Article ID Journal Published Year Pages File Type
795880 Journal of Materials Processing Technology 2013 10 Pages PDF
Abstract

In this paper a comprehensive approach is presented for the consideration of the interactions between process, tool and machine during the design of cold forging tools and processes by simulation. The interactions occur due to the high forming loads in cold forging and yield considerable deflections of press and tooling system. These, in turn, influence the workpiece dimensions. The entire approach comprises an efficient determination of the deflection characteristic of stroke-controlled press and tooling system and its condensed modeling in combination with the FE simulation of a cold forging process. Building on that, an analytic process model is developed that is based on a set of variant simulations. It permits an optimization of the values of influencing parameters to achieve high workpiece accuracy without subsequent adjusting effort. Initially, the analytic process model required a high number of variant simulations. By acquiring knowledge on the specific process behavior in an analysis of effects and interactions a considerable reduction of simulation runs by a factor of almost 12 was achieved in the case study on full forward extrusion. The approach is supplemented by an analytic model of the die load. In addition, scatter and uncertainties of target values depending on the ones of the influencing parameters can be estimated by applying the Monte Carlo method to the analytic process model.

► Determination of press and tool characteristic combining experiment and simulation. ► Combined FE modeling of cold forging process and entire deflection characteristic. ► Accurate analytic process modeling and optimization based on variant simulations. ► Usage of process knowledge leads to reduced simulation effort for process modeling. ► Estimate of achievable tolerances by applying Monte Carlo method to process model.

Related Topics
Physical Sciences and Engineering Engineering Industrial and Manufacturing Engineering
Authors
, , ,