Investigation of Hardness, Microstructure, and Process Temperature in the Internal Gear Flow-Forming Process

被引:0
|
作者
Khodadadi, M. [1 ]
Khalili, K. [1 ]
Ashrafi, A. [1 ]
Kolahan, F. [2 ]
机构
[1] Univ Birjand, Dept Mech Engn, Birjand, Iran
[2] Ferdowsi Univ Mashhad, Dept Mech Engn, Mashhad, Iran
关键词
Flow-forming; Internal gear; Optimization; Firefly algorithm; Finite element simulation; WALLED TUBULAR PART; STRAIN-HARDENING RATE; RING COMPRESSION TEST; OPTIMIZATION; PREDICTION; PARAMETERS;
D O I
10.1007/s40799-022-00622-0
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The advantages of the flow-forming process, such as excellent mechanical properties, simple tools, and the need for low forming force, have led to the increasing use of this process in various industries, especially in the military, aerospace, and automotive industries. New application of this process is the internal gear flow-forming process (IGFP), in which the gear is produced with simple tools and low forming force. In this paper, IGFP was studied by the finite element method and experiments. Experiments include tensile test (determine stress-strain curve of the material), ring compression test (determine friction coefficient), flow-forming test, and metallography. The material was considered elastic-plastic, and the Coulomb friction model was used to simulate the friction between surfaces. IGFP was performed by a simple setup. Teeth height and gear profile were measured and compared to simulated values, and there is a good agreement between the simulation and experimental results. Once the simulation is verified, the effects of process parameters (feed rate, roller diameter, attack angle of the roller, and thickness reduction percentage) on the process temperature were obtained using the design of experiments (DOE). According to DOE results, thickness reduction percentage (T) and roller diameter (D) have the most significant effect on process temperature. Finally, a function for process temperature was obtained versus input parameters, and this function was optimized by the firefly algorithm.
引用
收藏
页码:1169 / 1182
页数:14
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