Multi-objective optimization of preforming operation in near-net shape forming of complex forging

Meng, Fanxiang; Cai, Zhongyi; Chen, Qing-Min

doi:10.1007/s00170-019-04539-8

Cited by 12 publications

(6 citation statements)

References 23 publications

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“…To accurately judge the forming effect of forgings by computer, it is necessary to quantify the equivalent strain field of the finished parts. The essence of an equivalent strain field is the combination of equivalent strain values for each grid element [31]. By extracting and calculating, the ratio of the grid area within the set strain range to the total grid area can accurately judge whether the forming effect is good or not.…”

Section: Design Of Algorithm For Preform Optimization 21 Design Of Ob...mentioning

confidence: 99%

“…In addition, it is possible to use other physical fields to describe the material flow and thus obtain the shape of the preform, for example, by integrating QForm metal forming simulation software with special CAD software that enables isothermal surface extraction to preform modeling [27]. With the development of random computer technology, a preform shape design method based on optimal design is widely used, which is to optimize the design variables related to the preform shape size to get the optimal solution with a particular index or a specific relative relationship as the objective function, such as response surface method (RSM) [29][30][31], sensitivity analysis [32,33], genetic algorithms (GA) [34][35][36], topological optimization [37,38] and reduced basis technique (RBT) [39].…”

Section: Introductionmentioning

confidence: 99%

“…The preform shape, no matter what design method is used to obtain it, needs to be verified by the forward forming process [27,31,36,38]. The difficulty of forwarding process analysis is parameter setting and constraint control, which reduces the number of trials and errors and improves optimization efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automatic preform design and optimization for aeroengine disk forgings

Han

Wang

Chen

et al. 2023

Int J Adv Manuf Technol

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To ensure a more uniform microstructure distribution of forging and improve the service performance of aeroengine disk parts, an automated preform design method is proposed for integrated preform shape design and optimization based on the NURBS curve, finite element method (FEM), and genetic algorithm (GA). Firstly, the random preform shape graph is automatically constructed by the NURBS curve design criterion. The volume and shape complexity are used as the constraints of the preform. Then the ratio of the mesh area within the set strain range to the total mesh area is used as the fitness function for the uniformity of deformation, and the genetic algorithm module is used for optimization. Finally, a large disk forging is an example of its optimal design. The results show that the deformation uniformity of the forgings is excellent, its fitness value is as high as 99.59%, and there are no problems such as folding, underfilling, and limited distribution of flash, which verifies the effectiveness of the method. In addition, the method has the advantage of strong universality, which can find the preform shape with good deformation uniformity for any shape forgings.

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Section: Design Of Algorithm For Preform Optimization 21 Design Of Ob...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automatic preform design and optimization for aeroengine disk forgings

Han

Wang

Chen

et al. 2023

Int J Adv Manuf Technol

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show abstract

“…The number of experimental steps groups is lower, which can greatly save time and cost, and helps analyze optimized process parameters [ 18 , 19 , 20 ]. Recently, Meng et al [ 21 ] used RSM merged with an FEM simulation to study the preforging of railway freight car couplers and proposed a closed-die forging method without flash, and also designed and optimized the preforming process of railway freight. The test results verified that the process was able to produce high-quality parts without forming defects.…”

Section: Introductionmentioning

confidence: 99%

A Comparison and Analysis of Three Methods of Aluminum Crown Forgings in Processing Optimization

Chen

Shih

et al. 2022

Materials

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In this study, three parameter optimization methods and two designs of experiments (DOE) were used for the optimization of three major design parameters ((bill diameter (D), billet length (L), and barrier wall design (BWD)) in crown forging to improve the formability of aluminum workpiece for shock absorbers. The first optimization method is the response surface method (RSM) combined with Box–Behnken’s experimental design to establish fifteen (15) sets of parameter combinations for research. The second one is the main effects plot method (MEP). The third one is the multiobjective optimization method combined with Taguchi’s experimental design method, which designed nine (9) parameter combinations and conducted research and analysis through grey relational analysis (GRA). Initially, a new type of forging die and billet in the controlled deformation zone (CDZ) was established by CAD (computer-aided design) modeling and the finite element method (FEM) for model simulation. Then, this investigation showed that the optimal parameter conditions obtained by these three optimization approaches (RSM, MEP, and multiobjective optimization) are consistent, with the same results. The best optimization parameters are the dimension of the billet ((D: 40 mm, the length of the billet (L): 205 mm, and the design of the barrier wall (BWD): 22 mm)). The results indicate that the optimization methods used in this research all have a high degree of accuracy. According to the research results of grey relational analysis (GRA), the size of the barrier wall design (BWD) in the controllable deformation zone (CDZ) has the greatest influence on the improvement of the preforming die, indicating that it is an important factor to increase the filling rate of aluminum crown forgings. At the end, the optimized parameters are verified by FEM simulation analysis and actual production validation as well as grain streamline distribution, processing map, and microstructure analysis on crown forgings. The novelty of this work is that it provides a novel preforming die through the mutual verification of different optimization methods to solve a typical problem such as material underfill.

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“…Therefore, to obtain higher dimensional accuracy, subsequent processing is necessary [1] , which is low efficiency and high cost. Near net forming or precision forming [2,3] can reduce or completely avoid the subsequent machining, thus reducing production processes while improving material utilization and production efficiency.…”

Section: Introductionmentioning

confidence: 99%