Overall Equipment Effectiveness Breakdown and Loss Modeling
Calculate OEE metrics and model manufacturing loss factors across availability, performance, and quality dimensions.
Use this template when a production line is underperforming against standard targets and you need a mathematical breakdown of operating losses. It converts raw shop-floor run logs into clear availability, performance, and quality loss figures.
Role: Principal Manufacturing Operations Engineer specializing in total productive maintenance and line throughput optimization.
Context
- Manufacturing facility: {{plant_facility}}
- Target line: {{production_line_name}}
- Planned operational duration: {{planned_operating_time_hours}} hours
- Actual units produced: {{actual_output_units}} units
- Ideal cycle standard: {{ideal_cycle_time_seconds}} seconds per unit
- Defective or rework units: {{scrap_rework_units}} units
- Total recorded unplanned stops: {{unplanned_downtime_minutes}} minutes
Task
Provide a rigorous mathematical breakdown of Overall Equipment Effectiveness (OEE) and deliver a structured causal loss analysis isolating the primary mechanical, operational, and quality drivers reducing line performance.
Method
- Calculate net operating time by subtracting {{unplanned_downtime_minutes}} from the total {{planned_operating_time_hours}} converted to minutes.
- Compute the Availability rate as the ratio of actual operating time to planned run duration.
- Calculate the ideal operating run time required for {{actual_output_units}} using {{ideal_cycle_time_seconds}}.
- Determine the Performance rate by evaluating ideal run time against actual operating time, quantifying speed loss.
- Compute the Quality rate by dividing sound parts ({{actual_output_units}} minus {{scrap_rework_units}}) by total units produced.
- Multiply Availability, Performance, and Quality factors to derive final composite OEE.
- Model top loss categories into equivalent lost units and idle machine hours.
- Formulate ranked engineering recommendations targeting the greatest mathematical variance.
Constraints
- All mathematical calculations MUST display explicit formulas, intermediate values, and percentage conversions.
- Results MUST NOT round intermediary calculation steps before the final percentage outputs.
- State any baseline assumptions regarding micro-stops or changeover classifications.
- Recommendations must focus solely on direct physical and operational drivers.
Output format
- Section 1: Core Metric Equations and Values (Availability, Performance, Quality, Final OEE in tabular format)
- Section 2: Six Big Losses Quantification (Lost time in minutes and lost output units per category)
- Section 3: Engineering Diagnosis (Summary of primary bottleneck within 250 words)
- Section 4: Prioritized Action Plan (3 to 5 corrective actions with expected theoretical gain)
Self-review
- Confirm that the product of Availability, Performance, and Quality yields the exact OEE reported.
- Check that scrap plus sound units equals the declared actual output value.
- Verify all operational units are converted consistently between hours, minutes, and seconds.
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
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Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
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