pm4py.stats.get_cycle_time#
- pm4py.stats.get_cycle_time(log: EventLog | DataFrame, activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') float[source]#
Calculates the cycle time of the event log.
The definition that has been followed is the one proposed in: https://www.presentationeze.com/presentations/lean-manufacturing-just-in-time/lean-manufacturing-just-in-time-full-details/process-cycle-time-analysis/calculate-cycle-time/#:~: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 – Log object
activity_key (
str) – attribute to be used for the activitytimestamp_key (
str) – attribute to be used for the timestampcase_id_key (
str) – attribute to be used as case identifier
- Return type:
float
import pm4py cycle_time = pm4py.get_cycle_time(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')