'''
This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
PM4Py is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
PM4Py is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with PM4Py. If not, see <https://www.gnu.org/licenses/>.
'''
from typing import List, Tuple
[docs]def cycle_time(events: List[Tuple[float, float]], num_instances: int) -> float:
"""
Computes the cycle time given a list of events (having a start and a complete timestamp)
and the number of instances of the 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
---------------
events
List of events (each event is a tuple having the start and the complete timestamp)
num_instances
Number of instances of the log
Returns
---------------
cycle_time
Cycle time
"""
events = sorted(events, key=lambda x: (x[0], x[1]))
st = events[0][0]
et = events[0][1]
production_time = 0
for i in range(1, len(events)):
this_st = events[i][0]
this_et = events[i][1]
if this_st > et:
production_time += (et - st)
st = this_st
et = max(et, this_et)
return production_time / num_instances