International Journal of Precision Engineering and Manufacturing最新文献

This paper proposes a method for quick recognition of jigsaw puzzles using a small number of samples, solely relying on image processing and template matching techniques. In the preliminary stage, this paper proposes a segmentation approach to divide the jigsaw puzzle into individual pieces with partial features, obtaining template data for each puzzle piece. Subsequently, scattered puzzle pieces are captured using a camera, and their contours are extracted to acquire puzzle image data. The puzzle images are then matched with the template data, employing polar coordinate transformation during the matching process to reduce computational time. The matching process also identifies the puzzle piece's number and orientation. Finally, the matching results are integrated with a robotic arm to complete the task of puzzle assembly. This paper not only outlines the generation of puzzle image data and template data through image processing but also elaborates on the determination of corresponding numbers and orientations during image matching. The feasibility of this method is validated through different types of puzzles, and its applicability to industrial parts is also examined for practicality.

The cold rolling mills are complex electro-hydro-mechanical systems in which vibrations are usually detected as issues during production process. In the present work, the vibrations with frequencies of 80Hz were found at top of the rolling mill and the pressure behind servo valve during the production process. In order to understand the vibration mechanism and to explore the measurements for vibration suppression, the dynamic models were proposed to describe valve spool, 8-DOF cold rolling mill, and hydraulic system based on the dynamic characteristics of servo-valve. The analytical solutions and numerical solutions were obtained for the vibration rules for the valve spool displacement and the output flow rate under different working conditions. Moreover, the influence of dynamic characteristics of servo-valve on the vibrations and optimization of the servo-valve were discussed. The results suggest that the dynamic characteristics of servo-valve have a significant influence on the hydro-mechanical coupled vibration of rolling mill and the vibrations can be dampened by improving the dynamic characteristics of rolling mill. This work is expected to provide a new perspective to suppress the hydro-mechanical coupled vibrations.

Large-size parts such as aircraft wing structures require a lot of hole machining for assembly between parts. As demand for hole positional accuracy, such as in determinant assembly (DA) concept, securing the positional accuracy of hole machining is becoming more important. Specifically, during the hole machining of large-size parts, significant errors occur due to thermal expansion according to temperature change of a machine tool and a workpiece. In this study, a technique for efficiently reducing the positional error of hole machining in large-size parts is proposed by compensating geometric errors and thermal errors of a machine tool and a workpiece. The thermal displacement error, representing changes in volume error due to temperature variations in the machine tool, is estimated by measuring the distance between the centers of two spheres on the master with low thermal expansion coefficient measured at the reference temperature (20 °C). The thermal expansion error, caused by variations in workpiece temperature, is estimated by assuming the temperature of the workpiece to be that of the cutting fluid just before machining. Hole machining errors are integrally compensated by considering the geometric error measured at the reference temperature and the thermal errors of the machine tool and the workpiece. In the verification experiment, the maximum error was improved by 60.2%, and it was confirmed that the tendency of the error was significantly reduced.

The constraint level of TKR is essential for ensuring product performance to prevent knee joint dislocation. Computer modeling and simulation (CM&S) technology is widely used in the medical device industry due to its advantages such as reducing testing time and costs. However, there is a lack of research on the constraint level of TKR according to the size and flexion angle of the femoral component. In this study, the constraint levels of AP draw, ML shear, and rotary laxity were tested according to the size and flexion angle of TKR products using finite element analysis. A TKR model was constructed using a 3D scanner, and a finite element model with mechanical testing and error rates of 2.49% and 3.00% was developed through AP draw testing. In AP draw, as the size of TKR decreases, the constraint level increases by about 3.6%, and rotary laxity also increases by about 1.3%. In all tests, the constraint level increased as the bending angle of the femoral component increased. We found that the curvature and contact area of a TKR influenced the constraint level. Through this study, it is believed that CM&S technolaogy can be widely used in evaluating the unique performance of medical devices.

The pipe belt conveyor is one of the most important bulk material transportation equipment in the world nowadays, which has great advantages compared with traditional belt conveyor and meets the requirements and concepts of green and sustainable development advocated by the society. This paper aims to solve the problem of transition segment of the pipe belt conveyor. By analyzing the forming mechanism of the transition segment conveyor belt, the theoretical maximum position of additional deformation and additional stress in the transition segment of the pipe belt conveyor is obtained, and a 3D simulation model of the transition segment of the pipe belt conveyor is established. Using the finite element analysis method, the model is subjected to mechanical finite element simulation analysis to obtain the equivalent elastic deformation and equivalent stresses under different scenarios. In this paper, mathematical modeling was used to estimate the curves of the main influencing factors and multiple linear regression analysis, and finally, the reliability of the model was mathematically verified and analyzed. It provides a certain reference for solving the practical problems of the transition segment of the pipe belt conveyor and provides a theoretical basis for the design of the pipe belt conveyor.

