Project Details
Projekt
Inverse modelling of the process chain of an ADI component to control process-related distortion and hardening problems
Subject Area
Metal-Cutting and Abrasive Manufacturing Engineering
Primary Shaping and Reshaping Technology, Additive Manufacturing
Primary Shaping and Reshaping Technology, Additive Manufacturing
Term
since 2025
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 558452356
Austempered Ductile Iron (ADI), an ausferritic cast iron with nodular graphite, combines high tensile strength and wear resistance with remarkable elongation at break. However, the production of ADI components is complex and requires precise control of numerous material and process parameters along the process chain from casting and heat treatment to machining. Important quality characteristics include dimensional accuracy, hardness, martensite content and tool life during machining. Process fluctuations, such as in the chemical composition and temperature control during heat treatment, influence the microstructure of the ADI and lead to different degrees of hardness. Different cooling rates can cause residual stresses and distortion in complex components, which further complicates the machining process. As part of the planned research project, the process chain for the production of ADI cast components consisting of the casting, heat treatment and machining steps is to be modelled and inversely optimized. The aim of the first funding period is to gain an in-depth understanding of the relationships between 14 adjustable process parameters and four quality-relevant target variables (hardness, martensite content, dimensional accuracy and tool life). For this purpose, an experimental process chain is being set up that is comprehensively instrumented to record the relevant measured variables using sensors. This serves as the basis for modeling the individual processes, whereby a multivariant, invertible prediction model is developed for each process step. Another central aspect of the project is the quantification of stochastic uncertainties in the models in order to ensure robust optimization. Based on the individual models, a global overall forecasting model is created that links all individual processes with each other. This overall model makes it possible to predict the effects of the various process parameters on the quality of the end product across all processes. A particular focus is on the inverse design: Instead of optimizing the process parameters sequentially, the required parameters are inferred backwards from the target parameters. The results of the first funding period create the basis for the second phase, in which a global, multi-criteria optimization of the entire process chain will be carried out in order to manufacture ADI components more efficiently and with less use of resources in the future.
DFG Programme
Priority Programmes
