design and Machine Parts. The experiment was performed within the project of a lightweight type of sampler, designed by a team of collaborators from our institute for OK Servis BioPro, s.r.o. For the new-ly designed type of sampler, it was necessary to determine the operation of a newly designed grain sampler. The load of the rollers is different in each environment. This paper presents the average values from the measurement, including its evaluation. Moreover, the paper compares different temperatures that can be achieved in the practice. Negative temperature values were not performed, as this meas-urement would be expensive and inefficient.

The study is focused on the dynamic response of the head and thoracic area of an anthropomorphic test device (ATD) during low-impact collisions with a tram. Two collision scenarios were analyzed: the frontal impact (a chest as a primary contact area) and the side impact (a thigh as a primary contact area). The measurements used a pedestrian dummy (Hybrid III 50th percentile male dummy, Jasti Co., ltd., Tokyo, Japan) and a unique pendulum impact testing machine (impactor) of own design. The crash tests were conducted at various impact intensities (velocities) into the chest and left thigh of the dummy. The primary outcome variable was a resultant magnitude of acceleration measured in the area of thoracic vertebra Th5 and on the vertex of the head. The differences between both areas of interest were analyzed as well. The results provide the analysis of the dynamic behavior of the head and chest of the dummy at low impacts, the validation of the impactor for crash-test analyses, and a possible way to verify the use of the dummy in similar experimental settings.

Article deals with design of welding jig for assembly of wind power plant component. Mainstay of article is design of welding jig, which makes exactly setting and reliable clamping of individual parts of welded desing possible for their complete welding. Design procedure of individual parts of welding jig is described in details in view of their functionality. Paper is especially focused on the parts of welding jig, which are necessary to make, including material selection of individual parts. Finally the technical and economic evaluation is carried out, approximate cost of jig is calculated and financial savings associated with practical use of welding jig are evaluated.

High deposition rate with minimal heat input is one of the primary emphases in wire arc additive manufacturing. This study aims to determine the optimal input parameters of micro plasma welding for single-layer deposition. The stability of a single layer is crucial as it serves as the foundation relative to the deposition of layers to avoid a discontinuous multi-layer material. The study focuses on wire feeding speed, welding speed, and pulse and their interaction between the input and response variables. Based on the study, the regression equation between the three key parameters and the response using the Box-Behnken Design response surface methodology was proposed. The outcome demonstrates that the op-timized sample deposition produces a smooth surface appearance with no apparent defects.

This article deals with unconventional materials usage in design of vehicle bodies. Main focus is on sandwich materials (with honeycomb structure) for walls of the main body. These panels are designed from polypropylene. Joining of theses sandwich panels is also solved here by special aluminium profile. Virtual simulations and stress evaluation are used methods for design evaluating. Research is focused also on material properties testing. Tested are sandwich materials and also connecting aluminium profiles. All material properties and testing principles are here clearly described. Lower weight of vehicle body leads to possibility of floor optimization. Welded frame of floor can be lighter and strength of floor is also evaluated here. All these steps lead to lighter design with economic benefits for producer.

There are a number of methods for measuring propeller pitch but it could be a problem for many fishing boat builders who lack of professional equipment. This paper presents a method of propeller pitch measuring based on photogrammetry and CAD (Computer Aided Design). This method con-sists of three stages. At first, a series of photos of the propeller were taken by a smart phone. After that, these 2D images were processed by a photogrammetry software to create the 3D virtual model of the propeller. Finally, in CAD environment, the pitch at different radii of each blade of the 3D vir-tual model were measured. To validate the proposed method, several propellers for fishing boats were measured and the measuring results were compared to those archived by using an EDM (Electrical Discharge Machining) machine and by a highly skilled man with simple tools. The measurement results show that the proposed method could be acceptable for measuring pitches of propellers of fishing boats.

