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WarmUpCoolDownEvents¤

Detect and characterize warm-up and cool-down curves for ovens, extruders, molds, hydraulic systems.

Module: ts_shape.events.engineering.warmup_analysis
Guide: Process Engineering

When to Use¤

Use for thermal equipment (ovens, extruders, molds) where warm-up and cool-down phases impact production planning and energy consumption. Tracks warm-up consistency over time to detect degrading heating elements or insulation, and measures time-to-target for scheduling.

Quick Example¤

from ts_shape.events.engineering.warmup_analysis import WarmUpCoolDownEvents

analyzer = WarmUpCoolDownEvents(
    df=oven_data,
    uuid="oven_temperature_zone1"
)

# Detect warm-up intervals (rising at least 50 deg over 1+ min)
warmups = analyzer.detect_warmup(min_rise=50.0, min_duration="1m")

# Detect cool-down intervals
cooldowns = analyzer.detect_cooldown(min_fall=30.0, min_duration="1m")

# Check consistency of warm-up curves across days
consistency = analyzer.warmup_consistency(
    min_rise=50.0,
    min_duration="1m"
)

# Time to reach 180C operating temperature
time_to_temp = analyzer.time_to_target(
    target_value=180.0,
    direction="rising"
)

Key Methods¤

Method Purpose Returns
detect_warmup(min_rise, min_duration='1m') Warm-up interval detection DataFrame of warm-up events
detect_cooldown(min_fall, min_duration='1m') Cool-down interval detection DataFrame of cool-down events
warmup_consistency(min_rise, min_duration='1m') Warm-up curve consistency DataFrame with consistency metrics
time_to_target(target_value, direction='rising') Time to reach a target value DataFrame with time-to-target

Tips & Notes¤

Track warm-up consistency for predictive maintenance

A gradually increasing time-to-target across weeks indicates degrading heating elements, fouled heat exchangers, or deteriorating insulation. Plot warmup_consistency() output over time to set up early maintenance alerts.

Related modules

See Also¤