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The Knowledge Based Cloud FEA (KBC-FEA) simulation technique allows multi-objective FE simulations to be conducted on a cloud-computing environment, which effectively reduces computation time and expands the capability of FE simulation software. In this paper, a novel functional module was developed for the data mining of experimentally verified FE simulation results for metal forming processes obtained from KBC-FE. Through this functional module, the thermo-mechanical characteristics of a metal forming process were deduced, enabling a systematic and data-driven guideline for mechanical property characterization to be developed, which will directly guide the material tests for a metal forming process towards the most efficient and effective scheme. Successful application of this data-driven guideline would reduce the efforts for material characterization, leading to the development of more accurate material models, which in turn enhance the accuracy of FE simulations

Knowledge Based Cloud FE simulation - data-driven material characterization guidelines for the hot stamping of aluminium alloys