3D FEM simulation of flow velocity field for 5052 aluminum alloy multi-row sprocket in cold semi-precision forging process

Cheng, Wangjun; Chi, Chengzhong; Wang, Yongzhen; Peng, Lin; Zhao, Rongsheng; Liang, Wei

doi:10.1016/s1003-6326(15)63681-0

Cited by 8 publications

(2 citation statements)

References 17 publications

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“…Suthep and Uten (2015) proposed cold heading of stainless steel, which is a complicated process based on DEFORM simulation, and they compared the parameters of production processes to factory processes. Cheng et al (2015) proposed a cold semiprecision forging process for the 5052-aluminum alloy multi-sprocket. DEFORM-3D was used to simulate the flow velocity fields in cold semi-precision forging.…”

Section: Previous Workmentioning

confidence: 99%

Quality Prediction Modeling of a Preform Fastener Process using Fuzzy Logic and DEFORM Simulation

Butdee¹,

Khanawapee²

2021

IJTech

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Quality is the most important aspect of fastener production for maintaining competitiveness and customer satisfaction. Nowadays, the quality control process is uncertain and complicated. Cold forging is used to produce preform fasteners via various processes. As a traditional measure of cold forging, quality prediction can be done using the normal probability method, but this approach is not effective or accurate enough. This paper proposes a novel quality prediction for preform fasteners using a fuzzy inference system and DEFORM simulation using an engineering software called DEFORM® system that can analyze metal forming. Multi-factors and criteria are considered, consisting of deformability, defects, stress, and time. The developed modeling can predict the cold forging quality at the stage of product design, which can associate decision making with production control. It can eliminate defects and reduce cost and time to rework. The case study is illustrated on the cold heading of stainless 341 using DEFORM, whereas the modeling is simulated by MATLAB.

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Section: Previous Workmentioning

confidence: 99%

Quality Prediction Modeling of a Preform Fastener Process using Fuzzy Logic and DEFORM Simulation

Butdee¹,

Khanawapee²

2021

IJTech

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“…The preforming die and hot forging process can be adjusted and optimized through the Marc software, and the die set with the best performance has been obtained [31]. Multiple rows of sprockets are produced using a semi-precision die, and then the in uence of speed on cavity lling is analyzed [32]. The new closure proposed to eliminate the existing steering knuckle forming process is the extrusion forging die [33].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Controllable Deformation Zone And Die Wear of Aluminum Crown Forgings For Shock Absorber Assembly

Shih

et al. 2021

Preprint

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In this research, numerical analysis, response surface method (RSM) and experiments are used to investigate and verify the hot forging process for manufacturing aluminum crown forgings for shock absorber assembly. First, establish the computer aided design (CAD) model of the die and the billet, and simulate it from the finite element method (FEM). Second, a new preforming die was designed with a preformed dressing of controllable deformation zone (CDZ) by the CAD software. Third, numerical simulation was combined with RSM to optimize the processing parameters with the aim of minimizing the die wear while the integrity of forgings should be prioritized preserved. According to RSM, the billet size and preformed dressing of CDZ are important factors affecting the distance between die and workpiece (C). The optimal design factor of the preforming die: billet diameter (D), billet length (L) and flash design (F) are 40 mm, 205 mm and CDZ 1, respectively. Through the results of FEM, this study describes the distribution of microscopic grain flow lines are highly related to forming, stress, strain, and temperature as well as die design such as CDZ in preformed dressing. In order to accurately verify that the parameters analyzed by the RSM, both numerical analysis and physical experiments are carried out and optimal scheme exhibit reasonable consistency.

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Case-Based Reasoning with Fuzzy Logic Knowledge Acquisition for Adaptive Fastener Die Design on Bi-material Forming

Butdee,

Khanawapee,

Thanadngarn

2024

Advanced in Creative Technology- Added Value Innovations in Engineering, Materials and Manufacturing

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3D FEM simulation of flow velocity field for 5052 aluminum alloy multi-row sprocket in cold semi-precision forging process

Cited by 8 publications

References 17 publications

Quality Prediction Modeling of a Preform Fastener Process using Fuzzy Logic and DEFORM Simulation

Quality Prediction Modeling of a Preform Fastener Process using Fuzzy Logic and DEFORM Simulation

Optimization of Controllable Deformation Zone And Die Wear of Aluminum Crown Forgings For Shock Absorber Assembly

Case-Based Reasoning with Fuzzy Logic Knowledge Acquisition for Adaptive Fastener Die Design on Bi-material Forming

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