Abstract
The emergence of cloud-based technologies has been transforming manufacturing industries over the last decade; however, their application in process modelling and finite element simulations is still limited. With the development of new hot stamping technologies, comprehensive knowledge of forming process phenomena is essential for their implementation, yet this knowledge is not readily accessible. In this paper, the development of a novel technique known as Knowledge Based Cloud-Finite Element (KBC-FE) simulation is described. KBC-FE is a research-oriented sheet metal-forming simulation technique that operates on an online platform. It was developed to facilitate the computation of advanced predictive models and to provide advanced functionalities to research institutions as well as industry. By making the relevant knowledge accessible, the technique enables multi-objective simulations, comprised of individual advanced functional modules each with their own speciality in the field of hot stamping of sheet metals, for rigorous analyses of different processes and for process optimisation. The capability of multi-objective FE simulations is demonstrated through the case study of a hot-formed U-shaped component, where multiple aspects of a part formed at elevated temperatures were examined. The advanced functional modules ‘Formability’, ‘Tool Maker’, and ‘Tailor’ were used to predict formability, die quenching efficiency, and post-form strength respectively.
Highlights
The application of cloud computing and the Internet of Things (IoT) in industry has been growing rapidly in recent years
2.4 Characteristics of the Knowledge Based Cloud-Finite Element (KBC-finite element (FE)) simulation technique inputs that are designed to fulfil the needs of design challenges, whilst the application layer offers tailored functional modules for computation; both rely on the underlying cloud platform layer, which efficiently carries out the computations and processes the data inputs and outputs, whilst linking all the users of the framework together
The capability of the KBC-FE simulation technique in enabling multi-objective simulations was successfully demonstrated through the case study of the hot forming of the Ushaped part from the aluminium alloy AA6082
Summary
The application of cloud computing and the Internet of Things (IoT) in industry has been growing rapidly in recent years. Advanced mechanism-based predictive models are essential for gaining a comprehensive understanding of different aspects of a sheet metal-forming process, such as the material’s formability and post-form strength during hot stamping. Advanced mechanism-based models are operated independently as sophisticated subroutines running on FE simulation software, as was applied to a hot deep drawing process simulated in ABAQUS with a specially designed VUMAT subroutine to predict the evolution of damage [24]. The utility of such advanced functions could be enhanced by developing them into FE software agnostic functional modules and subsequently running them simultaneously on a cloud-based platform This platform would foster a collaborative research and development environment, providing a means for research digitalisation and knowledge sharing, and for exploring manufacturing technologies in more depth and promoting step-changes in scientific research and industrial production. Based on an experimentally validated FE simulation, the Ushaped part was evaluated using multiple functional modules: ‘Formability’, ‘Tool Maker’, and ‘Tailor’, from which the formability, the die quenching efficiency, and the post-form hardness respectively were predicted
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