The term solid forming describes processes in which compact metallic bodies, primarily of steel or aluminium, are formed: These are used, for example, as components for the automotive industry. In cold massive forming, blanks are not heated before forming, but are pressed into forming tools at room temperature and under high pressure. However, the parts can reach temperatures of well over 100 °C during the actual forming process. A prerequisite for economical production in cold forging is a complex pretreatment of the material by applying release layer lubricant systems to reduce friction in the forming process, without which premature wear or failure of the forming tools would occur.
However, multilayer lubricant systems with a conversion layer have some disadvantages. For example, large quantities of fresh water are used to operate the numerous treatment baths, which ultimately have to be disposed of as contaminated wastewater. In addition, all parts must be thoroughly rinsed between the process steps, which further increases the water requirement and wastewater accumulation, and the constant heating of the baths and the resulting evaporation are accompanied by energy losses.
In the DBU project, the ZWEZ-CHEMIE GmbH, Lindlar has developed and optimised water-based, oil- and solvent-free single-layer lubricant systems, which are explicitly designed for higher alloyed aluminium materials. In contrast to previous practice, this enables the combination of a fully automated mechanical surface treatment of the metal bodies to be formed, integrated into the production chain, with a subsequent coating by the new single-layer lubricants. The entire production process is thus made more flexible and can be digitally recorded in the context of "Industry 4.0". The new process is associated with considerably lower investment costs, which facilitates its introduction to users in the cold massive forming of aluminium materials.
The technology is currently undergoing further development to make it suitable for industrial use.
translated by DeepL