The issue of accident analysis in relation to railway vehicles of urban mass transportation is highly accentuated at the moment. In terms of designing the frontal area of trams, adequate attention should be paid to the optimal front end design in order to reduce the risk of pedestrian injury. The properly used shape and materials can minimize the consequences of the pedestrian’s contact with the vehicle, or the eventual dragging of the pedestrian under the vehicle. For the front end to be tested and optimized, it is necessary to develop and validate a pedestrian model for performing calculations even in the design preparation stage. From a historical perspective, impact tests and pedestrian protection were not paid significant attention. There should also be a methodology for data collection and evaluation across the public transit company. The data collected within the Czech Republic is inconsistent and hard to analyze. At the beginning of our research, we addressed the question of which dummy configuration with respect to the tram is most appropriate for our crash tests.

This paper proposes a solution not previously used in the forging industry, which aims to reduce the proportion of arduous human labour. The concept of a prototype robotic station for hot forging includes a system that allows the selection of batch material with its heating, the execution of the process of lu-brication of forging tools and the forging itself, synchronised with the feeding and removal of material using full automation, in accordance with the idea of Industry 4.0. At the same time, by increasing the repeatability of the entire forging process and changing some of its key parameters, it will be possible to influence the durability of the tools used during its implementation. In order to verify the impact of such a modified technological process on forging tool life, computer simulations of forging were performed, where the currently applied technology using hand forging was compared with a conceptual automated process.

Composite materials have consistently been applied in areas where a combination of properties such as strength, stiffness, and low weight is crucial. Motorcycle construction is no exception, as these parameters significantly impact riding characteristics, safety, and overall performance. This article focuses on quantifying the torsional and vertical stiffness of a single-sided swingarm made of carbon fiber reinforced polymer (CFRP) using finite element analysis (FEA) and verifying these results through experimental measurements. To enhance the accuracy of the simulations, which involve complex geometries and anisotropic materials, the material properties of selected fabrics used in the prototype production were measured. Specific fixtures were designed for the experimental measurements, enabling the application of torsional moments and vertical forces. Deformation under these loads was evaluated using the TRITOP photogrammetric system, which tracks deformations by monitoring the displacement of reference points under static load conditions and comparing them to a reference, unloaded state. Based on the acquired data, the overall stiffness values and their distribution along the length of the swingarm were calculated. The results showed a significant difference between simulation and reality. For the overall torsional stiffness, the simulated value was 249 N·m/°, while the measured was 270 N·m/°, showing a discrepancy of 7.7%. The vertical stiffness value from simulation was 414 N/mm, compared to 411 N/mm from experimental measurements, with a minimal difference of -0.7%. The stiffness distribution along the length of the swingarm exhibited a correlation, but with notable variation in certain areas. This confirms that accurately simulating CFRP parts with complex geometries is highly challenging, partly due to the sensitivity of the manufacturing process. Therefore, verification through experimental measurement is considered good practice.

As part of my research work, in its practical part, I deal with the selection of suitable 3D printing pa-rameters for parts of a robotic kit, as well as the selection of a 3D printer and the determination of a set of experimental measurements and testing in order to obtain the necessary data to determine a suitable filament material for 3D printing of a part of a robotic kit and setting the appropriate 3D printing parameters to obtain the desired mechanical properties of the parts while maintaining the economic benefits of 3D printing. The main aspects for choosing a filament material are printability in primary and secondary school conditions, easy printing (beginner level), minimal postprocessing, adequate mechanical properties – these are obtained by experimental measurement and correspon-ding destructive tests on a real part from the VEX GO and IQ kit.

Workpiece fabrication of titanium alloy is widely used in several high-end fields. In this study, finite element analysis of titanium alloy turning process is carried out and the turning process is modeled by using material properties and intrinsic equations. Then the power transmission of centerless lathe is controlled in the machining process, so as to obtain the performance calculation of different process parameters on cutting force, chips, and residual stress. The analysis of the simulation and experimental data yielded that when the tool travel speed was 1 m/min, the radial force increased to a maximum value of 150N. When the depth of cut was 0.3mm, the radial force was 151N and then increased to 200N. In the comparison of the simulation results, it was concluded that the depth of cut was 0.3mm, the minimum error value was 7.43%. In the quality analysis, the optimum parameters for travel speed and depth of cut were 1.0 m/min and 0.2mm respectively. When the spindle speed was 480 r/min, the roughness of the machined surface of titanium alloy was closer to the simulation results, and the lowest difference was 0.1 μm. Therefore, the finite element machining model of titanium alloy turning proposed by the study could effectively improve the machining quality and accuracy, and it has superiority. In the future machining and parts manufacturing, it can improve the processing efficiency and promote the optimization of titanium alloy material properties.

