  With the ever increasing number of active satellites in space, the rising
demand for larger formations of small satellites and the commercialization of
the space industry (so-called New Space), the realization of manufacturing
processes in orbit comes closer to reality. Reducing launch costs and risks,
allowing for faster on-demand deployment of individually configured satellites
as well as the prospect for possible on-orbit servicing for satellites makes
the idea of realizing an in-orbit factory promising. In this paper, we present
a novel approach to an in-orbit factory of small satellites covering a digital
process twin, AI-based fault detection, and teleoperated robot-control, which
are being researched as part of the "AI-enabled Cyber-Physical In-Orbit
Factory" project. In addition to the integration of modern automation and
Industry 4.0 production approaches, the question of how artificial intelligence
(AI) and learning approaches can be used to make the production process more
robust, fault-tolerant and autonomous is addressed. This lays the foundation
for a later realisation of satellite production in space in the form of an
in-orbit factory. Central aspect is the development of a robotic AIT (Assembly,
Integration and Testing) system where a small satellite could be assembled by a
manipulator robot from modular subsystems. Approaches developed to improving
this production process with AI include employing neural networks for optical
and electrical fault detection of components. Force sensitive measuring and
motion training helps to deal with uncertainties and tolerances during
assembly. An AI-guided teleoperated control of the robot arm allows for human
intervention while a Digital Process Twin represents process data and provides
supervision during the whole production process. Approaches and results towards
automated satellite production are presented in detail.
