Advances in Manufacturing

Insight into deformation allocation in the multi-pass roll forming of a double-walled brazed tube

Meng-Meng Liu, Yu-Li Liu, Heng Li

2023, 11(4): 567-586. doi:10.1007/s40436-023-00448-y

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Deformation allocation is an important factor that affects 720° curling forming from copper-coated steel strips to double-walled brazed tubes (DWBTs). In this study, four schemes of deformation allocation, considering different weights of the total feed distance, are proposed, and a 3D finite element (FE) model of the multi-pass roll forming process for DWBT is developed and verified to investigate the cross-sectional evolution and deformation features. The results show the following. (i) In the 720° curling forming process from the steel strip into double-walled tubes, the curvature of the formed circular arc initially increases and then remains stable with roll forming, and the inner and outer tubes of the DWBT are formed in the third and fifth forming passes. Size forming can eliminate the gap between the double walls and improve the overall roundness. (ii) For different deformation allocations, the cross-sectional profiles of the roll-formed parts exhibit a discrepancy, and the deformation amount varies with the roll-forming process. The deformation amount in Scheme three is the maximum, and the cross-sectional profile deviates significantly from the ideal shape and fails to form a DWBT, which indicates that the deformation allocation is unsuitable. (iii) The roundness of the outer tube is better than that of the inner tube. Therefore, the roundness of the inner tube is the key to restricting the forming accuracy of the DWBT. Compared with Schemes one and two, Scheme four with a linear allocation of the total feed distance exhibits the best roundness, and the deformation allocation is reasonable; i.e., when the contact points between the rollers and steel strip are in a straight line, the roundness of the DWBT is in good agreement with the ideal condition.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00448-y

Alternative flexible correction forming of a blade: multipoint correction with surface measurement and deformation simulation

Da-Wei Zhang, Wen-Long Gao-Zhang, Qi Zhang

2023, 11(4): 587-600. doi:10.1007/s40436-023-00440-6

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Distortion during the forging or machining processes of a blade causes problems in subsequent manufacturing. This paper proposes an alternative multipoint correction method integrated with blade measurement, determination of correcting parameters, and adjustment of the correcting die. An iterative algorithm for determining the correcting parameters is proposed. Measuring equipment combining a laser displacement sensor with multipoint flexible support is manufactured to measure the blade shape. Multipoint correcting equipment with an adaptive lower die and rapid adjustment is manufactured, and software is developed for data analysis and equipment control. The correction experiment for a rough-machined steam-turbine blade indicates that the correcting parameters can be determined after one modification based on numerical simulation, and that a rough blade that meets the allowance for finish machining can be obtained using the determined correction parameters.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00440-6

Rapid development methodology of agricultural robot navigation system working in GNSS-denied environment

Run-Mao Zhao, Zheng Zhu, Jian-Neng Chen, Tao-Jie Yu, Jun-Jie Ma, Guo-Shuai Fan, Min Wu, Pei-Chen Huang

2023, 11(4): 601-617. doi:10.1007/s40436-023-00438-0

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Robotic autonomous operating systems in global n40avigation satellite system (GNSS)-denied agricultural environments (green houses, feeding farms, and under canopy) have recently become a research hotspot. 3D light detection and ranging (LiDAR) locates the robot depending on environment and has become a popular perception sensor to navigate agricultural robots. A rapid development methodology of a 3D LiDAR-based navigation system for agricultural robots is proposed in this study, which includes: (i) individual plant clustering and its location estimation method (improved Euclidean clustering algorithm); (ii) robot path planning and tracking control method (Lyapunov direct method); (iii) construction of a robot-LiDAR-plant unified virtual simulation environment (combination use of Gazebo and SolidWorks); and (vi) evaluating the accuracy of the navigation system (triple evaluation: virtual simulation test, physical simulation test, and field test). Applying the proposed methodology, a navigation system for a grape field operation robot has been developed. The virtual simulation test, physical simulation test with GNSS as ground truth, and field test with path tracer showed that the robot could travel along the planned path quickly and smoothly. The maximum and mean absolute errors of path tracking are 2.72 cm, 1.02 cm; 3.12 cm, 1.31 cm, respectively, which meet the accuracy requirements of field operations, establishing the effectiveness of the proposed methodology. The proposed methodology has good scalability and can be implemented in a wide variety of field robot, which is promising to shorten the development cycle of agricultural robot navigation system working in GNSS-denied environment.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00438-0

Precision wire electrochemical machining of thick structures in powder superalloy René 88DT using a partially insulated tube electrode

