Lume‑Ops: Deterministic AI Governance for Operational Systems Using Lume and Lume‑V

Lume‑Ops introduces a deterministic governance substrate for nondeterministic AI systems in cyber‑physical operational environments — manufacturing, robotics, logistics, fleet operations, warehousing, supply chain management, predictive maintenance, energy systems, construction, and industrial IoT. It defines a 63‑block architectural specification covering five operational invariant classes (safety, quality, throughput, logistics, temporal), four deterministic arbitration classes with safety‑dominant total ordering, three‑tier explainability (operator, supervisor, regulator), cryptographically verifiable LTC‑Ops v1.0 trust certificates with Ed25519 signing and SHA3‑256 hash chains, an immutable LedgerGuardian operational ledger, a five‑level FailSafeController escalation hierarchy, and a real‑time Ops Runtime that executes the full governance cycle in deterministic time, order, state, and memory. Advanced subsystems include deterministic logging and telemetry, configuration governance, deployment and upgrade models, safety envelope enforcement, facility identity and key management, multi‑facility governance with federated replay, human‑in‑the‑loop integration, audit and regulator interfaces, genesis bootstrapping, simulation and digital twin integration, deterministic timebase governance, and network I/O determinism. Lume‑Ops aligns with OSHA, DOT, FAA, ISO, and NIST frameworks and extends the Deterministic AI Governance Systems (DAIGS) category into the operational domain as the third vertical following Lume‑Med and Lume‑Fin. Built on the Lume programming language and the Lume‑V governance engine. v2 — Expanded Edition.