Scope for Machine Learning in Digital Manufacturing
September 19, 2016 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Martin Baumers, Ender Ozcan
arXiv ID
1609.05835
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CY
Citations
5
Venue
arXiv.org
Last Checked
4 months ago
Abstract
This provocation paper provides an overview of the underlying optimisation problem in the emerging field of Digital Manufacturing. Initially, this paper discusses how the notion of Digital Manufacturing is transforming from a term describing a suite of software tools for the integration of production and design functions towards a more general concept incorporating computerised manufacturing and supply chain processes, as well as information collection and utilisation across the product life cycle. On this basis, we use the example of one such manufacturing process, Additive Manufacturing, to identify an integrated multi-objective optimisation problem underlying Digital Manufacturing. Forming an opportunity for a concurrent application of data science and optimisation, a set of challenges arising from this problem is outlined.
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