SECTION B: CASE SCENARIOS TO BE SOLVED ON MONTE CARLO SIMULATION Edward, owner, and manager of General Hardware, wants to find a good, low- cost inventorypolicy for one product: The Ace model electric drill. Due to the complexity of this situation, he has decided to use simulation to help with this. Daily demand for the Ace model drill is relatively low but subject to some variability. Over thepast 300 days, Edward has observed the sales shown in the table. When Edward places an order to replenish his inventory of Ace drills, there is a delivery lag of one to three days. The first inventory policy that General Hardware wants to simulate is an order quantity of 10 with a reorder point of 5 (if the lead time is one day, by the way, the order will not arrive the nextmorning but at the beginning of the following working day). Demand 10 Ace Drill for Frequency (days) 15 30 2 60 3 120 14 45 5 30 Lead Time Frequency (order) 10 2 25 3 15 Take note of the steps for conducting Monte Carlo simulation: 1. Establish the probability distribution based on the historical data available. 2. Cumulate the probability distribution obtained in step one. 3. Set random number intervals based on your results in Step 2. Remember random number intervals can only be from 0 to 99. 4. Generate random numbers. 5. Determine the answer to the questions asked based on the results for 4 steps. Questions: 1. Simulate for 10 days period assuming that the beginning inventory is 10 units on day 1. Selected random numbers are: 06, 63, 57, 02, 94, 52, 69, 33, 32, 30 (14) 2. Simulate the inventory system of Ace Drill and determine the following: 1.2.1 Average ending inventory (2) 1.2.2 Average lost sales (2) 1.2.3 Average number of orders (2)