runtime_accounting

runtime_accounting

Runtime / operating-hours accounting for equipment.

Computes operating-time metrics from a single boolean run signal:

• total run time, idle time and utilization,
• equipment start count and longest continuous run,
• run time per calendar window,
• a cumulative operating-hours meter (like a physical hour meter).

Per-sample duration is the gap to the next sample, summed over True samples -- the same approach as OEEEvents.availability. Per window, each sample's interval is split at the window boundaries, so a run that crosses midnight counts in both days (the ISO 22400-2 time model). This is distinct from DutyCycleEvents (duty percentage and cycle counts): here the focus is absolute run time and an hour-meter reading.

RuntimeAccountingEvents

RuntimeAccountingEvents(
    dataframe: DataFrame,
    run_state_uuid: str,
    *,
    event_uuid: str = "prod:runtime",
    value_column: str = "value_bool",
    time_column: str = "systime"
)

Bases: Base

Operating-hours accounting from one boolean run signal.

Example usage::

rt = RuntimeAccountingEvents(df, run_state_uuid="machine:running")
rt.runtime_summary()
rt.runtime_by_window(window="1D")
rt.operating_hours_meter(window="1h")

Initialize the runtime-accounting analyzer.

Parameters:

Name	Type	Description	Default
dataframe	DataFrame	Input DataFrame with timeseries data.	required
run_state_uuid	str	UUID of the boolean run-state signal (True = running).	required
event_uuid	str	UUID to tag derived events with.	'prod:runtime'
value_column	str	Column holding the boolean run state.	'value_bool'
time_column	str	Name of the timestamp column.	'systime'

run_uuid property

run_uuid: str

Deprecated read-only alias of :attr:run_state_uuid.

runtime_summary

runtime_summary(
    *, max_gap: str | None = None
) -> pd.DataFrame

Overall operating-time summary across the whole dataset.

Parameters:

Name	Type	Description	Default
max_gap	str | None	Optional cap (e.g. "15min"). A gap to the next sample longer than this is treated as a logging outage and excluded, so it does not inflate run/idle time or utilization. Without it, a gap while the last state was running is booked as run time. None (default) applies no cap: every interval between readings, however long, counts toward the preceding state.	None

Returns:

Type	Description
DataFrame	Summary-shape DataFrame (one row) with columns: start, end,
DataFrame	duration_seconds, run_seconds, run_hours, idle_seconds,
DataFrame	start_count, longest_run_seconds, mean_run_seconds,
DataFrame	utilization_pct.

runtime_by_window

runtime_by_window(
    window: str = "1D", *, max_gap: str | None = None
) -> pd.DataFrame

Run time per calendar window.

Each sample's state holds until the next sample; the interval is split at the window boundaries, so each window gets the run and idle time that fell inside it. A start counts in the window of the sample that begins the run. Windows holding a sample or any observed time are reported.

Parameters:

Name	Type	Description	Default
window	str	Resample window (e.g. "1D", "8h").	'1D'
max_gap	str | None	Optional cap (e.g. "15min") excluding a logging gap from run time and utilization (see :meth:runtime_summary). None (default) applies no cap.	None

Returns:

Type	Description
DataFrame	Summary-shape DataFrame with columns: start, end, duration_seconds,
DataFrame	run_seconds, run_hours, start_count, utilization_pct.

operating_hours_meter

operating_hours_meter(
    window: str = "1h", *, max_gap: str | None = None
) -> pd.DataFrame

Cumulative operating-hours meter, sampled per window.

Mirrors a physical equipment hour meter: a monotonically increasing total of run hours. Run time is split at the window boundaries (see :meth:runtime_by_window); every window holding a sample or any observed time is reported, so the meter has no holes.

Parameters:

Name	Type	Description	Default
window	str	Resample window for the meter readings.	'1h'
max_gap	str | None	Optional cap (e.g. "15min") excluding a logging gap from run time so the meter does not advance across an outage. None (default) applies no cap.	None

Returns:

Type	Description
DataFrame	Summary-shape DataFrame with columns: start, end, duration_seconds,
DataFrame	run_seconds, cumulative_run_hours.