This ontology captures how CPG goods move from factory gate to retail shelf. It maps the core entities any supply chain team works with daily: orders, shipments, loads, vehicles, drivers, carriers, distribution centers, and the delivery commitments that tie them all together. Critically, it also models the exceptions - delays, breakdowns, temperature breaches, customs holds as first-class entities, because in CPG logistics, exceptions are not edge cases. They are the job.
The scenario is straightforward: a retailer raises a purchase order, the manufacturer produces and ships to a distribution center, the DC receives, consolidates, and dispatches outbound shipments, a carrier picks them up, and a driver delivers within a contractually agreed window. That chain sounds simple. In practice, it breaks constantly - a reefer unit fails at 2am on an outbound lane, a DC is holding 200 pallets because inbound volume has exceeded dock capacity and nothing is moving out, a driver hits his HOS limit 40 miles short of the destination. The ontology is built around exactly these failure modes, not the happy path.
Every relationship was chosen because it enables a specific operational decision. Linking TransportEvent to Shipment lets an AI agent surface at-risk deliveries before a dispatcher even opens his screen. Connecting DistributionCenter to both inbound and outbound Shipments gives a chatbot enough context to detect where freight is stacking up and trigger carrier notifications before a backlog compounds. Tying DeliveryWindow directly to Retailer with penalty rates attached means the system understands commercial consequences, not just timestamps. And grounding Vehicle temperature range against Product storage requirements closes the loop on cold chain compliance automatically. Together, these relationships turn a static data model into something a logistics team can actually reason with.
Ontology URL:
https://microsoft.github.io/Ontology-Playground/#/share/eJzFW82O40hyfpWADG-rAEqzxg7gRQE-VKumpxtTNd2o...
