Use case
Use case3 min readBy The Data Workers Team

Live production monitoring data, run by agents

MES and machine data arrive with gaps and different clocks, so OEE dashboards are wrong during the shift. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. MES and machine data arrive with gaps and different clocks, so OEE dashboards are wrong during the shift.
  • •What changes. Agents stream machine events, align clocks and verify OEE before every shift huddle.
  • •What stays with your people. Alarms sent to operators: they change line decisions.
  • •The result. Shift huddles run on verified OEE.

The problem today

MES and machine data arrive with gaps and different clocks, so OEE dashboards are wrong during the shift.

What changes with Data Workers

Agents stream machine events, align clocks and verify OEE before every shift huddle.

The workflow: Real-Time Streaming agent (register_stream_schema) → Quality Monitoring agent (get_anomalies) → Incident Debugging agent (diagnose_incident) → Autonomous Data-Conductor (verify_data).
Fig. 1:The workflow: Real-Time Streaming agent (register_stream_schema) → Quality Monitoring agent (get_anomalies) → Incident Debugging agent (diagnose_incident) → Autonomous Data-Conductor (verify_data).

The workflow, step by step

  1. 1.The Real-Time Streaming agent calls register_stream_schema and streams machine events.
  2. 2.The Quality Monitoring agent calls get_anomalies and catches gaps.
  3. 3.The Incident Debugging agent calls diagnose_incident and traces connectivity issues.
  4. 4.The Autonomous Data-Conductor calls verify_data and verifies OEE.

The impact metrics we move

  • •Machine gap caught: from about 2 hours to minutes
  • •OEE verified: from about 8 hours to 15-20 min
  • •Connectivity issue traced: from about a day to under 1 h
Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.
Fig. 2:Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.

What goes on autopilot

  • •Machine streams are checked continuously, so OEE is right during the shift.
  • •Clocks align across systems, so events line up.

Where your people stay in charge

Alarms sent to operators always go to a named approver, because they change line decisions. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. Live OEE for one line.
  • •First week. Agents run at L1, observing only, and show the fixes they would have made, with receipts.
  • •By week two. The routine work above runs on its own; anything sensitive stays with a named approver.
  • •At day 30. We review the impact metrics against your baseline:
  • •Machine gap caught: from about 2 hours to minutes
  • •OEE verified: from about 8 hours to 15-20 min
  • •Connectivity issue traced: from about a day to under 1 h
  • •Cost. Start with a pilot ($7,500 one-time, credited in full against the first year). Scale is from $1,000 a month and Enterprise from $3,000 a month, billed annually, with unlimited seats, no usage meter and no markup on model spend. See pricing.

Related: The manufacturing hub · The full team playbook

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