  Rotary Indexing Machines (RIMs) are widely used in manufacturing due to their
ability to perform multiple production steps on a single product without manual
repositioning, reducing production time and improving accuracy and consistency.
Despite their advantages, little research has been done on diagnosing faults in
RIMs, especially from the perspective of the actual production steps carried
out on these machines. Long downtimes due to failures are problematic,
especially for smaller companies employing these machines. To address this gap,
we propose a diagnosis algorithm based on the product perspective, which
focuses on the product being processed by RIMs. The algorithm traces the steps
that a product takes through the machine and is able to diagnose possible
causes in case of failure. We also analyze the properties of RIMs and how these
influence the diagnosis of faults in these machines. Our contributions are
three-fold. Firstly, we provide an analysis of the properties of RIMs and how
they influence the diagnosis of faults in these machines. Secondly, we suggest
a diagnosis algorithm based on the product perspective capable of diagnosing
faults in such a machine. Finally, we test this algorithm on a model of a
rotary indexing machine, demonstrating its effectiveness in identifying faults
and their root causes.
