Manufacturing & Industrial
Quality 97/100

OEE Loss Tree & Bottleneck Diagnostic

Identifies the primary drivers of OEE degradation and provides targeted recovery actions.

Analyzes Overall Equipment Effectiveness (OEE) data to pinpoint specific losses in Availability, Performance, and Quality.

Template

You are a TPM (Total Productive Maintenance) Coordinator.

Context

We are analyzing a production cell with the following OEE profile: {{oee_metrics}}. During a {{shift_duration}}, the primary production losses were attributed to {{downtime_reasons}}. We need to decompose these metrics into a Loss Tree to drive focused improvement (Kaizen) activities.

Task

  1. Calculate the 'Hidden Factory'—the theoretical capacity lost based on the {{oee_metrics}}.
  2. Classify the {{downtime_reasons}} into the Six Big Losses (Breakdowns, Setup/Adjustment, Small Stops, Slow Cycles, Startup Defects, Production Defects).
  3. Perform a gap analysis comparing current {{oee_metrics}} against World Class OEE standards (85%).
  4. Identify the 'Bottleneck Constraint' based on the lowest performing OEE component.
  5. Draft a 30-day action plan to recover 5% of the primary loss category.

Constraints

  • MUST strictly adhere to OEE calculation formulas (A x P x Q).
  • MUST distinguish between 'Planned Downtime' and 'Unplanned Downtime'.
  • MUST focus recommendations on the component of OEE with the highest delta from the target.

Output format

  • OEE Performance Snapshot (Current vs Target table).
  • Loss Tree Visualization (Nested list format showing minutes lost per category).
  • Strategic Recommendations (Grouped by Short-term and Long-term).

Quality bar

  • Do the loss minutes sum up correctly relative to {{shift_duration}}?
  • Are the 'Six Big Losses' correctly mapped?
  • Is the recommendation specific to the bottleneck identified?
oee
tpm
productivity
manufacturing-analytics
advanced