  This paper explores supply chain viability through empirical network-level
analysis of supplier reachability under various scenarios. Specifically, this
study investigates the effect of multi-tier random failures across different
scales, as well as intelligent attacks on the global supply chain of medical
equipment, an industry whose supply chain's viability was put under a crucial
test during the COVID-19 pandemic. The global supply chain data was mined and
analyzed from about 45,000 firms with about 115,000 intertwined relationships
spanning across 10 tiers of the backward supply chain of medical equipment.
This complex supply chain network was analyzed at four scales, namely: firm,
country-industry, industry, and country. A notable contribution of this study
is the application of a supply chain tier optimization tool to identify the
lowest tier of the supply chain that can provide adequate resolution for the
study of the supply chain pattern in the medical equipment sector. We also
developed data-driven-tools to identify the thresholds for the breakdown and
fragmentation of the medical equipment supply chain when faced with random
failures, or different intelligent attack scenarios. The novel network analysis
tools utilized in the study can be applied to the study of supply chain
reachability and viability in other industries.
