Framing Artificial Intelligence (AI) Additive Manufacturing (AM)
Bernhard Heiden, Volodymyr Alieksieiev, Matthias Volk, Bianca Tonino-Heiden
Abstract
Nowadays AM is a rapidly growing and emerging discipline in manufacturing, as well as AI is in informational applications. Both are related to logistical and self-referential/-copying concepts which make them scalable. What is in AM osmotic mass production spreading is in AI-related Cyber-Physical Systems (CPS) the osmotic computational approach. AI-AM self-propagatedly framed is itself an emerging field, which can be logically or systematically unified. The paper investigates firstly recent developments in the field of the AM process flow and how it is related to AI applications. The result is a list of logistical, organisational, and industrial process steps as well as modern and future AI-AM applications. The extended approach then gives prospect to a meta-perspectively embedded osmotic decentralized computing, as well as an osmotic manufacturing paradigm, which utilizes glocal functions, concerning local production as well as global distributed material and information transport nets and their connection graphs.