One of Performance Lawn Equipment’s (PLE) manufacturing plants supplies various engine components to manufacturers of motorcycles on a just-in-time basis. Planned production capacity for one component is 100 units per shift, and the plant operates one shift per day. Because of fluctuations in customers’ assembly operations, however, demand fluctuates and is historically between 80 and 130 units per day. To maintain sufficient inventory to meet its just-in-time commitments, PLE’s management is considering a policy to run a second shift the next day if inventory falls to 50 or below at the end of the day (after the daily demand is known). For the annual budget planning process, managers need to know how many additional shifts will be needed. The fundamental equation that governs this process each day is: ending inventory = beginning inventory + production – demand

Develop a spreadsheet model to simulate 260 working days (1 year), and count the number of additional shifts that are required. Assume that the initial inventory is 100 units. Use Psi functions for all uncertain cells in building your model. Using the number of additional shifts required as the output cell for a Monte Carlo simulation, find the distribution of the number of shifts that the company can expect to need over the next year.