from dream.simulation.Globals import runSimulation
# define the objects of the model
S=BatchSource('S','Source',interArrivalTime={'Fixed':{'mean':1.5}}, entity='Dream.Batch', batchNumberOfUnits=100)
Q=Queue('Q','StartQueue',capacity=100000)
BD=BatchDecomposition('BC', 'BatchDecomposition', numberOfSubBatches=4, processingTime={'Fixed':{'mean':1}})
M1=Machine('M1','Machine1',processingTime={'Fixed':{'mean':0.5}})
Q1=LineClearance('Q1','Queue1',capacity=2)
M2=Machine('M2','Machine2',processingTime={'Fixed':{'mean':4}})
BRA=BatchReassembly('BRA', 'BatchReassembly', numberOfSubBatches=4, processingTime={'Fixed':{'mean':0}})
M3=Machine('M3','Machine3',processingTime={'Fixed':{'mean':1}})
E=Exit('E','Exit')
# define the predecessors and successors for the objects
S.defineRouting([Q])
Q.defineRouting([S],[BD])
BD.defineRouting([Q],[M1])
M1.defineRouting([BD],[Q1])
Q1.defineRouting([M1],[M2])
M2.defineRouting([Q1],[BRA])
BRA.defineRouting([M2],[M3])
M3.defineRouting([BRA],[E])
E.defineRouting([M3])
def main(test=0):
# add all the objects in a list
objectList=[S,Q,BD,M1,Q1,M2,BRA,M3,E]
# set the length of the experiment
maxSimTime=1440.0
# call the runSimulation giving the objects and the length of the experiment
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
R.initialize()
for object in G.ObjList:
object.initialize()
for objectInterruption in G.ObjectInterruptionList:
objectInterruption.initialize()
for object in G.InternalProcessList+G.InternalQueueList:
totalParts+=len(object.getActiveObjectQueue())
return totalParts
QB=Queue('QB','QueueBefore', capacity=float("inf"))
Q1=InternalQueue('Q1','Q1', capacity=1)
M1=InternalProcess('M1','M1',processingTime={'Exp':{'mean':1}})
Q2=InternalQueue('Q2','Q2', capacity=1)
M2=InternalProcess('M2','M2',processingTime={'Exp':{'mean':1}})
Q3=InternalQueue('Q3','Q3', capacity=1)
M3=InternalProcess('M3','M3',processingTime={'Exp':{'mean':1}})
QA=Queue('QA','QueueAfter', capacity=float("inf"))
MA=Machine('MA','MachineAfter',processingTime={'Exp':{'mean':1}})
E=Exit('E','Exit')
QB.defineRouting(successorList=[Q1,Q2,Q3])
Q1.defineRouting(predecessorList=[QB],successorList=[M1])
Q2.defineRouting(predecessorList=[QB],successorList=[M2])
Q3.defineRouting(predecessorList=[QB],successorList=[M3])
M1.defineRouting(predecessorList=[Q1],successorList=[QA])
M2.defineRouting(predecessorList=[Q2],successorList=[QA])
M3.defineRouting(predecessorList=[Q3],successorList=[QA])
QA.defineRouting(predecessorList=[M1,M2,M3],successorList=[MA])
MA.defineRouting(predecessorList=[QA],successorList=[E])
E.defineRouting(predecessorList=[MA])
P1=Part('P1','P1',currentStation=QB)
P2=Part('P2','P2',currentStation=QB)
P3=Part('P3','P3',currentStation=QB)
P4=Part('P4','P4',currentStation=QB)
P5=Part('P5','P5',currentStation=QB)
'Fixed': {
'mean': 40.0
}
},
'TTR': {
'Fixed': {
'mean': 10.0
}
}
},
repairman=R)
#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(test=0):
# add all the objects in a list
objectList = [S, M1, M2, E, Q, R, F1, F2]
# 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
blockage_ratio = (M1.totalBlockageTime / maxSimTime) * 100
}})
M1 = Machine('M1', 'Machine1', processingTime={'Fixed': {'mean': 0.5}})
Q1 = LineClearance('Q1', 'Queue1', capacity=2)
M2 = Machine('M2', 'Machine2', processingTime={'Fixed': {'mean': 4}})
BRA = BatchReassembly('BRA',
'BatchReassembly',
numberOfSubBatches=4,
processingTime={'Fixed': {
'mean': 0
}})
M3 = Machine('M3', 'Machine3', processingTime={'Fixed': {'mean': 1}})
E = Exit('E', 'Exit')
# define the predecessors and successors for the objects
S.defineRouting([Q])
