HEAVY VEHICLE / OFF-HIGHWAY · TELEMETRY NORMALIZATION
16,908 confirmed mappings·18 OEM families·14 protocols·99% field coverage
Forge turns raw Caterpillar tags into one clean, governed schema your AI agent already understands. One MCP call, no per-vehicle integration project.
Cat engines and mining trucks broadcast everything as J1939 SPNs on the CAN bus, SPN 100 (oil pressure), SPN 175 (oil temp), plus proprietary parameter groups that VIMS and third-party telematics each decode differently.
Typical Caterpillar equipment communicates over J1939 (CAN), HTTP / REST. Each firmware revision, model line and integrator names the same physical quantity differently, so every AI or analytics project pays the integration tax again, the tax that cancels 40% of industrial AI deployments before they ship.
Forge normalizes Caterpillar telemetry into Forge's canonical field set, the same 366 canonical fields used across all 18 manufacturers. Point Forge at the vehicle, pass oem: "caterpillar", and spindle speed is spindle_speed_rpm whether it came from a Caterpillar controller or anything else on the floor.
Confirmed canonical fields your agent gets from Caterpillar vehicles, drawn from Forge's 16,908-mapping corpus:
| Raw tag in | Canonical field out | Meaning | |
|---|---|---|---|
| SPN_100: 55 | → | vehicle.engine.oil_pressure: 55 | engine oil pressure (psi) |
| SPN_175: 98 | → | vehicle.engine.oil_temp: 98 | engine oil temp (°C) |
| SPN_103: 78000 | → | vehicle.turbocharger.rpm: 78000 | turbo speed |
| SPN_1636: "P0087" | → | vehicle.dtc_description: "Fuel rail pressure low" | active DTC |
No SDK, no per-tag mapping, no historian project. Connect the MCP server and normalize live Caterpillar data:
Unknown tags never get force-mapped. Fields below the confidence floor abstain rather than guess, so your agent never acts on a bad reading.