Optimized Design for a Combined Die with Two Stress Rings in Cold Forging Considering Thermal-Mechanical Effects

doi:10.1007/s12204-019-2150-y

摘要/Abstract

摘要： Stress analysis and optimization of combined die structure with two stress rings were performed. Using thermoelastic deformation, the contact pressure at the interfaces between layers was calculated. Then, theoretical expressions of stress distribution for the combined die were derived. The thermal-mechanical effect under working conditions was considered. To verify the theoretical expressions, simulation work was performed. Optimization of die design was carried out by defining radius ratio and shrink fit coefficient as optimization variables. The objective was to minimize the effective circumferential stress at the inner surface of the die insert, under the constraint that the maximum equivalent stress values of die insert and stress rings did not exceed their respective yield stresses. The Kriging model was used to describe the influence of shrink fit and die dimensions on the objective function and the maximum equivalent stress. Using a genetic algorithm, optimum parameters were found with a minimum circumferential stress of 442.9MPa under a working stress of 1 800MPa. Further analysis of five selected optimal results was carried out, and the specific design parameters of these combined dies are different under the same level of circumferential stress, and the combined die is overdesigned if the thermal effect is ignored.

关键词: cold forging, combined die, die dimension, optimization, thermal-mechanical effect, genetic algorithm

Abstract: Stress analysis and optimization of combined die structure with two stress rings were performed. Using thermoelastic deformation, the contact pressure at the interfaces between layers was calculated. Then, theoretical expressions of stress distribution for the combined die were derived. The thermal-mechanical effect under working conditions was considered. To verify the theoretical expressions, simulation work was performed. Optimization of die design was carried out by defining radius ratio and shrink fit coefficient as optimization variables. The objective was to minimize the effective circumferential stress at the inner surface of the die insert, under the constraint that the maximum equivalent stress values of die insert and stress rings did not exceed their respective yield stresses. The Kriging model was used to describe the influence of shrink fit and die dimensions on the objective function and the maximum equivalent stress. Using a genetic algorithm, optimum parameters were found with a minimum circumferential stress of 442.9MPa under a working stress of 1 800MPa. Further analysis of five selected optimal results was carried out, and the specific design parameters of these combined dies are different under the same level of circumferential stress, and the combined die is overdesigned if the thermal effect is ignored.

Key words: cold forging, combined die, die dimension, optimization, thermal-mechanical effect, genetic algorithm

中图分类号:

TG 316

LI Zibo, ZENG Fan, ZHAO Zhen, HU Chengliang. Optimized Design for a Combined Die with Two Stress Rings in Cold Forging Considering Thermal-Mechanical Effects[J]. Journal of Shanghai Jiao Tong University (Science), 2020, 25(3): 304-314.