Q.defineRouting([S], [BD])
BD.defineRouting([Q], [M1])
M1.defineRouting([BD], [Q1])
Q1.defineRouting([M1], [M2])
M2.defineRouting([Q1], [BRA])
BRA.defineRouting([M2], [M3])
M3.defineRouting([BRA], [E])
E.defineRouting([M3])
def main(test=0):
# add all the objects in a list
objectList = [S, Q, BD, M1, Q1, M2, BRA, M3, E]
# set the length of the experiment
maxSimTime = 1440.0
from dream.simulation.imports import Machine, Source, Exit, Part, Queue, NonStarvingEntry
from dream.simulation.Globals import runSimulation
#define the objects of the model
NS = NonStarvingEntry('NS1', 'Entry', entityData={'_class': 'Dream.Part'})
M1 = Machine('M1', 'Machine1', processingTime={'Exp': {'mean': 1}})
Q2 = Queue('Q2', 'Queue2')
M2 = Machine('M2', 'Machine2', processingTime={'Exp': {'mean': 3}})
Q3 = Queue('Q3', 'Queue3')
M3 = Machine('M3', 'Machine3', processingTime={'Exp': {'mean': 5}})
E = Exit('E1', 'Exit')
#define predecessors and successors for the objects
NS.defineRouting(successorList=[M1])
M1.defineRouting(predecessorList=[NS], successorList=[Q2])
Q2.defineRouting(predecessorList=[M1], successorList=[M2])
M2.defineRouting(predecessorList=[Q2], successorList=[Q3])
Q3.defineRouting(predecessorList=[M2], successorList=[M3])
M3.defineRouting(predecessorList=[Q3], successorList=[E])
E.defineRouting(predecessorList=[M3])
def main(test=0):
# add all the objects in a list
objectList = [NS, M1, M2, M3, Q2, Q3, E]
# set the length of the experiment
maxSimTime = 480
solutionList = []
for i in range(1, 10):
from dream.simulation.Globals import runSimulation
#define the objects of the model
NS=NonStarvingEntry('NS1','Entry',entityData={'_class':'Dream.Part'})
M1=Machine('M1','Machine1', processingTime={'Exp':{'mean':1}})
Q2=Queue('Q2','Queue2')
M2=Machine('M2','Machine2', processingTime={'Exp':{'mean':3}})
Q3=Queue('Q3','Queue3')
M3=Machine('M3','Machine3', processingTime={'Exp':{'mean':5}})
E=Exit('E1','Exit')
#define predecessors and successors for the objects
NS.defineRouting(successorList=[M1])
M1.defineRouting(predecessorList=[NS],successorList=[Q2])
Q2.defineRouting(predecessorList=[M1],successorList=[M2])
M2.defineRouting(predecessorList=[Q2],successorList=[Q3])
Q3.defineRouting(predecessorList=[M2],successorList=[M3])
M3.defineRouting(predecessorList=[Q3],successorList=[E])
E.defineRouting(predecessorList=[M3])
def main(test=0):
# add all the objects in a list
objectList=[NS,M1,M2,M3,Q2,Q3,E]
# set the length of the experiment
maxSimTime=480
solutionList=[]
for i in range(1,10):
Q2.capacity=i
}})
M1 = Machine('M1', 'Machine1', processingTime={'Fixed': {'mean': 0.5}})
Q1 = Queue('Q1', 'Queue1', capacity=2)
M2 = Machine('M2', 'Machine2', processingTime={'Fixed': {'mean': 1}})
BRA = BatchReassembly('BRA',
'BatchReassembly',
numberOfSubBatches=4,
processingTime={'Fixed': {
'mean': 0
}})
M3 = Machine('M3', 'Machine3', processingTime={'Fixed': {'mean': 1}})
E = Exit('E', 'Exit')
# define the predecessors and successors for the objects
S.defineRouting([Q])
Q.defineRouting([S], [BD])
BD.defineRouting([Q], [M1])
M1.defineRouting([BD], [Q1])
Q1.defineRouting([M1], [M2])
M2.defineRouting([Q1], [BRA])
BRA.defineRouting([M2], [M3])
M3.defineRouting([BRA], [E])
E.defineRouting([M3])
def main(test=0):
# add all the objects in a list
objectList = [S, Q, BD, M1, Q1, M2, BRA, M3, E]
# set the length of the experiment
maxSimTime = 1440.0
# call the runSimulation giving the objects and the length of the experiment
# 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
runSimulation(objectList, maxSimTime)