Cheng Tang, Zhao Han, Zhong-Qi Zhou, Xiao-Long Fang

2023, 11(4): 618-635. doi:10.1007/s40436-023-00441-5

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Wire electrochemical machining (WECM) is a potential method for manufacturing macrostructures from difficult-to-cut materials, such as turbine slots, with good surface integrity and low costs. In this study, a novel tube electrode with array holes in the front and insulation in the back was applied using WECM to improve the machining precision and efficiency. Additionally, assisted by an immersion electrolyte and axial flushing, the electrolyte-deficient gap was supplemented to achieve the cutting of a very thick workpiece. The simulation results indicated that this method could effectively reduce the machining gap and improve the uniformity of the electric- and flow-field distributions. Experiments verified that when the uninsulated range (machining angle) was reduced from 360° to 90°, the side machining gap was reduced from 462.5 μm to 175 μm. Finally, using optimized machining parameters, array slits with gaps as small as (175±10) μm were machined on a powder superalloy René 88DT sample with a thickness of 10 mm at a feed rate of 16 μm/s. The feasibility of fabricating complex profiles using this method was verified using a self-designed servo device.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00441-5

Melt flow, solidification structures, and defects in 316 L steel strips produced by vertical centrifugal casting

Li-Bing Liu, Cong-Hui Hu, Yun-Hu Zhang, Chang-Jiang Song, Qi-Jie Zhai

2023, 11(4): 636-646. doi:10.1007/s40436-023-00439-z

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Vertical centrifugal casting can significantly enhance the filling capability of molten metals, enabling the production of complex thin-walled castings at near-rapid cooling rates. In this study, the melt flow, solidification structures, and defects in 316 L steel cast strips with a geometry of 80 mm×60 mm×2.5 mm produced by vertical centrifugal casting were numerically and experimentally analyzed under different rotation speeds. With gradually increasing the rotation speed from 150 r/min to 900 r/min, the simulated results showed the shortest filling time and minimum porosity volume in the cast strip at a rotation speed of 600 r/min. Since a strong turbulent flow was generated by the rotation of the mold cavity during the filling process, experimental results showed that a “non-dendritic” structure was obtained in 316 L cast strip when centrifugal force was involved, whereas the typical dendritic structure was observed in the reference sample without rotation. Most areas of the cast strip exhibited one-dimensional cooling, but three-sided cooling appeared near the side of the cast strip. Moreover, the pores and cracks in the 316 L strips were detected by computed tomography scanning and analyzed with the corresponding numerical simulations. Results indicated the existence of an optimal rotational speed for producing cast strips with minimal casting defects. This study provides a better understanding of the filling and solidification processes of strips produced by vertical centrifugal casting.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00439-z

Digital twin-driven green material optimal selection and evolution in product iterative design

Feng Xiang, Ya-Dong Zhou, Zhi Zhang, Xiao-Fu Zou, Fei Tao, Ying Zuo

2023, 11(4): 647-662. doi:10.1007/s40436-023-00450-4

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In recent years, green concepts have been integrated into the product iterative design in the manufacturing field to address global competition and sustainability issues. However, previous efforts for green material optimal selection disregarded the interaction and fusion among physical entities, virtual models, and users, resulting in distortions and inaccuracies among user, physical entity, and virtual model such as inconsistency among the expected value, predicted simulation value, and actual performance value of evaluation indices. Therefore, this study proposes a digital twin-driven green material optimal selection and evolution method for product iterative design. Firstly, a novel framework is proposed. Subsequently, an analysis is carried out from six perspectives: the digital twin model construction for green material optimal selection, evolution mechanism of the digital twin model, multi-objective prediction and optimization, algorithm design, decision-making, and product function verification. Finally, taking the material selection of a shared bicycle frame as an example, the proposed method was verified by the prediction and iterative optimization of the carbon emission index.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00450-4

Coupling effect of micro-textured tools and cooling conditions on the turning performance of aluminum alloy 6061

Guo-Liang Liu, Jin-Tao Zheng, Chuan-Zhen Huang, Shu-Feng Sun, Xin-Fu Liu, Long-Jie Dai, De-Xiang Wang, Xiang-Yu Wang

2023, 11(4): 663-681. doi:10.1007/s40436-022-00432-y

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Micro-texturing has been widely proven to be an effective technology for achieving sustainable machining. However, the performance of micro-textured tools under different cooling conditions, especially their coupling effect on machined surface integrity, was scarcely reported. In this paper, the non-textured, linear micro-grooved, and curvilinear micro-grooved inserts were used to turn aluminum alloy 6061 under dry, emulsion, and liquid nitrogen cryogenic cooling conditions. The coupling effects of different micro-textures and cooling conditions on cutting force, cutting temperature, and machined surface integrity, including the surface roughness, work hardening, and residual stress, were revealed and discussed in detail. Results indicated that the micro-grooved tools, especially the curvilinear micro-grooved tools, not only reduced the cutting force and cutting temperature, but also improved the machined surface integrity. In addition, the micro-grooved tools can cooperate with the emulsion or liquid nitrogen to reduce the cutting force, cutting temperature, and improve the machined surface integrity generally, although the combination of emulsion cooling condition and micro-grooved tools generated negative coupling effects on cutting forces and surface work hardening. Especially, the combination of curvilinear micro-grooved cutting tools and cryogenic cooling condition resulted in the lowest cutting force and cutting temperature, which generated the surface with low roughness, weak work hardening, and compressive residual stress.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00432-y