In the automotive sector, poroelastic materials (PEMs) are used as trim elements to achieve the desired interior acoustics of a vehicle. This study examines the effect of manufacturing as well as measurement techniques on airflow resistivity. This property plays a key role in the acoustic behavior of PEMs. First, the importance of engineering acoustics and poroelastic materials in vehicle industry is reviewed, followed by the introduction of the most important properties and their measurement techniques. Next, the theory and the measurement techniques used to determine resistivity via direct method are detailed. Then the factors influencing the results and their quantified effects are presented. More than 10 influencing factors are identified and examined, from which the inhomogeneity, resulting from the production technology proved to be the most significant. The results obtained with direct and inverse methods are compared for validation purposes and to determine the achievable accuracy of the inverse method. The average difference between the two methods is 4.54%, which means that the inverse method can provide a good approximation. Finally, conclusions are drawn and suggestions are made for the future.

In order to reduce the production cost of nano titanium based functional materials, a production cost control method of nano titanium based functional materials based on DMAIC is proposed in this paper. The DMAIC (Define, Measure, Analyze, Improve, Control) model was used to analyze the production of nanoTi-based functional materials and define the main factors affecting the production cost of nanoTi-based functional materials. The indicators for measuring the quali. The regression model was established to determine the main factors affecting the rod content and yield of nanoTi-based functional materials. The appropriate experiments were used to determine the best control conditions and to improve the technical parameters. Through the control methods of monitoring, coordination and improvement, the phased results are consolidated and improved. The experimental results show that the quality and yield of nanoTi-based functional materials are significantly im-proved after using this method, and the cost reduction of each production link is also significantly higher than that of the comparison method.

Motor rehabilitation contributes to neural remodeling in individuals with motor disabilities, which is crucial for their recovery of motor ability. In addressing the No. of human-machine coupling and synergistic motion characteristics in motor rehabilitation, this study analyzes the collaborative motion characteristics of each joint in the lower limbs. A virtual human-machine coupling system is proposed, and the driving functions of the human-machine coupling system are designed. By utilizing ADAMS motion simulation software, the motion characteristics of the human-machine system are analyzed, and the variation patterns of motion parameters at key positions are obtained. Based on this, the system's synergy is analyzed and experimentally validated from the perspectives of gait, motion speed, and joint motion angles. The experimental results demonstrate that the hip and knee joint angles of the exoskeleton robot exhibit a motion pattern highly consistent with that of the human body, with an angle error of less than 3°,indicating excellent synergy.

The present paper is focused on the study of the characteristics of selected titanium alloys before and after heat treatment. The specimens were cooled both in water and liquid nitrogen from 900°C and 1000°C for pure titanium and from 1000°C and 1100°C for the Ti-6Al-4V alloy. Further, the paper deals with line MG63 live bone cells deposited on a titanium base substrate. Proliferation and differentiation are monitored of cells during 7-day in vitro cultivation portraying growth of cells on a biologically selected material.

