pm4py.statistics.traces.cycle_time.log package¶
Submodules¶
pm4py.statistics.traces.cycle_time.log.get module¶

class
pm4py.statistics.traces.cycle_time.log.get.
Parameters
(value)[source]¶ Bases:
enum.Enum
An enumeration.

START_TIMESTAMP_KEY
= 'pm4py:param:start_timestamp_key'¶

TIMESTAMP_KEY
= 'pm4py:param:timestamp_key'¶


pm4py.statistics.traces.cycle_time.log.get.
apply
(log_or_trace: Union[pm4py.objects.log.obj.Trace, pm4py.objects.log.obj.EventLog], parameters: Optional[Dict[str, Any]] = None) → float[source]¶ Computes the cycle time starting from an event log or a trace object
The definition that has been followed is the one proposed in: https://www.presentationeze.com/presentations/leanmanufacturingjustintime/leanmanufacturingjustintimefulldetails/processcycletimeanalysis/calculatecycletime/#:~:text=Cycle%20time%20%3D%20Average%20time%20between,is%2024%20minutes%20on%20average.
So: Cycle time = Average time between completion of units.
Example taken from the website: Consider a manufacturing facility, which is producing 100 units of product per 40 hour week. The average throughput rate is 1 unit per 0.4 hours, which is one unit every 24 minutes. Therefore the cycle time is 24 minutes on average.
 Parameters
log_or_trace – Log or trace
parameters – Parameters of the algorithm, including:  Parameters.START_TIMESTAMP_KEY => the attribute acting as start timestamp  Parameters.TIMESTAMP_KEY => the attribute acting as timestamp
 Returns
Cycle time
 Return type
cycle_time