Metody materiálového modelování pro procesy tepelného zpracování kovů

Waldenmaier Thomas, Hermann Autenrieth - Robert Bosch GmbH (Germany)

In metal processing, components with the highest quality requirements are produced for many aspects of life. However, the quality demands are matched by equally high requirements in terms of costs throughout the entire product life cycle. Increasing or decreasing quantities also demand very flexible production routes, mostly across supply chains. For this reason, specifications are agreed upon that sufficiently describe the condition of material batches, a semi-finished product or a component so that the product properties can be guaranteed to the end customer.
Modern approaches to describing a process, condition or component allow the quality of metal processing steps to be described along the process chain, which could eliminate non-value-added controls to maintain quality within supply chains. Digital twins of individual components, assemblies or entire products can also make a significant contribution to preventive maintenance of products in the field. Likewise, the resilience of the products can be related to the stresses placed on them by the users.
This paper will provide an overview of possible modelling approaches that are required to create digital twins of components along manufacturing and supply chains.

KEYWORDS: physical modelling, data mining, machine learning, hybrid modelling, artificial intelligence, digital twin

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