Currently, there is a demand in the aerospace industry for a more effective and non-invasive milling technique for powder metallurgy γ-TiAl alloy. The primary objective of this research is to examine the surface milling process of a γ-TiAl alloy generated by powder metallurgy. The primary objective of this study is to examine the impact of process parameters on the surface roughness and cutting force of the alloy, with the aim of optimizing both surface roughness and cutting force. The response surface method was implemented to examine the milling process, and the NSGA II algorithm was employed to optimise surface roughness, cutting force, and material removal rate. The findings indicate that the cutting depth exerts a significant impact on both the surface morphology and surface roughness. The available data indicates a clear correlation between the depth of cutting and the rate of feed, as well as the resulting assessment of surface roughness. Nevertheless, the first rise in spindle speed is associated with a subsequent increase in surface roughness, followed by a subsequent drop of a lesser magnitude. A minimal threshold for surface roughness has been established at 0.203μm. The spindle speed exerts the primary impact on the cutting force. There exists a positive link between the cutting force value and both the cutting depth and feed speed, as the cutting force value has a positive correlation with the incremental changes in these variables. Nevertheless, the relationship between cutting force and the observed trend is non-linear, exhibiting an initial decrease followed by a rise when cutting force is augmented. The minimal cutting force necessary was quantified as 112.3 N. Subsequently, a regression analysis was employed to develop a correlation model between surface roughness and cutting force. and machining parameters. The confirmation of the coefficients' validity in the model was achieved via the utilisation of analysis of variance (ANOVA) and residual analysis. The main goal of developing a machining parameter optimisation model is to limit surface roughness and cutting force, thereby improving operational efficiency. The NSGA-II method is utilised to tackle the problem of multi-objective optimisation, leading to the attainment of the optimal parameter solution. The purpose of the verification test is to evaluate the precision of the forecasts generated by the optimised model. The work holds importance in its analysis and juxtaposition of diverse processing factors, alongside the use of multi-objective optimization methodologies.

The study examines the effect of various post-processing heat treatments on the microstructural evolution and hardness of the AlSi10Mg alloy produced by selective laser melting (SLM). The alloy was examined in the as-built (AB) condition and after three heat treatment regimes: direct aging (DA, 160°C/5 h), stress relieving (SR, 300°C/2 h), and solution annealing followed by artificial aging (SA, 520°C/2 h + 170°C/4 h) to better understand the solidification and consolidation processes. A multiscale characterization using OM, SEM, EBSD, TEM, and EDS was performed to reveal the changes in specific microstructures due to additive manufacturing and different levels of heat treatment. The AB state exhibited a fine cellular network of Si within an α-Al matrix, and high hardness (approx. 138 HV1). The DA treatment preserved cellular morphology with mild coarsening, whereas SR led to partial fragmentation of the Si network and a significant drop in hardness (approx. 83 HV1). The SA condition caused recrystallization, Si spheroidization, and formation of Mg- and Fe-rich precipitates, accompanied by moderate hardness recovery (approx. 104 HV1). The persistent crystallographic texture was confirmed across all states.

Monitoring and diagnostics of cutting tools are crucial for ensuring production efficiency and product quality in the machining industry. This study uses acoustic emission (AE) to non-invasively detect damage and monitor tool condition in real time. Experiments assessed cutting inserts in a milling head, both used and new. Results showed AE effectively diagnoses tool wear, with significant differences in signals from worn and new inserts. Fast Fourier Transform (FFT) analysis determined the frequency range of signals during machining, confirming AE's usefulness. Microscope verification supported the AE findings on tool wear. This research highlights AE's potential in non-destructive diagnostics, enhancing production efficiency and product quality

The aim of this study is to investigate the effect of oscillatory loading frequency on the dynamic-mechanical properties of 3D printed thermoplastics, namely acrylonitrile-butadiene-styrene (ABS), glycol-modified polyethylene terephthalate (PETG), and polylactide, also known as polylactic acid (PLA). The investigated samples were manufactured using fused filament fabrication (FFF) technology and tested at different oscillation frequencies (1, 5, 10, 15 and 20 Hz). Dynamic mechanical analysis (DMA) demonstrated that an increase in the oscillation frequency causes an increase in the glass transition temperature (Tg) for all analyzed materials, while in the case of the used loading frequencies above 5 Hz, an almost linear dependence between the magnitude of the applied frequency and Tg was observed. The findings also show that with increasing frequency of mechanical loading, there are changes in the visco-elastic properties of the investigated polymers, specifically in the value of the storage modulus (E′), loss modulus (E′′) and loss angle (tan δ), which points to the complex behavior of the materials under dynamic conditions. The results of this study provide valuable insights for the use of 3D printed polymer materials in applications where they are exposed to dynamic stress - in the automotive or aerospace industries.

