from dream.simulation.imports import Machine, Source, Exit, Part, ShiftScheduler
from dream.simulation.Globals import runSimulation
#define the objects of the model
S=Source('S1','Source',interarrivalTime={'distributionType':'Fixed','mean':0.5}, entity='Dream.Part')
M=Machine('M1','Machine', processingTime={'distributionType':'Fixed','mean':3})
E=Exit('E1','Exit')
# create a repeated shift pattern
shiftPattern=[]
i = 0
while i<100:
shiftPattern.append([i,i+5])
i+=10
print shiftPattern
#create the shift
SS=ShiftScheduler(victim=M, shiftPattern=shiftPattern)
#define predecessors and successors for the objects
S.defineRouting(successorList=[M])
M.defineRouting(predecessorList=[S],successorList=[E])
E.defineRouting(predecessorList=[M])
def main(test=0):
# add all the objects in a list
objectList=[S,M,E,SS]
# set the length of the experiment
maxSimTime=100.0
# call the runSimulation giving the objects and the length of the experiment
from dream.simulation.imports import Machine, Source, Exit, Part, Repairman, Queue, Failure
from dream.simulation.Globals import runSimulation
#define the objects of the model
R = Repairman('R1', 'Bob')
S = Source('S1',
'Source',
interArrivalTime={'Fixed': {
'mean': 0.5
}},
entity='Dream.Part')
M1 = Machine('M1', 'Machine1', processingTime={'Fixed': {'mean': 0.25}})
Q = Queue('Q1', 'Queue')
M2 = Machine('M2', 'Machine2', processingTime={'Fixed': {'mean': 1.5}})
E = Exit('E1', 'Exit')
#create failures
F1 = Failure(victim=M1,
distribution={
'TTF': {
'Fixed': {
'mean': 60.0
}
},
'TTR': {
'Fixed': {
'mean': 5.0
}
}
},
repairman=R)
F2 = Failure(victim=M2,
from dream.simulation.imports import Machine, Source, Exit, Part, G, Repairman, Queue, Failure
from dream.simulation.imports import simulate, activate, initialize
#define the objects of the model
R=Repairman('R1', 'Bob')
S=Source('S1','Source', interarrivalTime={'distributionType':'Fixed','mean':0.5}, entity='Dream.Part')
M1=Machine('M1','Machine1', processingTime={'distributionType':'Fixed','mean':0.25})
Q=Queue('Q1','Queue')
M2=Machine('M2','Machine2', processingTime={'distributionType':'Fixed','mean':1.5})
E=Exit('E1','Exit')
#create failures
F1=Failure(victim=M1, distribution={'distributionType':'Fixed','MTTF':60,'MTTR':5}, repairman=R)
F2=Failure(victim=M2, distribution={'distributionType':'Fixed','MTTF':40,'MTTR':10}, repairman=R)
G.ObjList=[S,M1,M2,E,Q] #add all the objects in G.ObjList so that they can be easier accessed later
G.MachineList=[M1,M2]
G.ObjectInterruptionList=[F1,F2] #add all the objects in G.ObjList so that they can be easier accessed later
#define predecessors and successors for the objects
S.defineRouting([M1])
M1.defineRouting([S],[Q])
Q.defineRouting([M1],[M2])
M2.defineRouting([Q],[E])
E.defineRouting([M2])
def main():
initialize() #initialize the simulation (SimPy method)
#initialize all the objects
from dream.simulation.imports import Machine, Source, Exit, Part, Frame, Assembly, Failure
from dream.simulation.Globals import runSimulation
#define the objects of the model
Frame.capacity = 4
Sp = Source('SP',
'Parts',
interArrivalTime={'Fixed': {
'mean': 0.5
}},
entity='Dream.Part')
Sf = Source('SF',
'Frames',
interArrivalTime={'Fixed': {
'mean': 2
}},
entity='Dream.Frame')
M = Machine('M', 'Machine', processingTime={'Fixed': {'mean': 0.25}})
A = Assembly('A', 'Assembly', processingTime={'Fixed': {'mean': 2}})
E = Exit('E1', 'Exit')
F = Failure(victim=M,
distribution={
'TTF': {
'Fixed': {
'mean': 60.0
}
},
'TTR': {
'Fixed': {
'mean': 5.0
part.machineId=self.id #create an attribute to the obtained part and give it the value of the object's id
return activeEntity #return the entity obtained
#the custom exit
class CountingExit(Exit):
def getEntity(self):
activeEntity=Exit.getEntity(self) #call the parent method to get the entity
#check the attribute and update the counters accordingly
if activeEntity.machineId=='M1':
G.NumM1+=1
elif activeEntity.machineId=='M2':
G.NumM2+=1
return activeEntity #return the entity obtained
#define the objects of the model
