Examples

Additional examples can be found in the Github repository under simantha/examples.

Single Machine Degradation

The following example implements a single machine that is subject to Markovian degradation.

import random

from simantha import Source, Machine, Sink, System, utils

degradation_matrix = [
    [0.9, 0.1, 0.,  0.,  0. ],
    [0.,  0.9, 0.1, 0.,  0. ],
    [0.,  0.,  0.9, 0.1, 0. ],
    [0.,  0.,  0.,  0.9, 0.1],
    [0.,  0.,  0.,  0.,  1. ]
]

source = Source()
M1 = Machine(
    name='M1',
    cycle_time=1,
    degradation_matrix=degradation_matrix,
    cm_distribution={'geometric': 0.1}
)
sink = Sink()

source.define_routing(downstream=[M1])
M1.define_routing(upstream=[source], downstream=[sink])
sink.define_routing(upstream=[M1])

system = System([source, M1, sink])

random.seed(1)
system.simulate(simulation_time=utils.WEEK)

# Output:
# Simulation finished in 0.34s
# Parts produced: 7963

Parallel Stations

In this example several machines are arranged in parallel to form stations. This arrangement is sometimes referred to as a series-parallel configuration.

from simantha import Source, Machine, Buffer, Sink, System, utils

source = Source()

M1 = Machine('M1', cycle_time=2)
M2 = Machine('M2', cycle_time=2)
station1 = [M1, M2]

B1 = Buffer(capacity=5)

M3 = Machine('M3', cycle_time=3)
M4 = Machine('M4', cycle_time=3)
M5 = Machine('M5', cycle_time=3)
station2 = [M3, M4, M5]

B2 = Buffer(capacity=5)

M6 = Machine('M6', cycle_time=2)
M7 = Machine('M7', cycle_time=2)
station3 = [M6, M7]

sink = Sink()

source.define_routing(downstream=station1)
for machine in station1:
    machine.define_routing(upstream=[source], downstream=[B1])
B1.define_routing(upstream=station1, downstream=station2)
for machine in station2:
    machine.define_routing(upstream=[B1], downstream=[B2])
B2.define_routing(upstream=station2, downstream=station3)
for machine in station3:
    machine.define_routing(upstream=[B2], downstream=[sink])
sink.define_routing(upstream=station3)

objects = [source] + station1 + [B1] + station2 + [B2] + station3 + [sink]
system = System(objects)

system.simulate(simulation_time=utils.WEEK)

# Output:
# Simulation finished in 1.54s
# Parts produced: 10074