The topic of this paper is the application of machine learning and neural networks in engineering, specifically in the prediction of the lifetime of bearings operating in different conditions. In addition, the basics of machine learning are introduced, giving an idea of the importance of input data quality for model training. It also presents the elements of neural network training to be used in other projects. The article is supplemented by a source code examples written using only the Python language, and some other popular libraries, like the NumPy, Matplotlib, Tensorflow, Keras, and Scikit-learn. The main advantage of the libraries used is that they are freely available and widely used, bringing variety of sophisticated tools for gen-eral use.

The materials used in VVER nuclear power plants are subject to thermal ageing in operation, among other degradation mechanisms. The aim of the experiment was to verify the effect of thermal ageing on the change of ultrasound velocity on the extracted parts of main circulation piping and pressurizer surge line made of austenitic steels. Two steel conditions were evaluated, as received and thermally aged. The research was carried out on samples made from non-operated pipelines and samples from pipelines after 28 years of operation. The samples were subjected to thermal ageing at 450 °C in an atmospheric furnace with a specified exposure time to simulate extended operation of the compo-nent for 60 years, where 1 year of operation means 10 months at 100 %-unit power and 2 months in shutdown. The samples were subjected to ultrasonic property measurements and the longitudinal and transverse wave velocities obtained are further used to calculate the Poisson's constant and elastic modulus E of the material. To verify the ultrasonic measurements, the samples were also subjected to mechanical tests to verify the changes in the mechanical properties in terms of elastic behaviour of the selected steels when subjected to a static 3-point flexural test and Electron backscatter diffraction analysis (EBSD).

The Ti-6Al-4V alloy is widely used as a material for medical implants. In the future, it may be employed for 3D printing using the selective laser melting method. The advantages of 3D printing are for example production of complex shapes or ability to create customized implants. One of the disadvantages of this method is the deterioration of mechanical properties, particularly the ductility of the alloy, caused by high residual stress resulting from rapid cooling during printing. This article aims to characterize the microstructure and defects of the printed alloy and the impact of hot isostatic pressing. Optical microscopy, scanning electron microscopy, and micro-computed tomography were utilized for the study. It was found that the heat treatment has a significant effect on the pore size and microstructural transformation. These findings could lead to the optimization of the manufacturing process and improve the quality of implants made from this alloy.

Recently, engineering polymers like PMMA have increasingly replaced traditional materials in industry where feasible, with CO2 laser cutting gaining attention for its high quality and speed in processing these materials. Achieving precise cuts is crucial for product accuracy, with kerf width serving as a key quality attribute to ensure quality and functionality of the final product. This study focuses on the im-pact of three critical process variables: stand-off distance, laser power, and cutting speed, on the kerf width in CO2 laser cutting of PMMA. Through a full-factorial experiment, the process parameters are systematically varied to understand their individual and interaction effects on the cutting process. The kerf width is measured as an indicator of precision using an optical microscope to evaluate the quality of the laser cuts. To address the non-linear relationships between these process parameters and kerf width, several machine learning models were utilized. Performance comparisons indicated that the Artificial Neural Network (ANN) model provided the highest accuracy, with R² values of 0.98 for the validation dataset and 0.95 for the testing dataset. The optimized ANN model offers a robust tool for parameter optimization, facilitating the determination of optimal settings to achieve the desired kerf width while ensuring productivity.

This study proposes a multi-stage intelligent diagnostic approach integrating Physics-Guided Normalization (LPGN), enhanced Transformer networks, and Gaussian Mixture Models (GMM) for thermal fault detection in turbine generator stators. The methodology sequentially performs the following steps: (1) enhances localized anomaly features in temperature data through LPGN, (2) efficiently extracts temporal patterns via the optimized Transformer architecture, and (3) achieves unsupervised fault classification using GMM. Experimental results demonstrate the proposed method's superiority over conventional ARIMA and LSTM models across multiple evaluation metrics, exhibiting a lower RMSE and a higher detection accuracy. Ablation studies further validate the individual contributions of each component to performance improvement. This solution provides an efficient and reliable framework for intelligent thermal monitoring in large rotating electrical machinery.

