After plotting the demand, we could tell that we were dealing with an uncertain demand, which had an average of 12 orders per day with a standard deviation of 3 orders. The current capacities of machine 1 and 3 were at 13 jobs per day and the capacity of machine 2 was 25 jobs per day. This was calculated by dividing the average demand by the average utilization of each machine, additionally, our average lead-time was 1 day with a standard deviation of .72. This meant that our factory was able to meet the majority of demand since our overall flow rate was equal to demand plus its standard deviation (FR=min of 13 capacity and 12 demand) as well as meet the specified conditions of contract 1. Additionally, this information showed that we currently had two bottlenecks in machines 1 and 3, which meant that when we decided to buy more machines we would need to have enough to increase the capacities of machine 1 and 3 at the same time or else our overall flow rate would not change.
Our first step was to calculate the correct EOQ and ROP quantities so that we could begin to maximize our profits and be able to advance to the next contract as soon as possible. Our ROP quantity was then changed to 60 jobs (12 demand*4 days of supplier lead time+1.65 95% Z score*3.412 standard deviation of demand*square root 4 days of supplier lead time). Our EOQ was 38 (square root of 2*1000 setup cost*12 demand/600 cost per unit * .02373 10% interest compounded daily). After changing EOQ and ROP we determined we needed to hit a cash savings of $212,800 to afford to buy 2 machines for station 1 and 2 and be able to re-stock our inventory (2,280 EOQ * $10 per kit)+ $90,000 for machine 1 + $100,000 for machine 2). To do this we calculated daily profit to determine how long it would take us to reach our goal.
We knew that the factory re-ordered every 4 days at a EOQ of 2,280, which costs us $22,800 every 4 days (22800 * 10), however, on average we are only getting 12 new orders a day, which meant we are only collecting $36,000 every 4 days, which meant every 4 days we were making $13,100 profit, on average. In the beginning of the game we hade a balance of $177,898, which meant we needed an additional $34,902 to meet our goal ($212,800-$177,898). This meant we would have sufficient funds in exactly 10.65 days or 10 hours and 15 minutes to buy everything we needed and advance to contract 2 ($13,100 profits every 4 days, meant $3,275 profits every day. $34,902 / $3,275 = 10.65 days which equals 10 hours and 15 minutes in real life).
When going to buy machines for station one, we hit 1 in the order box thinking that it would buy us one more machine, instead the simulation sold 2 out of 3 machines we had. We quickly had to use the rest of our money to re-purchase one more machine to make up for this mistake. Our capacities were now at 8 jobs per day for station 1, 25 jobs per day for station 2, and 23 jobs per day for station 3, and our cash balance was $42,800.
Correction to mistake 1
As a correction we decided to change our ROP and EOQ. New ROQ would be 31 and new ROP would be 43 (EOQ = square root of 2(1000)(8)/16.38. ROP = 8*4+1.65(3.412403)(2) = 43, 8 was chosen as d since we were now supply constrained). We believed that this would allow us to gain profits again since we were currently making almost no money due to the fact that the assumed amount of jobs we were completing were bringing in just above the costs to buy new inv at the past EOQ level. Additionally we believed that we were still under the quoted lead-time of contract 1 (12 jobs on average / 8 flow rate = 1.5 flow time), which meant we were still making $750 per completed job.
This meant with the new calculations we would be making 24,000 in revenue every 4 days. Every 4 days we would also spend 18,600 in re order costs (with new EOQ) causing us to predict 5,400 profits every 4 days or 1,350 profits every day. To raise enough to buy 1 more machine to return to our original capacity we believed we would only have to wait 49 days until we have 126,000 to buy a new machine and re-stock. From there we thought we would get back to completing 12 orders a day on average, bringing us back to 3,300 profit per day. From there it will take 38 days to raise enough to buy a another machine and advance to contract 2 giving us 6,300 profit per day. From there it will take 20 days to buy a 5th machine to advance to contract 3, giving us 9,300 profits per day. Overall, we thought it would take us 119 days to reach contract 3.