# calculate metrics
working_ratio = (AC.totalWorkingTime/maxSimTime) * 100
S=Source('S','Source', interarrivalTime={'distributionType':'Fixed','mean':0.5}, entity='Dream.Part')
Q=Queue('Q','Queue', capacity=infinity)
M1=Machine('M1','Milling1', processingTime={'distributionType':'Fixed','mean':0.25})
M2=Machine('M2','Milling2', processingTime={'distributionType':'Fixed','mean':0.25})
E=Exit('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
#define predecessors and successors for the objects
S.defineRouting([Q])
Q.defineRouting([S],[M1,M2])
M1.defineRouting([Q],[E])
M2.defineRouting([Q],[E])
E.defineRouting([M1,M2])
def main():
initialize() #initialize the simulation (SimPy method)
for object in G.ObjList:
object.initialize()
for objectInterruption in G.ObjectInterruptionList:
objectInterruption.initialize()
#activate all the objects
for object in G.ObjList:
totalParts += len(object.getActiveObjectQueue())
return totalParts
QB = Queue('QB', 'QueueBefore', capacity=float("inf"))
Q1 = InternalQueue('Q1', 'Q1', capacity=1)
M1 = InternalProcess('M1', 'M1', processingTime={'Exp': {'mean': 1}})
Q2 = InternalQueue('Q2', 'Q2', capacity=1)
M2 = InternalProcess('M2', 'M2', processingTime={'Exp': {'mean': 1}})
Q3 = InternalQueue('Q3', 'Q3', capacity=1)
M3 = InternalProcess('M3', 'M3', processingTime={'Exp': {'mean': 1}})
QA = Queue('QA', 'QueueAfter', capacity=float("inf"))
MA = Machine('MA', 'MachineAfter', processingTime={'Exp': {'mean': 1}})
E = Exit('E', 'Exit')
QB.defineRouting(successorList=[Q1, Q2, Q3])
Q1.defineRouting(predecessorList=[QB], successorList=[M1])
Q2.defineRouting(predecessorList=[QB], successorList=[M2])
Q3.defineRouting(predecessorList=[QB], successorList=[M3])
M1.defineRouting(predecessorList=[Q1], successorList=[QA])
M2.defineRouting(predecessorList=[Q2], successorList=[QA])
M3.defineRouting(predecessorList=[Q3], successorList=[QA])
QA.defineRouting(predecessorList=[M1, M2, M3], successorList=[MA])
MA.defineRouting(predecessorList=[QA], successorList=[E])
E.defineRouting(predecessorList=[MA])
P1 = Part('P1', 'P1', currentStation=QB)
P2 = Part('P2', 'P2', currentStation=QB)
P3 = Part('P3', 'P3', currentStation=QB)
P4 = Part('P4', 'P4', currentStation=QB)
P5 = Part('P5', 'P5', currentStation=QB)
distribution={
'TTF': {
'Fixed': {
'mean': 60.0
}
},
'TTR': {
'Fixed': {
'mean': 5.0
}
}
})
#define predecessors and successors for the objects
S.defineRouting([Q])
Q.defineRouting([S], [M1, M2])
M1.defineRouting([Q], [E])
M2.defineRouting([Q], [E])
E.defineRouting([M1, M2])
def main(test=0):
# add all the objects in a list
objectList = [S, Q, M1, M2, 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
from dream.simulation.Globals import runSimulation
# define the objects of the model
S=BatchSource('S','Source',interarrivalTime={'distributionType':'Fixed','mean':1.5}, entity='Dream.Batch', batchNumberOfUnits=100)
Q=Queue('Q','StartQueue',capacity=100000)
BD=BatchDecomposition('BC', 'BatchDecomposition', numberOfSubBatches=4, processingTime={'distributionType':'Fixed','mean':1})
M1=Machine('M1','Machine1',processingTime={'distributionType':'Fixed','mean':0.5})
Q1=Queue('Q1','Queue1',capacity=2)
M2=Machine('M2','Machine2',processingTime={'distributionType':'Fixed','mean':1})
BRA=BatchReassembly('BRA', 'BatchReassembly', numberOfSubBatches=4, processingTime={'distributionType':'Fixed','mean':0})
M3=Machine('M3','Machine3',processingTime={'distributionType':'Fixed','mean':1})
E=Exit('E','Exit')
# define the predecessors and successors for the objects
S.defineRouting([Q])
