Surface defects is an important issue in sheet metal stamping as the stamping process affects surface appearance and thus influences surface quality. A great amount of time is therefore spent during the product development process on the optimization of surface defects, particularly surface lows during tryout. Surface lows are characterized by unwanted changes of curvatures, i.e. isolated deviations between actual and desired geometry.
In light of the increased global competition, car manufacturers aim to build their new car models using state-of-the-art technologies which reduce time intensive work processes and increase planning accuracy. By implementing such technologies, the amount of time between the design freeze and the start of production can be optimally reduced. While the prediction of surface defects plays an important role in car manufacturing today, it is only effective if accomplished in time to carry out corrective measures.
During the product development process, experienced engineers discuss and define the measures for tool adjustments, which usually include the re-milling of tools. The extent to which these measures lead to an improvement of surface lows issues becomes apparent only after their implementation. Therefore, in order to achieve a satisfactory result, it is usually necessary to carry out several optimization loops, which are not only time consuming and costly but also difficult to plan. As a result, car manufacturers, particularly volume producers in the middle and upper class segments, must allow for time corridors in which the appropriate measures can be taken.
During the tryout phase, the detection and measurement of surface defects is carried out by stoning or optical measurement. In practice, new state-of-the-art software products enable the easy visualization of surface defects and imperfections by the digital stoning method. This method emulates the back and forth scratching of a stone block on a stamped outer panel.
In order to not only generate time and cost savings but especially to increase planning accuracy, surface defects detection and optimization must be moved up from the tryout phase to early on in the virtual process validation phase. The associated benefits are time and cost savings in the tryout phase and a significant increase in planning predictability.
Further information on surface defects at AutoForm: