| Along with the rapid development of automobile industry and the continuous increase of automobile sales in our country,the use of automobile stamping die performance and life were put forward higher requirements.The use performance and life of the stamping die directly influence the quality,processing cost and efficiency of automobile.Meanwhile,along with economic globalization and increasing competition,in order to be better development,enterprises must improve the quality and reduce cost.In automobile industry,die fee can be more than 15%of the product cost,the users play extreme attention to the service life of stamping die.The die material occurred plastic deformation,surface friction,wear,or fatigue damage,mostly resulted in the failure and abandon of stamping die,which 70%are caused by the die wear directly or indirectly.As a result,how to accurately predict the die wear site and wear depth to reduce wear have very important significance for the improvement of die life.Previous studies mostly not considered the die wear of subsequent time stamping affected by the previous stamping,and the relationship between single stamping wear and gross wear is not always simple linear,and as the increase of wear,the contact stress of die and the relative sliding velocity of blank are also changing.In this paper,a dynamic mixed wear model by studying the die wear mechanisms of automobile covering parts and a new method were put forward for predicting die wear life.The method considered the influence of wear coefficients and roughness coefficients of the chromium plating layer and heat treatment in the thickness direction,material hardness gradient change from mold surface to core.The new parameters which acquired by constantly updating the wear geometric profile via moving mesh nodes,make up for the shortage which the classical Archard’s model ignores the contact stress and sliding speed changed by the wear.In finite element methods,the shell elements were used to simulate stamping contact surface,which didn’t need to express the whole die,to reduce the complexity problems greatly and to improve the efficiency of calculation,and this method set up the exact relationship between the number of stamping times and die wear depth and obtained the die wear depth quantitative prediction methods.As different strengthening ways have significant effect on die wear,laser quenching is widely used because of its obvious advantages in die surface treatment,and different process parameters on the quenching effect is different.In this paper,by optimizing the power of laser quenching,the moving speed and the light spot diameter,to find out the common die material—nodular cast iron QT600-3 the best laser quenching process parameters and get the best hardness and hardening depth.The hardness gradient change relationship from the surface to the core was obtained through the study of the die material of temperature field,organization transformation and hardness of laser surface hardening numerical simulation and experimental verification,and proved the accuracy and feasibility of the simulation results,then used to wear prediction analysis.In order to increase the die’s smoothness and abrasion resistance,the die must be processed by chromium plating after laser quenching.In this paper,the die material which treated by laser quenching was used to experiment in electroplating chromium,to get the thickness and surface hardness of the chromium plating layer.Two kinds of die material samples which were respectively treated by laser quenching and electroplating chromium after laser quenching were used to experiment in wear by self-developed friction tester,to get the wear coefficients and roughness of different processing methods and the proportion of different wear types,and then applied these parameters to the wear dynamic model to predict the die wear life.By analyzing a hood outer by this method and comparing with the classical Archard method and the actual die wear,the result shows that the new method is closer to the actual wear distinctly—deviation is 2.533%,smaller than classical Archard method 21.35%,and the accuracy is obviously higher than the classical Archard method. |