PartProductionEvents

Quantities per part number per window, per day and in total, from a part-number string signal and a production counter (value_integer).

ts_shape.events.production.part_tracking · Production guide · API reference

Example

import numpy as np
import pandas as pd
import ts_shape
from ts_shape.events.production.part_tracking import PartProductionEvents

t = pd.date_range("2024-01-01 06:00", periods=480, freq="1min")
df = pd.concat([
    ts_shape.make_id_signal("part_id", ["PN-100", "PN-200", "PN-100"], hold=160, freq="1min", start="2024-01-01 06:00"),
    pd.DataFrame({"systime": t, "uuid": "part_counter", "value_integer": np.arange(480) % 200}),  # resets
], ignore_index=True)

pt = PartProductionEvents(df)
result = pt.production_by_part(part_id_uuid="part_id", counter_uuid="part_counter", window="1h").head()
print(result[["start", "part_number", "quantity", "resets"]])
totals = pt.production_totals(part_id_uuid="part_id", counter_uuid="part_counter")
resets = pt.detect_resets(part_id_uuid="part_id", counter_uuid="part_counter")

Methods

Method	Returns
production_by_part(part_id_uuid, counter_uuid, window='1h')	per window and part: start, part_number, quantity, first_count, last_count (+ resets)
daily_production_summary(part_id_uuid, counter_uuid)	per date and part: total_quantity, hours_active (+ resets)
production_totals(part_id_uuid, counter_uuid, start_date=None, end_date=None)	per part: total_quantity, days_produced (+ resets)
detect_resets(part_id_uuid, counter_uuid)	one row per counter drop: time, part_number, count_before, count_after, drop

Notes

• Counters often reset at a shift change, part change or controller restart. With handle_resets=True (default) the quantity is the sum of per-reading increments, a drop counts as a reset that contributes the new counter value, and resets counts resets per group.
• handle_resets=False reports max(0, last_count - first_count) per group, so a window with a reset loses its production.