Scope for Machine Learning in Digital Manufacturing
It highlights opportunities for machine learning in manufacturing, but is incremental as it focuses on conceptual challenges rather than new solutions.
The paper identifies an integrated multi-objective optimization problem in Digital Manufacturing, using Additive Manufacturing as an example, and outlines challenges for applying data science and optimization to address it.
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.