Recent Advances and Applications of Machine Learning in Metal Forming Processes
Overview & Synopsis
Machine learning (ML) technologies are emerging in Mechanical Engineering, driven by the increasing availability of datasets, coupled with the exponential growth in computer performance. In fact, there has been a growing interest in evaluating the capabilities of ML algorithms to approach topics related to metal forming processes, such as: Classification, detection and prediction of forming defects; Material parameters identification; Material modelling; Process classification and selection; Process design and optimization. The purpose of this Special Issue is to disseminate state-of-the-art ML applications in metal forming processes, covering 10 papers about the abovementioned and related topics.
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Document Information
| Document Title | Recent Advances and Applications of Machine Learning in Metal Forming Processes |
|---|---|
| Author / Organization | DOAB Contributor |
| Subject & Discipline | sheet metal forming |
| Categories | Open Access Books |
| Publication Year | 2022 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
Directory of Open Access Books
(www.doabooks.org)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-121675 |
| Original Source Link | Visit Source Page on www.doabooks.org » |