The use of numerical simulations for tool tryout and process control is becoming increasingly prevalent. In this work, the deep drawing process of a car inner door panel of DC06 mild steel is numerically analyzed and compared with industrial process results. Five batches of DC06 material were analyzed mechanically and tribologically. Diverse tribological models were developed based on experimental strip drawing tests, where a Coefficient of Friction (CoF) was obtained as a function of contact pressure, sliding velocity, and amount of lubricant. A topography analysis was defined to compare material batches and to replicate industrial tool conditions. The simulation was fed with three tribological models: constant (CoF 0.15), Filzek pressure and velocity dependent, and TriboForm with lubrication zones. Thinning, Forming Limit Diagram (FLD) and draw-in were used as indicators for the comparison. Using the industrial tool, both FLD and draw-in were measured and compared with the numerical models. The constant model predicted the most conservative strain state and also differed most from the experimental results. The P-v-dependent and TriboForm models more accurately predicted the experimental results. This work highlights the importance of considering more complex tribological models to feed numerical simulations to yield results closer to real process conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.