Modeling, analysis, and multi-objective optimization of cold extrusion process of clutch outer gear hub using response surface method and meta-heuristic approaches

Liu, Zuofa; Zhou, Jie; Wang, Feng; Chen, Yingying

doi:10.1007/s00170-021-07451-2

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…e experimental process of the thesis mainly verified the effectiveness of the two aspects of optimization proposed by SVR: one is to introduce SVR to generate timing evaluation proposals on multiscale timing feature maps; the second is to apply 2D convolution on the original feature map to jointly model the timing-channel [18]. e evaluation index of the result of the experiment includes the AUc of the AR curve to measure the performance of the sequential action proposal generation and the mAp to evaluate the performance of the sequential action detection.…”

Section: Experimental Results and Analysismentioning

confidence: 92%

Action Recognition, Tracking, and Optimization Analysis of Training Process Based on SVR Model and Multimedia Technology

Zhong

2022

Advances in Multimedia

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In order to explore the action recognition, tracking, and optimization analysis of the training process based on the SVR model and multimedia technology, the author proposes based on the radial basis function model, researching a new surrogate model technology-support vector regression (SVR). We first introduce the basic principles of SVR, select the parameters of SVR, and then elaborate the basic steps of SVR modeling. Then, we design and optimize application examples through numerical example multimedia technology; the validity of the support vector regression method is verified. Experimental results: the comparison of SVR1 and SVR2 shows that the utilization of multiscale timing feature maps should occur after tem (SVR2) rather than being directly fused in the feature dimension (SVR1), mainly because small-scale information affects the resolution of large-scale information; on data sets such as ActivityNet, in order to verify the effectiveness of SVR and DR-Dvc algorithms, the performance of the proposed algorithm and the baseline before improvement and the current mainstream algorithm are respectively compared. Experimental results show the proposed algorithm has a significant performance improvement compared to before the improvement; at the same time, it is better than most current mainstream algorithms, which proves the feasibility and effectiveness of the algorithm. Describing the introduction of regression can effectively improve the performance of sequential action proposals and event description algorithms, and compared with the current mainstream methods, it has certain performance advantages.

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Section: Experimental Results and Analysismentioning

confidence: 92%

Action Recognition, Tracking, and Optimization Analysis of Training Process Based on SVR Model and Multimedia Technology

Zhong

2022

Advances in Multimedia

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Technical review on design optimization in forging

Kitayama

2024

Int J Adv Manuf Technol

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Forging is a traditional and important manufacturing technology to produce various high strength products and is widely used in engineering fields such as automotive, aerospace and heavy industry. To produce highly accurate product, underfill that the material is not filled into the cavity should strongly avoided. For material saving and near-net product, flash should be minimized. To make the tool life long, it is preferable to produce product with low forging load. It is also preferable to uniformly deform the billet as much as possible for high strength product. Crack is a crucial defect and should strongly be avoided. Therefore, many requirements are taken into account in order to produce the forged product. To meet the requirements, design optimization in forging coupled with computer aided engineering (CAE) is an effective approach. This paper systematically reviews the related papers from the design optimization point of view. For the billet or die shape optimization, the papers are classified into four approaches. The process parameters optimization such as the billet temperature, the die temperature, the stroke length and the friction coefficient is conducted, and the related papers are also classified into four categories. The design variables and the objective function(s) used in the papers are clarified with the design optimization technique. The multi-stage forging including the hammer forging for producing complex product shape is also briefly reviewed. Finally, major performance indexes and the future outlook are summarized for the further development of design optimization in forging.

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Optimal energy distribution in hydraulic hammer forging for minimizing total energy and forging load

Kitayama,

Sugita,

Amano

et al. 2024

Int J Adv Manuf Technol

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Hammer forging is an important manufacturing technology in heavy industry to produce high stiffness product. Forging using mechanical press produces the product by controlling the distance between dies whereas the hydraulic hammer forging utilizes the energy given by the sum of hydraulic energy and potential energy of die, and the product is then produced through several blows. The energy at each blow is conventionally determined through the trial-and-error method. The process to produce the product is simple and the response of hammer foundations and anvil is mainly discussed in the literature, but the optimal energy distribution to successfully produce the product is rarely discussed. In this paper, the optimal energy distribution in hydraulic hammer forging is determined using numerical simulation coupled with design optimization technique. To determine the optimal energy distribution through the process, multi-objective design optimization for minimizing both the total energy and the maximum forging load is performed. High dimensional accuracy is generally required in the forged product, and the underfill is handled as the design constraint. The numerical simulation in hydraulic hammer forging is computationally so expensive that sequential approximate optimization that response surface is repeatedly constructed and optimized is adopted to identify the pareto-frontier between the total energy and the maximum forging load. It is clarified through the numerical result that the total energy is drastically reduced without the underfill in comparison with the conventional one. The experiment is also conducted to examine the proposed approach.

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Modeling, analysis, and multi-objective optimization of cold extrusion process of clutch outer gear hub using response surface method and meta-heuristic approaches

Cited by 3 publications

References 21 publications

Action Recognition, Tracking, and Optimization Analysis of Training Process Based on SVR Model and Multimedia Technology

Action Recognition, Tracking, and Optimization Analysis of Training Process Based on SVR Model and Multimedia Technology

Technical review on design optimization in forging

Optimal energy distribution in hydraulic hammer forging for minimizing total energy and forging load

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