Digital Forging Laboratory
A new simulation model developed by the Fraunhofer Institute for Mechanics of Materials IWM in Freiburg predicts weak points in forged components caused by incomplete grain formation (recrystallisation). Embedded within an efficient digital workflow, this creates a virtual forging laboratory that enables material and energy savings in forging processes.
Rising energy costs and stricter legal requirements for climate protection are putting pressure on the forging industry. At the same time, the shift towards sustainably produced ‘green’ steel requires a rethink in manufacturing. This is because new production processes result in fluctuating chemical compositions and altered material properties, making behaviour during forging more difficult to predict. Furthermore, a defective microstructure in safety-critical components is not only a quality issue but can also lead to catastrophic failure. This conflict between greater sustainability and the highest quality requirements is putting the forging industry under pressure.
Untapped potential for optimisation
On its journey from blank to component, the metal undergoes numerous energy-intensive steps: heating, forming, intermediate annealing and further forming. Each step depends on numerous variables, such as temperatures, degrees of forming, holding times and pressing forces, which must be precisely coordinated. The status quo in many forging plants is based on decades of experience and costly trial-and-error cycles. However, this approach reaches its limits when it comes to managing uncertainties caused by fluctuating material qualities. Attempts to replace real-world tests with computer simulations often fail due to a lack of models precisely tailored to the material, insufficient data and the difficulty of reliably translating simulation results into actionable recommendations.
Materials technology challenge
The real challenge lies in the material itself: during hot forming, the internal microstructure of the steel is not a rigid structure, but a dynamic system that is constantly changing. On the one hand, the material is strengthened by deformation; on the other hand, a process known as recrystallisation constantly forms new, stress-free grains within the microstructure. Subsequent grain growth can coarsen the microstructure again, whilst tiny particles (precipitates) can slow down this movement within the material. All these mechanisms are significantly influenced by the temperature, the degree of forming and the chemical composition of the steel.
The fine art of forging technology lies in mastering this complex interplay of physics, chemistry and mechanics. How can the machine settings on the giant forging press be linked to the development of the microscopically small material microstructure?
A digital forging laboratory in a traditionally oriented environment
This is precisely where the Fraunhofer IWM comes in, with a practical digital workflow that makes these complex processes within the material calculable. At the heart of this is a physical material model that focuses specifically on grain formation (recrystallisation). The so-called mean-field model combines the advantages of two worlds: It is based on thermodynamic principles and is therefore highly reliable – even under the complex, fluctuating conditions of industrial forging processes. At the same time, it is so computationally efficient that even components weighing several tonnes can be simulated on a computer within a reasonable timeframe. As the model is based on real physical quantities, it provides robust predictions, even when new alloys or altered process conditions come into play.
Demonstration of the digital forging laboratory’s capabilities
Just how well this model works in practice was demonstrated in the EU project AID4GREENEST. To this end, the entire forging process for a 22-tonne turbine shaft made from high-strength steel was simulated on a computer – a multi-stage process lasting several hours, involving multiple stages of forming and reheating.
“Our simulation correctly identified critical zones in advance,” explains Dr Maxim Zapara, Team Leader for Mass Forming at Fraunhofer IWM. An undesirably coarse-grained microstructure was predicted for the ends of the shaft, as the material in these areas had not been sufficiently worked during the final, decisive forging step.The model not only predicted the weak points but also directly identified the cause: whilst the core of the shaft was sufficiently deformed during the final forging step and the microstructure there was completely renewed and refined, this crucial ‘reset’ did not occur at the ends. This virtual prediction was later confirmed by material analyses carried out on the actual forged component.
Zapara goes on to explain: “This use case demonstrates that the model not only replicates material behaviour but can also uncover process errors before they occur in actual production. We can now test different approaches virtually: a simple adjustment to the final forging step in the simulation directly resulted in a completely fine-grained, defect-free component. In practice, this saves enormous amounts of material and energy.”
New scope for innovation
The digital forging laboratory opens up new scope for innovation: the focus is shifting from retrospective quality control to proactive process planning. Instead of months of test series for new materials, hundreds of scenarios can now be run through virtually within a few hours. In future, every forged component could even be issued with a “digital passport” – comprehensive documentation of its internal structure, verifying its quality and safety from manufacture right through to final use.
Source: Fraunhofer IWM