This study introduces a non-invasive approach to monitor operation and productivity of a legacy pipe bending machine in real-time based on a lightweight convolutional neural network (CNN) model and internal sound as input data. Various sensors were deployed to determine the optimal sensor type and placement, and labels for training and testing the CNN model were generated through the meticulous collection of sound data in conjunction with webcam videos. The CNN model, which was optimized through hyperparameter tuning via grid search and utilized feature extraction using Log-Mel spectrogram, demonstrated notable prediction accuracies in the test. However, when applied in a real-world manufacturing scenario, the model encountered a significant number of errors in predicting productivity. To navigate through this challenge and enhance the predictive accuracy of the system, a buffer algorithm using the inferences of CNN models was proposed. This algorithm employs a queuing method for continuous sound monitoring securing robust predictions, refines the interpretation of the CNN model inferences, and enhances prediction outcomes in actual implementation where accuracy of monitoring productivity information is crucial. The proposed lightweight CNN model alongside the buffer algorithm was successfully deployed on an edge computer, enabling real-time remote monitoring.

For achieving high precision and effectiveness in five-axis computer numerical control (CNC) machine tools, the geometrical accuracy of the rotary axes is a crucial performance criterion. Furthermore, recent advancements in commercial CNCs for machine tools have enabled the numerical compensation for all parameters of geometric errors within rotary axes. As a result, this paper initially delves into the evolution of ISO standards concerning the accuracy testing and error definition in machine tools. Subsequently, the classifications of the rotary axis’s geometric errors in five-axis machine tools are described in this paper. Moreover, this paper comprehensively reviews various measurement schemes aimed at identifying the geometric errors of rotary axes. These measurement schemes are categorized based on the measurement instruments or technologies employed. Finally, it is essential to emphasize that this paper offers an overview of diverse measurement theories and technologies pertaining to geometric errors in rotary axes. The primary aim is to contribute to the progression of geometric error measurement and compensation in five-axis machine tools.

Generally, when two surfaces in contact move relative to each other, friction, wear, and lubrication occur. One of the methods for changing the characteristics of two surfaces in relative motion is to process a pattern on a surface; this method is referred to as surface texturing. Studies have used various approaches to identify friction characteristics through patterns. However, relatively insufficient research has been conducted on array of patterns. As the pressure of surface lubricants can vary depending on the arrangements of patterns, it is necessary to understand the friction characteristics with respect to the arrangements. In this study, the friction effect according to the shape and arrangement of the pattern was evaluated through friction experiment that takes into account the slope effect and the asperity contact, and proposed and executed a new method for the lubrication analysis of the rough surfaces. The patterns and roughness were produced by laser processing and particle jetting (AAJ) of the experimental specimens and friction experiments were performed with the fabricated specimens. The new lubrication analysis was performed for the four types of patterns (Reference surface, X-direction-line groove, X-direction-line + zigzag groove, X-direction-zigzag + line groove). The validity of the analysis was verified by comparing the results from the experiment and analysis under the same pattern and friction conditions. The results from the friction experiment and lubrication analysis showed a similar tendency to that of the friction coefficient. As a result of the lubrication analysis, it was found that the friction characteristics according to the arrangement of the pattern may have greater or smaller friction compared to the reference surface when considering the influence of the slope. Although it did not appear clearly in the experiment due to limitations in the experimental conditions, it was confirmed that the lubrication analysis and experimental results were similar. As a result of analyzing the friction phenomenon appearing from the application of various arrangement of patterns considering asperity contact, it was possible to identify an effective pattern arrangement for reducing friction.

Machining hard materials, such as tool steel and tungsten carbide, involves high cutting forces and temperatures that lead to severe tool wear. Frequent tool changes owing to tool wear increase costs and decrease productivity, degrading the surface quality and accuracy of machined parts. Various studies have explored approaches to reduce tool wear in the machining of hard materials, such as micropatterns on the rake face of cutting tools, ultrasonic elliptical vibration cutting, and built-up-edge at the end of the tool. However, limited research has been conducted on the microstructures and patterns of the built-up edges. This study proposes a methodology to stabilize the built-up edge at the end of a tool with microstructures and patterns. The chip morphology and behavior were simulated using FEM software to determine the machining conditions and microstructure required to maintain a constant built-up edge at the tool tip. Several microstructures were machined at the edge of the cutting tool, and orthogonal cutting experiments were conducted to validate the simulation. Additionally, tool wear was evaluated for the tool structure and machining conditions.

The aim of this study was to investigate gender differences in the biomechanics of lower limb joints during stair ascent, focusing on the distribution of joint loads. Thirty-six young subjects (18 males and 18 females) ascended instrumented stairs while kinematic and kinetic data were measured. Mechanical variables of the lower limb joints and body posture on the sagittal plane were compared between genders, and their associations were also investigated. Female subjects exerted more mechanical work, power, and joint moment than male subjects at the knee joint, while males exerted more at the hip joint. Females and males showed a longer moment arm of ground reaction force at the knee and hip joints, respectively. The moment arm, but not the magnitude, of ground reaction force was strongly associated with the joint moment (r = 0.80–0.97). Females exhibited a more crouched stance limb (lower heel lift, greater ankle dorsiflexion, and knee flexion) than males. A more crouched and extended lower limb posture was found to be correlated with a longer moment arm at the knee and hip joints, respectively. Half of the variance in moment arm could be explained by the heel lift angle. The results indicate that females allocate greater work to the knee joint but less to the hip joint than males do in order to elevate body mass to a higher step during stair ascent. The work distribution strategy appears to be influenced significantly by posture, particularly the choice of foot contact method: heel-toe standing in females and toe standing in males.