Littlefield simulation 2
Littlefield simulation 2Adair Gallo JuniorBarbara BedranFrank
RossJiaying GaoZachary NolteFactory Layout
ObjectivesTo make money
To be efficient
Objectives
Actions we took to accomplish our objectivesReduce queuesMake
sure there were always raw materials available Get the best
contract (Numer 3) with the maximum revenuesReduce lead times in
order to fulfill contract number 3
Job arrivalsThe job arrivals kept constant during all
simulationSo, at the moment we found the perfect number of machines
for each station, we did not have to change it for the rest of
simulation
Job arrivalsStation 1The utilization was very high in station 1
in the beginning of the simulation The big utilization generated
big queuesSo we decided to buy more machines to reduce the
utilization and by consequence, the queues Utilization in Station
1
Station 1The station was having big queues in the beginning of
the simulation So we decided to buy more machines to reduce the
queues
Queued Jobs in Station 1Station 2
Utilization in Station 2
Queues in Station 2The same analysis was taken in station 2We
bought one machine to reduce untilization and consequently reduce
queues Station 3Utilization in Station 3Queues in Station 3The same
analysis was taken in station 3We bought one machine to reduce
untilization and consequently reduce queues
Inventory (Raw materials)In the beginning of the simulation the
reorder point was too lateThe inventory got to zero before the next
order arrivedSo, we increased the reorder point to 3300 and later
to 3900 kits to ensure we would not run off materials We also
increased the order quantity to 10800 kits to reduce the number of
orders, since each order costed $ 1000Inventory in kits
Lead timesIn the beginning the lead times were big because there
were not enough capacity in the factoryAfter the lead times were
reduced, we changed our contract to make more money per jobAs we
can see, the number of machines we bought for each station and our
decision in the reorder point were good, because the lead times
kept constant and we could fulfill the requirements for contract
number 3Daily average job lead time
CashAs we can see, the growth rate increased after we bought
more machines and increased our capacityThe red line shows the
tendency if we took no decisions. As we can see, we would have have
finished the game with only $ 1,559,264 if we did nothing. We got
47.3% more money with our decisions or $ 738,142 more.
Cash on hand at the end of each day
Growth prediction (days: 66-123)We ploted our money just after
buying raw materials from day 66 to 123We used our data to find an
equation that described the growth rate of our moneyThe ajusted
equation (R=0.999) is presented in the graphThis data correspond to
a difference between the order quantity and the reorder point of
6300 kits
Ajustment of our money
Growth prediction (days: 136-258)We ploted our money just after
buying raw materials from day 66 to 123We used our data to find an
equation that described the growth rate of our moneyThe ajusted
equation (R=0.9995) is presented in the graphAfter day 132, we
changed the order quantity and the reorder point This data
correspond to a difference between the order quantity and the
reorder point of 6600 kits
Ajustment of our money
Growth prediction (Comparison)As we can see in the ajusted
equations, after incresing the difference between the order
quantity and the reorder point (day 132) from 6300 to 6900, we
notice that the growth rate (slope) increased from 6.95 to
7.55.This happened because we needed to order raw material with a
lower frequency. Thus, we reduced the frequency we paid the $ 1000
per order.So, we conclude that we should have increased the order
quantity sooner in the simulation, in order to get a higher growth
rate. (But the lack of data about interest over cash in hand and
money growth data prevented us from changing it before.
Overall team standing
Last thoughts Predict the future based on the pastAct as soon as
possible to improve efficiency
Questions?