In this study, binary zinc-based alloys (Zn–1Mg, Zn–1Li, Zn–2Mn, wt.%) were synthesized by performing mechanical alloying (MA) of elemental powders, followed by consolidation using spark plasma sintering (SPS). The processing parameters were optimized to obtain homogeneous powders with controlled particle size. X-ray diffraction and SEM analyses confirmed the presence of secondary intermetallic phases (Mg2Zn11, Zn13Mn, ZnLi2 phases) formed during milling, which were preserved after SPS. Microstructural examination revealed a fine-grained microstructure with residual oxide networks originating from powder surfaces. Mechanical testing demonstrated significant strengthening effects after Mg and Li additions, with Zn–1Mg alloy reaching the highest hardness (128 HV1) and compressive strength (526.7 MPa), attributed to uniformly distributed Mg2Zn11 precipitates. However, this strengthening was accompanied by reduced ductility. Zn–1Li exhibited the most balanced combination of strength and plasticity, while Zn–2Mn provided only a limited improvement over pure zinc. These results confirm that mechanical alloying combined with SPS is a promising route for developing biodegradable Zn-based biomaterials with enhanced properties.

The electrochemical discharge machining (ECDM) process is developing into a potentially useful method of performing micromachining in conductive or non-conductive materials. The materials are machined using a combination of chemical and thermal energy. This paper examines the effect of Artificial Neural Network (ANN) architectures combined with particle swarm optimization (PSO) on the predictive ability of tungsten carbide machining. Material removal rate (MRR) and surface roughness (SR) is the response used to evaluate the performance of the ECDM process. The four selected process parameters are voltage, gap width, electrode type, and type of electrolyte, with each parameter has two levels. The 4-9-1 structure was chosen to obtain pre-dictions in the form of an optimal formula based on the statistical values for surface roughness: MSE 0.001, RMSE 0.025, MAPE 1.36, and R2 0.99.

Biodegradable zinc-based alloys have recently attracted attention as promising candidates for temporary implant applications due to their favourable corrosion behaviour and biocompatibility. In this study, three materials — pure Zn, Zn–1Mg alloy, and a Zn + Zn–1Mg composite — were fabricated via powder metallurgy and extrusion to evaluate their microstructural characteristics and tensile performance. The composite material was designed to combine ductile Zn regions with a reinforcing Zn–1Mg network, aiming to achieve a balance of strength and ductility. Microstructural analysis revealed coarse-grained Zn regions surrounded by ultrafine-grained Zn–1Mg areas containing Mg₂Zn₁₁ particles, with oxide shells present at the Zn/Zn–1Mg interfaces. Tensile testing showed improvement in mechanical performance compared to the individual constituents. However, the oxide shells prevented effective load transfer between the fine-grained and coarse-grained areas of the microstructure.

This paper proposes a set of stable auxiliary positioning modules for die-cutting shoe material by means of image-based die-cut calibration. Used in combination with a self-developed polygonal-object packing system for shoe-material cutting, the punching machine tool can automatically cut accurately, stably, and efficiently with the highly integrated hardware and software. In particular, the packing of the shoe material is based on the contour of the die-cut mold vector, and the object-dilation method is used to maintain a fixed gap between the objects. Then, a search method is employed to calculate a compact packing of the die-cut contours. The center point and azimuth angle of the die-cut contours are determined through object packing by a heuristic search. The contours of this die-cut are projected directly onto the positioning module. The physical die-cut mold is aligned with the images, and then the die-bar is locked to complete the die positioning, which is synchronized with the packing system. This new die-cut calibration method is more accurate and reliable. Moreover, the error in the gap between the material and the die-cut was ±0.1 mm, which is in line with the development trend of automatic precision die-cutting.