S=Source('S','Source', interarrivalTime={'distributionType':'Fixed','mean':0.5}, entity='Dream.Part')
Q=SelectiveQueue('Q','Queue', capacity=infinity)
M1=Milling('M1','Milling1', processingTime={'distributionType':'Fixed','mean':0.25})
M2=Milling('M2','Milling2', processingTime={'distributionType':'Fixed','mean':0.25})
E=CountingExit('E1','Exit')
F=Failure(victim=M1, distribution={'distributionType':'Fixed','MTTF':60,'MTTR':5})
G.ObjList=[S,Q,M1,M2,E] #add all the objects in G.ObjList so that they can be easier accessed later
G.ObjectInterruptionList=[F] #add all the objects in G.ObjList so that they can be easier accessed later
#create the global counter variables
G.NumM1=0
G.NumM2=0
from dream.simulation.imports import Machine, Source, Exit, Part, Frame, Assembly, Failure
from dream.simulation.Globals import runSimulation
#define the objects of the model
Frame.capacity=4
Sp=Source('SP','Parts', interArrivalTime={'Fixed':{'mean':0.5}}, entity='Dream.Part')
Sf=Source('SF','Frames', interArrivalTime={'Fixed':{'mean':2}}, entity='Dream.Frame')
M=Machine('M','Machine', processingTime={'Fixed':{'mean':0.25}})
A=Assembly('A','Assembly', processingTime={'Fixed':{'mean':2}})
E=Exit('E1','Exit')
F=Failure(victim=M, distribution={'TTF':{'Fixed':{'mean':60.0}},'TTR':{'Fixed':{'mean':5.0}}})
#define predecessors and successors for the objects
Sp.defineRouting([A])
Sf.defineRouting([A])
A.defineRouting([Sp,Sf],[M])
M.defineRouting([A],[E])
E.defineRouting([M])
def main(test=0):
# add all the objects in a list
objectList=[Sp,Sf,M,A,E,F]
# set the length of the experiment
maxSimTime=1440.0
# call the runSimulation giving the objects and the length of the experiment
runSimulation(objectList, maxSimTime)
# calculate metrics
working_ratio=(A.totalWorkingTime/maxSimTime)*100
from dream.simulation.imports import Source, Queue, Machine, Exit
from dream.simulation.Globals import runSimulation
# This is the baby step to building a complicated model of the behavior
# of a fleet of systems with multiple stakeholders.
# The baby step includes:
# A source to generate students
# A Queue for students to wait for a flight
# A machine (aircraft) to give students time
# An exit for graduated students
# The source is API for Aviation Preflight Indocrination
API = Source('API', 'Source', interArrivalTime={'Fixed': {'mean': 0.5}},
entity='Dream.Part')
RR = Queue('ReadyRoom', 'Queue', capacity=1)
AC = Machine('AC1', 'Machine', processingTime={'Fixed': {'mean': 0.25}})
E = Exit('The Fleet', 'The Fleet')
# The predecessors and successors for the objects
API.defineRouting(successorList=[RR])
RR.defineRouting(predecessorList=[API], successorList=[AC])
AC.defineRouting(predecessorList=[RR], successorList=[E])
E.defineRouting(predecessorList=[AC])
def main(test=0):
# add all the objects in a list
objectList=[API, RR, AC, E]
# set the length of the experiment
maxSimTime = 1440.0
# call the runSimulation giving the objects and the length of the
# experiment
from dream.simulation.imports import Source, Queue, Machine, Exit
from dream.simulation.Globals import runSimulation
# This is the baby step to building a complicated model of the behavior
# of a fleet of systems with multiple stakeholders.
# The baby step includes:
# A source to generate students
# A Queue for students to wait for a flight
# A machine (aircraft) to give students time
# An exit for graduated students
# The source is API for Aviation Preflight Indocrination
API = Source('API',
'Source',
interArrivalTime={'Fixed': {
'mean': 0.5
}},
entity='Dream.Part')
RR = Queue('ReadyRoom', 'Queue', capacity=1)
AC = Machine('AC1', 'Machine', processingTime={'Fixed': {'mean': 0.25}})
E = Exit('The Fleet', 'The Fleet')
# The predecessors and successors for the objects
API.defineRouting(successorList=[RR])
RR.defineRouting(predecessorList=[API], successorList=[AC])
AC.defineRouting(predecessorList=[RR], successorList=[E])
E.defineRouting(predecessorList=[AC])
def main(test=0):
# add all the objects in a list