在SimPy Simulation on Availability方面需要帮助

时间:2014-10-07 14:44:36

标签: python simulation simpy

我在构建模拟时遇到了问题,我不知道如何解决它们。这种模拟的想法如下:

系统中总共有10台机器。模拟开始时,其中6台机器将开始工作,而其他4台机器将作为备件保留在库存中。

要求是系统中任何时候都应该有6台机器在工作。如果总共有6台机器工作,任何时间都将被视为停机时间。

经过一段时间的工作后,6台工作机器中的一台将会发生故障。当发生此故障事件时,我们将从库存中取出1台机器并将其添加到工作机组中,这样我们就可以满足每台6台机器一次工作的要求。

然后将故障机器送到维修车间并在一定时间后进行维修。当修理完成后,它将被移动到库存,它将加入其他机器。

下一次6台工作机器中的另一台发生故障时,将再次从库存中取出1台机器来更换发生故障的机器。这意味着库存中的机器数量将在整个模拟过程中不断波动。在整个模拟过程中,我还需要清单中有多少台机器,因此我添加了print语句来向我展示。

总之,一台机器将经历以下循环: 开始工作 - >失败 - >送到维修车间 - >修复后,放入库存 - >当另一台机器发生故障时,它会再次投入运行 - >开始工作 - >失败..等等。

我在此模拟中的另一个要求是我需要知道机器1到10在哪里。这样我就可以追踪每台机器的运动,例如,机器7何时发生故障,何时进入和离开维修车间,何时进入和离开库存等。

在建立此模拟之后,我将随后改变备件的初始数量和维修时间,以研究这些因素如何影响运营可用性水平。

我面临的主要问题:

我无法在整个周期中单独追踪10台机器中的每台机器

我无法正确建立我的备件库存。如果机器5-10在开始时处于操作中,当其中一个机器发生故障时,下一行输出应告诉我机器1已从库存中取出(并因此开始运行)以更换发生故障的机器。但是,我无法获得这样的输出。

提前谢谢!

到目前为止我已经包含了我的进展:

    import simpy
    import random

    RANDOM_SEED = 42
    NUM_SERVERS = 2
    MTBF = 10
    MTTR = 2
    TOTAL_MACHINES = 10
    TOTAL_SPARES = 4
    TOTAL_WORKING = TOTAL_MACHINES - TOTAL_SPARES
    SIM_TIME = 100

    class Working(object):
        def __init__ (self, env, num, repair_workshop, spares_inventory, downtime):
            self.env = env
            self.repair_workshop = repair_workshop
            self.spares_inventory = spares_inventory
            self.downtime = downtime
            self.name = 'Machine %d' % (num + 1)
            print('%s begins working %.2f' % (self.name, self.env.now))
            self.env.process(self.run())

        def run(self):
            yield self.env.timeout(random.expovariate(1.0 / MTBF))
            print('%s stops working %.2f' % (self.name, self.env.now))

            downtime_start = self.env.now
            spare = yield self.spares_inventory.get(1)
            self.downtime.append(self.env.now - downtime_start)

            print('%s taken from inventory at %.2f' % (spare.name, self.env.now))
            print('%d inside inventory' % len(spares_inventory.items))

            with self.repair_workshop.request() as req:
                yield req
                print('%s starts repair %.2f' % (self.name, self.env.now))

                yield self.env.timeout(random.expovariate(1.0 / MTTR))

                yield self.spares_inventory.put(1)
                print('%s finishes repair at %.2f' % (self.name, self.env.now))

            print(' %d inside inventory' % len(spares_inventory.items))

    def main():
        env = simpy.Environment()
        repair_workshop = simpy.Resource(env, capacity = NUM_SERVERS)
        spares_inventory = simpy.Container(env, capacity = TOTAL_MACHINES, init = TOTAL_SPARES)
        downtime = []
        working = [Working(env, i, repair_workshop, spares_inventory, downtime) for i in range(TOTAL_WORKING)]

        env.run(SIM_TIME)

        print('Total downtime for all machines throughout simulation time is %.2f hours' % sum(downtime))
        print('Operational Availability = %.2f percent' % ( (SIM_TIME - sum(downtime)) * 100 / (SIM_TIME)))

    if __name__ == '__main__':
        main()

在Stefan的帮助下,我修改了我的剧本:

    class Working(object):

        def __init__ (self, env, num, repair_workshop, spares_inventory, downtime, machine):
            self.env = env
            self.repair_workshop = repair_workshop
            self.spares_inventory = spares_inventory
            self.downtime = downtime
            self.machine = machine
            self.name = ('Machine %d' % (num + 1))
            print('%s begins working %.2f' % (self.name, self.env.now))
            self.env.process(self.run())

        def run(self):
            yield self.env.timeout(random.expovariate(1.0 / MTBF))
            print('%s stops working %.2f' % (self.name, self.env.now))

            downtime_start = self.env.now
            spare = yield self.spares_inventory.get(1)
            self.downtime.append(self.env.now - downtime_start)

            print('%s taken from inventory at %.2f' % (spare.name, self.env.now))
            print('%d inside inventory' % len(spares_inventory.items))

            with self.repair_workshop.request() as req:
                yield req
                print('%s starts repair %.2f' % (self.name, self.env.now))

                yield self.env.timeout(random.expovariate(1.0 / MTTR))

                yield self.spares_inventory.put(1)
                print('%s finishes repair at %.2f' % (self.name, self.env.now))

            print(' %d inside inventory' % len(spares_inventory.items))

    def main():
        env = simpy.Environment()
        repair_workshop = simpy.Resource(env, capacity = NUM_SERVERS)
        downtime = []

        machines = [object() for i in range(TOTAL_MACHINES)]
        working, spares = machines[:TOTAL_WORKING], machines[TOTAL_WORKING:]
        spares_inventory = simpy.Store(env, capacity = TOTAL_MACHINES)
        spares_inventory.items = spares
        working = [Working(env, i, repair_workshop, spares_inventory, downtime, machine) for i, machine in enumerate(working)]

        env.run(SIM_TIME)

        print('Total downtime for all machines throughout simulation time is %.2f hours' % sum(downtime))
        print('Operational Availability = %.2f percent' % ( (SIM_TIME - sum(downtime)) * 100 / (SIM_TIME)))

    if __name__ == '__main__':
        main()

这是我收到的追溯:

    Traceback (most recent call last):
    File "/Users/Scripts/8oct1.py", line 70, in <module> main()
    File "/Users/Scripts/8oct1.py", line 64, in main env.run(SIM_TIME)
    File "/Library/Python/2.7/site-packages/simpy/core.py", line 120, in run self.step()
    File "/Library/Python/2.7/site-packages/simpy/core.py", line 213, in step raise event._value
    TypeError: __init__() takes exactly 2 arguments (3 given)

1 个答案:

答案 0 :(得分:2)

您可以使用Store代替Container。使用Store,您可以为您的机器使用可区分的对象,这样您就可以在模拟中跟踪它们。

例如,

machines = [object() for i in range(TOTAL_MACHINES)]
working, spares = machines[:TOTAL_WORKING], machines[TOTAL_WORKING:]
spares_inventory = Store(env, capacity=TOTAL_MACHINES)
spares_inventory.items = spares
working = [Working(env, i, machine) for i, machine in enumerate(working)]

当然,您还可以使用(命名)元组,普通整数或任何其他最适合代表机器的对象来代替object