参考文献 27

[1]	DODD B. Introduction to cold forging [EB/OL].[2018-07-27]. https://www.icfg.info/general-information/cold-forging.html.
[2]	FUJIKAWA S, YOSHIOKA H, SHIMAMURA S.Cold- and warm-forging applications in the automotive industry [J]. Journal of Materials Processing Technology,1992, 35(3/4): 317-342.
[3]	BAY N. The state of the art in cold forging lubrication[J]. Journal of Materials Processing Technology, 1994,46(1/2): 19-40.
[4]	MACCORMACK C, MONAGHAN J. Failure analysis of cold forging dies using FEA [J]. Journal of Materials Processing Technology, 2001, 117(1/2): 209-215.
[5]	KOC M, ARSLAN M A. Design and finite element analysis of innovative tooling elements (stress pins) to prolong-die life and improve dimensional tolerances in precision forming processes [J]. Journal of Materials Processing Technology, 2003, 142(3): 773-785.
[6]	YEO H T, CHOI Y, HUR K D. Analysis and design of the prestressed cold extrusion die [J]. The International Journal of Advanced Manufacturing Technology,2001, 18(1): 54-61.
[7]	CHEN X, BALENDRA R, QIN Y. A new approach for the optimisation of the shrink fitting of cold-forging dies [J]. Journal of Materials Processing Technology,2004, 145(2): 215-223.
[8]	KROI? T, ENGEL U, MERKLEIN M. Comprehensive approach for process modeling and optimization in cold forging considering interactions between process,tool and press [J]. Journal of Materials Processing Technology, 2013, 213(7): 1118-1127.
[9]	ZHANG Y, ZHOU J, HU Q G. Optimization design of combined die for cold extrusion based on particle swarm optimization [J]. Hot Working Technology,2010, 39(3): 95-97 (in Chinese).
[10]	KWAN C T, WANG C C. An optimal pre-stress die design of cold backward extrusion by RSM method [J].Structural Longevity, 2011, 5(1): 25-32.
[11]	JUN B Y, KANG S M, LEE M C, et al. Prediction of geometric dimensions for cold forgings using the finite element method [J]. Journal of Materials Processing Technology, 2007, 189(1/2/3): 459-465.
[12]	ISHIKAWA T, YUKAWA N, YOSHIDA Y, et al.Prediction of dimensional difference of product from tool in cold backward extrusion [J]. CIRP Annals-Manufacturing Technology, 2000, 49(1): 169-172.
[13]	LONG H, BALENDRA R. FE simulation of the influence of thermal and elastic effects on the accuracy of cold-extruded components [J]. Journal of Materials Processing Technology, 1998, 84(1/2/3): 247-260.
[14]	KHALEED H M T, SAMAD Z, OTHMAN A R, et al. Work-piece optimization and thermal analysis for flash-less cold forging of AUV propeller hubs: FEM simulation and experiment [J]. Journal of Manufacturing Processes, 2011, 13(1): 41-49.
[15]	QIN Y, BALENDRA R, CHODNIKIEWICZ K. Analysis of temperature and component form-error variation with the manufacturing cycle during the forward extrusion of components [J]. Journal of Materials Processing Technology, 2004, 145(2): 171-179.
[16]	HU C L, YANG F Y, ZHAO Z, et al. Thermoelastic deformation of three-layer combined die under steady-state temperature field [J]. Journal of Thermal Stresses, 2016, 39(1): 103-119.
[17]	QIN Y, BALENDRA R, CHODNIKIEWICZ K. A method for the simulation of temperature stabilisation in the tools during multi-cycle cold-forging operations[J]. Journal of Materials Processing Technology, 2000,107(1/2/3): 252-259.
[18]	GROENBAEK J, BIRKER T. Innovations in cold forging die design [J]. Journal of Materials Processing Technology, 2000, 98(2): 155-161.
[19]	LIU Y G, JIAO A S. Analysis and study of stress and strain of cold extruding die [J]. Journal of Lanzhou Polytechnic College, 2003, 10(1): 31-34 (in Chinese).
[20]	HU C L, ZHAO Z, ZHI Y S, et al. Thermoelastic deformation of three-layer combined die with nonuniform temperature distribution [J]. Journal of Thermal Stresses, 2014, 37(10): 1230-1243.
[21]	MINASNY B, MCBRATNEY A B. A conditioned Latin hypercube method for sampling in the presence of ancillary information [J]. Computers & Geosciences,2006, 32(9): 1378-1388.
[22]	LEE H C, SAROOSH M A, SONG J H, et al. The effect of shrink fitting ratios on tool life in bolt forming processes [J]. Journal of Materials Processing Technology,2009, 209(8): 3766-3775.
[23]	JEONG S, MURAYAMA M, YAMAMOTO K. Efficient optimization design method using kriging model[J]. Journal of Aircraft, 2005, 42(2): 413-420.
[24]	HOLLAND J H. Genetic algorithms [J]. Scientific American, 1992, 267(1): 66-72.
[25]	JAYA SHANKAR T, BANDYOPADHYAY S. Optimization of extrusion process variables using a genetic algorithm [J]. Food and Bioproducts Processing, 2004,82(2): 143-150.
[26]	HOU E S H, ANSARI N, REN H. A genetic algorithm for multiprocessor scheduling [J]. IEEE Transactions on Parallel and Distributed Systems, 1994, 5(2): 113-120.
[27]	CHUNG J S, HWANG S M. Application of a genetic algorithm to the optimal design of the die shape in extrusion[J]. Journal of Materials Processing Technology,1997, 72(1): 69-77.