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}
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') # calculate metrics working_ratio = (M.totalWorkingTime/E.timeLastEntityLeft)*100
# 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 runSimulation(objectList, maxSimTime, trace='Yes')
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 R.initialize() for object in G.ObjList: object.initialize() for objectInterruption in G.ObjectInterruptionList:
'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 # return results for the test
'TTF': { '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
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):
#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 # return results for the test if test:
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):
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 runSimulation(objectList, maxSimTime, trace='Yes')
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):
# 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 # return results for the test
from dream.simulation.imports import Machine, BatchSource, Exit, Batch, BatchDecomposition, Queue, G from dream.simulation.imports import simulate, activate, initialize # define the objects of the model S=BatchSource('S','Source',interarrivalTime={'distributionType':'Fixed','mean':0.5}, entity='Dream.Batch', batchNumberOfUnits=4) Q=Queue('Q','StartQueue',capacity=100000) BD=BatchDecomposition('BC', 'BatchDecomposition', numberOfSubBatches=4, processingTime={'distributionType':'Fixed','mean':1}) M=Machine('M','Machine',processingTime={'distributionType':'Fixed','mean':0.5}) E=Exit('E','Exit') # add all the objects in the G.ObjList so that they can be easier accessed later G.ObjList=[S,Q,BD,M,E] # define the predecessors and successors for the objects S.defineRouting([Q]) Q.defineRouting([S],[BD]) BD.defineRouting([Q],[M]) M.defineRouting([BD],[E]) E.defineRouting([M]) def main(): # initialize the simulation (SimPy method) initialize() # initialize all the objects for object in G.ObjList: object.initialize() # activate all the objects for object in G.ObjList: activate(object,object.run()) # set G.maxSimTime 1440.0 minutes (1 day) G.maxSimTime=1440.0 # run the simulation simulate(until=G.maxSimTime)
batchNumberOfUnits=4) Q = Queue('Q', 'StartQueue', capacity=100000) BD = BatchDecomposition('BC', 'BatchDecomposition', numberOfSubBatches=4, processingTime={'Fixed': { 'mean': 1 }}) M = Machine('M', 'Machine', processingTime={'Fixed': {'mean': 0.5}}) E = Exit('E', 'Exit') # define the predecessors and successors for the objects S.defineRouting([Q]) Q.defineRouting([S], [BD]) BD.defineRouting([Q], [M]) M.defineRouting([BD], [E]) E.defineRouting([M]) def main(test=0): # add all the objects in a list objectList = [S, Q, BD, 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 blockage_ratio = (M.totalBlockageTime / maxSimTime) * 100
# 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