setup_time_tracking

setup_time_tracking

Setup/changeover time tracking for SMED analysis.

Track setup durations to support Single-Minute Exchange of Die improvement: - Setup event durations - Setup time by product transition - Setup statistics - Setup time trends

SetupTimeEvents

SetupTimeEvents(
    dataframe: DataFrame,
    *,
    time_column: str = "systime",
    shift_definitions: (
        dict[str, tuple[str, str]] | None
    ) = None,
    event_uuid: str = "prod:setup_time"
)

Bases: Base

Track and analyze setup/changeover durations.

Each UUID represents one signal: - run_state_uuid: machine state signal containing a setup indicator value - part_id_uuid: part number / product type signal (optional)

Merge keys: [date, shift] for shift-level, [period] for trend data, [from_product, to_product] for product transition analysis.

Durations are reported in seconds (*_seconds); the *_minutes columns are kept as a convenience.

Pipeline example::

setup = SetupTimeEvents(df)
durations = setup.setup_durations('machine_state', setup_value='Setup')
# → merge with ShiftReportEvents.shift_production() on [date, shift]
stats = setup.setup_statistics('machine_state')
# → standalone KPI reporting

Example usage

tracker = SetupTimeEvents(df)

List all setup events

events = tracker.setup_durations(run_state_uuid='machine_state')

Setup time by product transition

by_product = tracker.setup_by_product( run_state_uuid='machine_state', part_id_uuid='part_number', )

Initialize the setup-time tracker.

Parameters:

Name	Type	Description	Default
dataframe	DataFrame	Input DataFrame with timeseries data.	required
time_column	str	Name of timestamp column (default: 'systime').	'systime'
shift_definitions	dict[str, tuple[str, str]] | None	Mapping of shift name to (start, end) times. Default: 3-shift operation (06:00-14:00, 14:00-22:00, 22:00-06:00).	None
event_uuid	str	UUID tagged on derived interval events (the uuid column of :meth:setup_durations; default: 'prod:setup_time').	'prod:setup_time'

setup_durations

setup_durations(
    run_state_uuid: str,
    *,
    setup_value: str = "Setup",
    value_column: str = "value_string",
    production_day: bool = True
) -> pd.DataFrame

List every setup event with duration.

Parameters:

Name	Type	Description	Default
run_state_uuid	str	UUID for machine state signal.	required
setup_value	str	Value that indicates a setup state.	'Setup'
value_column	str	Column containing state values.	'value_string'
production_day	bool	Attribute an overnight shift's post-midnight setups to the shift's start date, so a night shift is one (date, shift) row (default). False groups by raw calendar date, which splits a night shift across two rows.	True

Returns:

Type	Description
DataFrame	DataFrame with columns:
DataFrame	start, end, duration_seconds (float seconds, end - start), uuid (event uuid), source_uuid (run_state_uuid), duration_minutes (convenience: duration_seconds / 60), date, shift

setup_by_product

setup_by_product(
    run_state_uuid: str,
    part_id_uuid: str,
    *,
    setup_value: str = "Setup",
    value_column_state: str = "value_string",
    value_column_part: str = "value_string"
) -> pd.DataFrame

Setup time statistics by product transition (from → to).

Parameters:

Name	Type	Description	Default
run_state_uuid	str	UUID for machine state signal.	required
part_id_uuid	str	UUID for part number / product type signal.	required
setup_value	str	Value indicating setup state.	'Setup'
value_column_state	str	Column containing state values.	'value_string'
value_column_part	str	Column containing part number values.	'value_string'

Returns:

Type	Description
DataFrame	DataFrame with columns:
DataFrame	from_product, to_product, avg_minutes, avg_seconds, min_minutes, min_seconds, max_minutes, max_seconds, count
DataFrame	The *_minutes columns are a convenience (*_seconds / 60).

setup_statistics

setup_statistics(
    run_state_uuid: str,
    *,
    setup_value: str = "Setup",
    value_column: str = "value_string"
) -> pd.DataFrame

Overall setup time statistics.

Parameters:

Name	Type	Description	Default
run_state_uuid	str	UUID for machine state signal.	required
setup_value	str	Value indicating setup state.	'Setup'
value_column	str	Column containing state values.	'value_string'

Returns:

Type	Description
DataFrame	DataFrame (single row) with columns:
DataFrame	total_setups, total_minutes, total_seconds, avg_minutes, avg_seconds, median_minutes, median_seconds, std_minutes, std_seconds, pct_of_available_time
DataFrame	The *_minutes columns are a convenience (*_seconds / 60).
DataFrame	Canonical twin columns: share_of_available_time_pct (after
DataFrame	pct_of_available_time); each holds the same values as the deprecated
DataFrame	column right before it, which is removed in the next major release.

setup_trend

setup_trend(
    run_state_uuid: str,
    *,
    setup_value: str = "Setup",
    value_column: str = "value_string",
    window: str = "1W"
) -> pd.DataFrame

Track setup time trend over time.

Parameters:

Name	Type	Description	Default
run_state_uuid	str	UUID for machine state signal.	required
setup_value	str	Value indicating setup state.	'Setup'
value_column	str	Column containing state values.	'value_string'
window	str	Time window for aggregation (default '1W').	'1W'

Returns:

Type	Description
DataFrame	DataFrame with columns:
DataFrame	start, end, duration_seconds: the period's bin bounds (for the default '1W' the Monday-to-Monday week; period is the pandas bin label, i.e. the week's Sunday)
DataFrame	period, avg_setup_minutes, avg_setup_seconds, setup_count, total_setup_minutes, total_setup_seconds (the *_minutes columns are a convenience)