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Języki publikacji
Abstrakty
In this paper, a typical cold forging process using spring-held die is considered, in which the process parameters such as stiffness of spring, the initial loads and the punch speed are conventionally adjusted by the trial-and-error method for high product quality. The target product has the earing, around which the crack is often observed by the conventional process parameters. To avoid the crack around the earing, the process parameters optimization is performed through numerical simulation using DEFORM3D, in which two objective functions are considered. The risk of crack is numerically evaluated and is minimized, whereas the total forging energy using the load-stroke diagram is also minimized. Therefore, the multi-objective design optimization is performed. The numerical simulation is so intensive that sequential approximate optimization using radial basis function network is adopted to identify the pareto-frontier between the objectives with a small number of simulations. Compared with the product using the conventional process parameters, the optimal process parameters can reduce both the risk of crack and the total forging energy. In addition, the flow lines along the product shape can be obtained by using the optimal process parameters. Based on the numerical result, the experiment using the mechanical press (IST100W, ITO) is carried out. No crack is observed in the experiment, and then the validity of the proposed approach is confirmed.
Czasopismo
Rocznik
Tom
Strony
795--806
Opis fizyczny
Bibliogr. 24 poz., fot., rys., wykr.
Twórcy
autor
- Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan
autor
- Graduate School of Natural Science and Technology, Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan
autor
- Industrial Research Institute of Ishikawa, 2-1, Kuratsuki, Kanazawa 920-8203, Japan
autor
- Kaga INC., Ota Ni-140, Tsubata-cho, Kahoku-gun, Ishikawa 929-0345, Japan
Bibliografia
- [1] Kohar CP, Zhumagulov A, Brahme A, Worswick MJ, Mishara RK, Inal K. Development of high crush efficient, extrudable aluminium front rails for vehicle lightweighting. Int J Impact Eng. 2016;95:17–34.
- [2] Zhou J, Lin L, Luo Y. The multi-objective optimization design of a new closed extrusion forging technology for a steering knuckle with long rod and fork. Int J Adv Manuf Technol. 2014;72:1219–25.
- [3] Alimirzaloo V, Biglari FR, Sadeghi MH, Keshtiban PM, Sehat HR. A novel method for preform die design in forging process of an airfoil blade based on Lagrange interpolation and meta-heuristic algorithm. Int J Adv Manuf Technol. 2019;102:4031–45.
- [4] Zhao G, Wright E, Grandhi RV. Preform die shape design in metal forming using an optimization method. Int J Numer Methods Eng. 1997;40:1213–30.
- [5] Vieilledent D, Fourment L. Shape optimization of axisymmetric preform tools in forging using a direct differentiation method. Int J Numer Methods Eng. 2001;52:1301–21.
- [6] Castro CF, Antonio CAC, Sousa LC. Optimisation of shape and process parameters in metal forging using genetic algorithms. J Mater Process Technol. 2004;146:356–64.
- [7] Poursina M, Parvizian J, Antonio CAC. Optimum pre-form dies in two-stage forging. J Mater Process Technol. 2006;174:325–33.
- [8] Kim DJ, Kim BM, Choi JC. Determination of the initial billet geometry for a forged product using neural networks. J Mater Process Technol. 1997;72:86–93.
- [9] Tang YC, Zhou XH, Chen J. Preform tool shape optimization and redesign based on neural network response surface methodology. Finite Elem Anal Des. 2008;44:462–71.
- [10] Shao Y, Lu B, Ou H, Ren F, Chen J. Evolutionary forging perform design optimization using strain-based criterion. Int J Adv Manuf Technol. 2014;71:69–80.
- [11] Lu B, Ou H, Cui ZS. Shape optimisation of preform design for precision close-die forging. Struct Multidiscip Optim. 2011;44:785–96.
- [12] Yang H, Ma X, Jiao F, Fang Z. Preform optimal design of H-shaped forging based on bi-directional evolutionary structural optimization. Int J Adv Manuf Technol. 2019;101:1–8.
- [13] Thiyagarajan N, Grandhi RV. 3D preform shape optimization in forging using reduced basis techniques. Eng Optim. 2005;37:797–811.
- [14] Bonte MHA, Fourment L, Do TT, van den Boogaard AH, Huetink J. Optimization of forging processes using finite element simulations a comparison of sequential approximate optimization and other algorithms-. Struct Multidiscip Optim. 2010;42:797–810.
- [15] Hino R, Sasaki A, Yoshida F, Toropov VV. A new algorithm for reducing of number of press-forming stages in forging processes using numerical optimization and FE simulation. Int J Mech Sci. 2008;50:974–83.
- [16] Sanjari M, Taheri AK, Movahedi MR. An optimization method for radial forging process using ANN and Taguchi method. Int J Adv Manuf Technol. 2009;40:776–84.
- [17] Zhu F, Wang Z, Lv M. Multi-objective optimization method of precision forging process parameters to control the forming quality. Int J Adv Manuf Technol. 2016;83:1763–71.
- [18] Okada M, Kitayama S, Kawamoto K, Chikahisa J, Yoneyama T. Determination of back-pressure profile for forward extrusion using sequential approximate optimization. Struct Multidiscip Optim. 2015;51:225–37.
- [19] Kitayama S, Arakawa M, Yamazaki K. Sequential approximate optimization using radial basis function network for engineering optimization. Optim Eng. 2011;12:535–57.
- [20] Deng L, Dai W, Wang X, Jin J, Li J. Metal flow controlled by back pressure in the forming process of rib-web parts. Int J Adv Manuf Technol. 2018;97:1663–72.
- [21] Zhang Y, Shan D, Xu F. Flow lines control of disk structure with complex shape in isothermal precision forging. J Mater Process Technol. 2009;209:745–53.
- [22] Gao P, Yang H, Fan X, Lei P. Forming defects control in transitional region during isothermal local loading of Ti-alloy rib-web component. Int J Adv Manuf Technol. 2015;76:857–68.
- [23] Miettinen KM. Nonlinear multiobjective optimization. Kluwer Academic Publishers; 1998.
- [24] Kitayama S, Saikyo M, Nishio Y, Tsutsumi K. Torque control strategy incorporating charge torque and optimization for fuel consumption and emissions reduction in parallel hybrid electric vehicles. Struct Multidiscip Optim. 2016;54:177–91.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-26a0c9a2-66b6-4caf-89b6-bbfd21196237