Q.defineRouting([S],[BD])
BD.defineRouting([Q],[M1])
M1.defineRouting([BD],[Q1])
Q1.defineRouting([M1],[M2])
M2.defineRouting([Q1],[BRA])
BRA.defineRouting([M2],[M3])
M3.defineRouting([BRA],[E])
E.defineRouting([M3])
def main(test=0):
# add all the objects in a list
objectList=[S,Q,BD,M1,Q1,M2,BRA,M3,E]
# set the length of the experiment
maxSimTime=1440.0
# call the runSimulation giving the objects and the length of the experiment
runSimulation(objectList, maxSimTime)
from dream.simulation.imports import Machine, Queue, Exit, Part, ExcelHandler
from dream.simulation.Globals import runSimulation, G
#define the objects of the model
Q=Queue('Q1','Queue', capacity=1)
M=Machine('M1','Machine', processingTime={'Fixed':{'mean':0.25}})
E=Exit('E1','Exit')
P1=Part('P1', 'Part1', currentStation=Q)
#define predecessors and successors for the objects
Q.defineRouting(successorList=[M])
M.defineRouting(predecessorList=[Q],successorList=[E])
E.defineRouting(predecessorList=[M])
def main(test=0):
# add all the objects in a list
objectList=[Q,M,E,P1]
# set the length of the experiment
maxSimTime=float('inf')
# call the runSimulation giving the objects and the length of the experiment
runSimulation(objectList, maxSimTime, trace='Yes')
# calculate metrics
working_ratio = (M.totalWorkingTime/G.maxSimTime)*100
# return results for the test
if test:
return {"parts": E.numOfExits,
"simulationTime":E.timeLastEntityLeft,
"working_ratio": working_ratio}
from dream.simulation.imports import Source, Queue, Machine, Exit
from dream.simulation.Globals import runSimulation
#define the objects of the model
S=Source('S1','Source',interArrivalTime={'Fixed':{'mean':0.5}}, entity='Dream.Part')
Q=Queue('Q1','Queue', capacity=1)
M=Machine('M1','Machine', processingTime={'Fixed':{'mean':0.25}})
E=Exit('E1','Exit')
#define predecessors and successors for the objects
S.defineRouting(successorList=[Q])
Q.defineRouting(predecessorList=[S],successorList=[M])
M.defineRouting(predecessorList=[Q],successorList=[E])
E.defineRouting(predecessorList=[M])
def main(test=0):
# add all the objects in a list
objectList=[S,Q,M,E]
# 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 = (M.totalWorkingTime/maxSimTime)*100
# return results for the test
if test:
return {"parts": E.numOfExits,
"working_ratio": working_ratio}
M=Machine('M1','Machine', processingTime={'Fixed':{'mean':3}})
E=Exit('E1','Exit')
P1=Part('P1', 'Part1', currentStation=Q1)
entityList=[]
for i in range(5): # create the WIP in a loop
Q1PartId='Q1_P'+str(i)
Q1PartName='Q1_Part'+str(i)
PQ1=Part(Q1PartId, Q1PartName, currentStation=Q1)
entityList.append(PQ1)
Q2PartId='Q2_P'+str(i)
Q2PartName='Q2_Part'+str(i)
PQ2=Part(Q2PartId, Q2PartName, currentStation=Q2)
entityList.append(PQ2)
#define predecessors and successors for the objects
Q1.defineRouting(successorList=[M])
Q2.defineRouting(successorList=[M])
M.defineRouting(successorList=[E])
E.defineRouting(predecessorList=[M])
EV=EventGenerator('EV', 'PredecessorChanger', start=0, stop=50, interval=10,method=changeMachinePredecessor,
argumentDict={'machine':M, 'possiblePredecessors':[Q1,Q2]})
def main(test=0):
# add all the objects in a list
objectList=[Q1,Q2,M,E,EV]+entityList
# set the length of the experiment
maxSimTime=float('inf')
# call the runSimulation giving the objects and the length of the experiment
runSimulation(objectList, maxSimTime, trace='Yes')
# 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
runSimulation(objectList, maxSimTime)
# calculate metrics
working_ratio = (AC.totalWorkingTime / maxSimTime) * 100