Example Reconstruction

A concrete example of how a fragmented operational event history becomes a sealed, reproducible chain.

Scenario

A robotics assembly cell reports actuator state transitions from three systems: PLC telemetry, operator workstation logs, and quality inspection records.

Timestamps drift. Event schemas differ. Revision identifiers are inconsistent. No single system preserves full context.

Raw intake

PLC Telemetry
14:02:11 ACTUATOR_A → EXTEND
14:02:14 ACTUATOR_A → RETRACT
Operator Log
Job ID 7421 initiated
Manual override triggered
Quality Record
Revision 3.2 applied
Inspection pass recorded
Observed Issues
  • Timestamp drift
  • Non-uniform identifiers
  • Missing cross-reference keys

Canonical envelope normalization

Each raw record is transformed into a canonical envelope: unified timestamp, source identifier, schema version, and structured payload.

{ event_id: "e1032", source: "plc.telemetry", timestamp: "2026-04-12T14:02:11Z", revision: "3.2", payload: { actuator: "A", state: "EXTEND" } }

Event chain construction

Each envelope is hashed. The hash of the prior event is embedded in the next. Order is explicit. Mutation invalidates the sequence.

e1032 → hash: a94f... e1033 → prev_hash: a94f... e1034 → prev_hash: b221...

Deterministic reconstruction

From the ordered chain, system state at any point in time can be reconstructed. Actuator state, job context, and revision lineage are derived from history.

Given the same chain input, reconstruction output is identical across environments.

Independent verification

The final bundle contains the full event sequence and hash lineage. A third party can validate structural integrity without access to the source systems.