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OEECalculator¤

Calculate Overall Equipment Effectiveness from timeseries signals: Availability x Performance x Quality.

Module: ts_shape.events.production.oee_calculator Guide: OEE Analytics

When to Use¤

Use for daily OEE reporting. Combines availability (from machine state), performance (from part counters vs ideal cycle time), and quality (from good/reject counters) into the standard OEE metric. World-class OEE is typically 85% or above; this module helps identify which of the three factors is the biggest loss.

Quick Example¤

from ts_shape.events.production.oee_calculator import OEECalculator
import pandas as pd
import numpy as np

df = pd.DataFrame({
    "timestamp": pd.date_range("2024-01-01 06:00", periods=480, freq="1min"),
    "machine_running": [True]*400 + [False]*30 + [True]*50,
    "part_counter": np.arange(1, 481),
    "reject_counter": np.cumsum(np.random.choice([0, 1], size=480, p=[0.97, 0.03])),
})

oee = OEECalculator(df, timestamp_column="timestamp")
availability = oee.calculate_availability(run_state_uuid="machine_running")
performance = oee.calculate_performance(counter_uuid="part_counter", ideal_cycle_time="55s")
quality = oee.calculate_quality(total_uuid="part_counter", reject_uuid="reject_counter")
result = oee.calculate_oee(
    run_state_uuid="machine_running",
    counter_uuid="part_counter",
    ideal_cycle_time="55s",
)
print(f"OEE: {result['oee']:.1%}")

Key Methods¤

Method Purpose Returns
calculate_availability(run_state_uuid) Compute availability ratio from run/idle state signal Float between 0.0 and 1.0
calculate_performance(counter_uuid, ideal_cycle_time) Compute performance ratio: actual output vs theoretical maximum at ideal cycle time Float between 0.0 and 1.0
calculate_quality(total_uuid, reject_uuid) Compute quality ratio: good parts divided by total parts produced Float between 0.0 and 1.0
calculate_oee(run_state_uuid, counter_uuid, ideal_cycle_time) Compute full OEE as Availability x Performance x Quality with daily breakdown Dict with oee, availability, performance, quality, and daily DataFrame

Tips & Notes¤

Validate each factor independently

Always check availability, performance, and quality separately before looking at the combined OEE number. A single factor can mask improvement in the others.

Related modules

See Also¤