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EnergyEfficiencyEvents¤

Track energy efficiency metrics against production and machine state.

Module: ts_shape.events.energy.efficiency_tracking Guide: Production Guide

When to Use¤

Use to track energy efficiency over time and identify waste. Detects energy consumed during idle periods and compares efficiency across shifts or production runs. Essential for continuous improvement programs targeting energy reduction.

Quick Example¤

from ts_shape.events.energy.efficiency_tracking import EnergyEfficiencyEvents

tracker = EnergyEfficiencyEvents(
    df=production_df,
    timestamp_col="timestamp",
    value_col="power_kw"
)

# Rolling energy efficiency (output per kWh)
trend = tracker.efficiency_trend(
    production_col="units_produced", window="1D"
)

# Detect energy waste during idle periods
waste = tracker.idle_energy_waste(
    state_col="machine_state", idle_value="IDLE", window="1H"
)
print(f"Total idle waste: {waste['waste_kwh'].sum():.1f} kWh")

# Specific energy consumption per period
sec = tracker.specific_energy_consumption(
    production_col="units_produced", window="1D"
)

# Compare efficiency across shifts
comparison = tracker.efficiency_comparison(
    group_col="shift", production_col="units_produced"
)

Key Methods¤

Method Purpose Returns
efficiency_trend() Rolling energy efficiency over time DataFrame with efficiency (units/kWh) per window
idle_energy_waste() Energy consumed during idle periods DataFrame of idle intervals with wasted energy
specific_energy_consumption() SEC (kWh per unit) per period DataFrame with SEC per window
efficiency_comparison() Compare efficiency across groups DataFrame with efficiency stats per group

Tips & Notes¤

Track idle waste to find quick wins

idle_energy_waste() often reveals the lowest-hanging fruit for energy savings. Machines left running during breaks or changeovers can account for 10-20% of total consumption.

Related modules

See Also¤