Explainable Causal Reinforcement Learning for circular manufacturing supply chains during mission-critical recovery windows

Explainable Causal Reinforcement Learning for circular manufacturing supply chains during mission-critical recovery windows Introduction: A Learning Journey Through Broken Supply Chains My journey into this specialized intersection of AI began during a particularly challenging consulting project in early 2023. I was working with an automotive manufacturer whose just-in-time supply chain had collapsed when a critical semiconductor supplier experienced a factory fire. The recovery window was measured in days, not weeks, and traditional optimization algorithms kept suggesting solutions that looked perfect mathematically but failed catastrophically in practice. They would recommend rerouting through suppliers that appeared available in the database but were actually allocation-constrained, or suggest material substitutions that violated unmodeled regulatory constraints. While exploring reinforcement learning solutions for dynamic resource allocation, I discovered something fundamental: sta