After checking back with the simulation in 49 days, we found that we had actually only been completing 6 jobs per day on average. Our cash balance was down to only $6,800, and demand had dropped to 7 jobs per day on average before hitting 0. There were two reasons for this. First, we had failed to make promised lead time. Initially we thought with a capacity of 8 jobs per day our lead time would only be 1.5 (12 batches a day from 12 jobs per day /8 flow rate = 1.5), however our lead time started go over 8 days.
This caused us to loose demand since we could not satisfy all of our orders. Second our calculation of ROP and EOQ was under the assumption that we would be processing 8 jobs per day. However because we were only completing 6 jobs per day on average we had been loosing $150 per day since our “correction of EOQ” (6 jobs on average completed per day * $750 per job * 4 days = $18,000 revenue every 4 days; 31 EOQ * 60 * 10 = 18,600 cost every 4 days; Profit every 4 days = -600, losing $150 per day up). This loss continued until we ran out of inventory and money to order our EOQ size, which caused demand to hit 0 and the factory to stop all production.
Correction to mistake 2
Because we only had a cash balance of $6,842 and since 1 job costs $600, we changed the EOQ to 11, so we could order more inventory. At least this way we could fulfill 11 orders, which was roughly 1 day of demand. This gave us revenue of 7,500 (10 flow rate * $750 per job). Additionally, we knew our inventory would drop back down to 0 the next day, so we also changed our ROP to 0, believing this would allow us to re-order faster. This strategy was thought to give us profit of $700 every 4 days or $175 a day on average. At this moment our target EOQ was 29 jobs, based on a demand of 7, which costs us 18,600, and it was thought to take 106 days to raise this much money given the current trend.
The correction to mistake 2 only brought in 1,000 in profit reason being was our factory stopped ordering units even though we had enough money to purchase inventory at the set EOQ.
Consideration of debt
When our team finally discovered that we could go into debt to re-purchase inventory and machines it was to late. Assuming that interest is compounded daily because the game is set in a timeframe of days, we calculated the possibilities of running debit to advance to contract 3, 2, and even to get back on par with contract 1. However, because there were only 170 days left in the game, none of the amounts of debt we wanted to raise could have been paid off before the game was over, additionally all the interest payments associated with purchasing 1-3 new machines combined with a ROP of 60 and EOQ of 38 (original EOQ and ROP levels first calculated) gave us negative profits.
For example, if we wished to advanced immediately to contract 3 at this point in time we would make $2,184 negative profit per day (3 additional machines *$90,000 + 22,280 cost of original EOQ + 36,000 cost to reach original ROP stock inventory = $418,280, 10% interest compounded daily at 2.74% interest would result in interest payments of $11,614 a day to pay off the debt within 160 days, we would only be making profit net of EOQ of 9,430 per day (12 demand *1250 contract 3 sales price – 22,280 EOQ cost /4 days = $9,430 per day). Getting back to contract 1 would cost us $4,117 interest per day with a profit net of EOQ of only $3,430 resulting in a negative profit per day of $987.
If we would do the simulation over again, the first thing our group should have done was to go into debt to restore the number of machines in station 1 to 3 machines. The reason why we chose this option was that out of the three options we had (e.g go into debt to advance to contract 2, 3, or re-meet contract 1) re-meeting contract 1 was the most profitable. Going into $90,000 debt with an annual 10% interest compounded daily, could have been paid off in 150 days, while making a profit of $766 per day (12 avg daily demand *$750 revenue per job
* 4 days – $22,800 re-order cost every 4 days = 13,200 profit every 4 days / 4 = 3,300 profit per day – $2,509 daily interest payments = $766 profit per day). After 150 days we hypothetically would have had a cash balance of $157,700 ($766 profit per day * 150 days + $42,800 initial cash balance = $157,700), which would have allowed us to advance to contract 2 and have a remaining balance of $67,700 to cover the next cycle of EOQ. After reaching contract two, it would have taken us 14 days to have enough money for a 5th machine in station one and advance to contract 3 (12 avg daily demand * $1000 per job *4 days – $22,800 re-order cost every 4 days =25,200 profit every 4 days / 4 days = 6,300 profit per day, $90,000 cost of machine / 6,300 = 14 days)