Multi-dimensional controllability analysis of precision ball bearing integrity

Lai Hu, Jun Zha, Wei-Hua Zhao, Xiao-Fei Peng, Yao-Long Chen

2023, 11(4): 682-693. doi:10.1007/s40436-022-00424-y

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Many factors affect the integrity of precision ball bearings. In this study, the multi-dimensional controllability of precision ball bearings produced in different company brands (bearing A and bearing B) were studied and compared. The geometric errors (flatness, parallelism, roundness and cylindricity of inner and outer rings, roundness, groove and roughness of inner and outer rings) and vibration errors of bearings were analyzed. Concurrently, the residual stress, residual austenite content, element content ratio, metamorphic layer and temperature-vibration displacement coupling test were also analyzed. Based on the above analysis conclusion, the bearing fatigue life test was carried out for 2 150 h. The reliability of the conclusion is proved again as follows. When the residual austenite content in the raceway of precision ball bearing is 10%, the axial residual stress is 877.4 MPa; the tangential residual stress is 488.1 MPa; the carbon content is 6%; the test temperature of bearing is the lowest; and the service life is prolonged.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00424-y

Identification of nonlinear process described by neural fuzzy Hammerstein-Wiener model using multi-signal processing

Feng Li, Li Jia, Ya Gu

2023, 11(4): 694-707. doi:10.1007/s40436-022-00426-w

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In this study, a novel approach for nonlinear process identification via neural fuzzy-based Hammerstein-Wiener model with process disturbance by means of multi-signal processing is presented. The Hammerstein-Wiener model consists of three blocks where a dynamic linear block is sandwiched between two static nonlinear blocks. Multi-signal sources are designed for achieving identification separation of the Hammerstein-Wiener process. The correlation analysis theory is utilized for estimating unknown parameters of output nonlinearity and linear block using separable signals, thus the interference of process disturbance is solved. Furthermore, the immeasurable intermediate variable and immeasurable noise term in identification model is taken over by auxiliary model output and estimate residuals, and then auxiliary model-based recursive extended least squares parameter estimation algorithm is derived to calculate parameters of the input nonlinearity and noise model. Finally, convergence analysis of the suggested identification scheme is derived using stochastic process theory. The simulation results indicate that proposed identification approach yields high identification accuracy and has good robustness.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00426-w

State of the art in finite element approaches for milling process: a review

Shailendra Chauhan, Rajeev Trehan, Ravi Pratap Singh

2023, 11(4): 708-751. doi:10.1007/s40436-022-00417-x

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Over a century, metal cutting has been observed as a vital process in the domain of manufacturing. Among the numerous available metal-cutting processes, milling has been considered as one of the most employable processes to machine a variety of engineering materials productively. In the milling process, material removal occurs when the workpiece is fed against a rotating tool with multiple cutting edges. In order to maximize the profitability of metal cutting operations, it is essential that the various input and output variable relationships are analyzed and optimized. The experimental method of studying milling processes is costly and time demanding, particularly when a large variety of elements such as cutting tool shape, materials, cutting conditions, and so on, are included. Due to these issues, other alternatives emerged in the form of mathematical simulations that employ numerical methods. The finite element approaches have well-proven to be the most practical and commonly utilized numerical methods. The finite element model (FEM) can be used to determine the various physical interactions occurring during the machining process along with the prediction of various milling characteristics, such as cutting forces, cutting temperature, stresses, etc., with the help of milling inputs. In the present article, various research studies in the broad milling process domain practiced with numerous finite element approaches have been critically reviewed and reported. It further highlights the several experimental and finite element approaches-based research studies that attempted to analyze and optimize the overall performance of the different milling processes. In recent years, various investigators have explored numerous ways to enhance milling performance by probing the different factors that influence the quality attributes. Some of the studies have also been found to be focused on the economic impacts of milling and various process inputs that affect milling performance. Furthermore, various milling factors’ impact on the performance characteristics are presented and critically discussed. The issues related to the recent improvements in tool-work interaction modeling, experimental techniques for acquiring various milling performance measures, and the aspects of turn and micro-milling with finite element-based modeling have been further highlighted. Among the various available classifications in the milling process as employed in industries, face milling is more strongly established compared to other versions such as end milling, helical milling, gear milling, etc. The final section of this research article explores the various research aspects and outlines future research directions.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00417-x

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