Towards data-driven additive manufacturing processes
Paper in proceeding, 2022

Additive Manufacturing (AM), or 3D printing, is a potential game-changer in medical and aerospatial sectors, among others. AM enables rapid prototyping (allowing development/manufacturing of advanced components in a matter of days), weight reduction, mass customization, and on-demand manufacturing to reduce inventory costs. At present, though, AM has been showcased in many pilot studies but has not reached broad industrial application. Online monitoring and data-driven decision-making are needed to go beyond existing offline and manual approaches. We aim at advancing the state-of-the-art by introducing the STRATA framework. While providing APIs tailored to AM printing processes, STRATA leverages common processing paradigms such as stream processing and key-value stores, enabling both scalable analysis and portability. As we show with a real-world use case, STRATA can support online analysis with sub-second latency for custom data pipelines monitoring several processes in parallel.

powder bed fusion - laser beam

additive manufacturing

stream processing

big data

Author

Vincenzo Massimiliano Gulisano

Network and Systems

Marina Papatriantafilou

Network and Systems

Zhuoer Chen

Chalmers, Industrial and Materials Science, Materials and manufacture

Eduard Hryha

Chalmers, Industrial and Materials Science, Materials and manufacture

Lars Nyborg

Chalmers, Industrial and Materials Science, Materials and manufacture

Middleware 2022 Industrial Track - Proceedings of the 23rd International Middleware Conference Industrial Track, Part of Middleware 2022

43-49
9781450399173 (ISBN)

23rd International Middleware Conference Industrial Track, Middleware Industrial Track 2022 - Part of Middleware 2022
Quebec, Canada,

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Software Engineering

Media Engineering

DOI

10.1145/3564695.3564778

More information

Latest update

1/3/2024 9