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MultiProcessTraceabilityEvents¤

Trace items across a multi-station topology with parallel paths.

Module: ts_shape.events.production.multi_process_traceability Guide: Traceability Guide

When to Use¤

Use for complex manufacturing topologies with parallel process lines, merges, and splits. Tracks items through non-linear routings where a single item may visit multiple stations simultaneously (e.g., sub-assemblies built in parallel then merged). This is the most powerful traceability module, suited for automotive or electronics assembly lines.

Quick Example¤

from ts_shape.events.production.multi_process_traceability import MultiProcessTraceabilityEvents

tracer = MultiProcessTraceabilityEvents(
    df=production_df,
    topology={
        "line_a": ["station-a1", "station-a2"],
        "line_b": ["station-b1", "station-b2"],
        "merge":  ["station-merge"],
        "final":  ["station-final-test"],
    },
    id_uuid="order-id-uuid"
)

# Full timeline across all stations
timeline = tracer.build_timeline()

# Items at multiple stations simultaneously
parallel = tracer.parallel_activity()

# Handover events between stations
handovers = tracer.handover_log()

# Most common routing paths
paths = tracer.routing_paths()

Key Methods¤

Method Purpose Returns
build_timeline() Full timeline across all stations and lines DataFrame
lead_time() End-to-end lead time per item DataFrame
parallel_activity() Detect items at multiple stations simultaneously DataFrame
handover_log() Log of handover events between stations DataFrame
station_statistics() Dwell time statistics per station DataFrame
routing_paths() Frequency of each unique routing path DataFrame

Tips & Notes¤

Define your topology explicitly

Providing a topology dict lets the module distinguish parallel lines from sequential steps. Without it, the module must infer ordering from timestamps alone, which can be ambiguous.

Related modules

See Also¤