MONTE CARLO SIMULATION – ILLUSTRATION 2

Auto Manufacture Ltd (hereinafter referred to as “the company”) is an automobile component manufacturer, supplying a similar component to many motorcycle manufactures in India. The company buys an important component called ‘Bonjo-2059’ from its suppliers. Each motorcycle needs two units of ‘Bonjo-2059’ to be fitted. It needs to decide on the Economic Order Quantity for ‘Bonjo-2059’ for next financial year commencing from Jan 1, 2015. Based on the indications given by its customers, the annual demand for motorcycles during next year (calendar year) would be a minimum of 75 million units and maximum of 90 million units. However, they expect that most likely the annual sales volume is likely to be 80 million units. The Company’s market share for the product that uses Component ‘Bonjo-2059’ is 55%. The suppliers of the company have indicated that the cost per unit could vary anything from Rs.70 to Rs.100 (a discrete uniform distribution with the average of Rs.85 and range of Rs.30). From the indications given by the bankers of the company, it is likely that the next year carrying cost as a percentage of Cost per Unit would follow normal distribution with mean of 4% and standard deviation of 1.5%. The cost of placing the order follows subjective normal probability distribution as follows:-

Cost of Rs.10 15% Rs.15 30% Rs.20 40% Rs.25 10% Rs.30 5%

Simulate the possibilities with 3,000 trials.

The EOQ is given by EOQ =

Where Q is the annual Demand, CO is ordering cost per order, CU is Cost per unit and CC% is carrying cost in percentage terms.

The Uniform Distribution variable can be converted in Triangular Distribution variable by using the following Formula

=IF(r<=(c-a)/(b-a), a+SQRT(r*(b-a)*(c-a)),b-SQRT((1-r)*(b-a)*(b-c))

Where ‘r, ‘a’, ‘b’ and ‘c’ having usual