Sturgill Manufacturing, Inc. needs to predict the numbers of machines and employees required to produce its planned production for the coming year. The plant runs three shifts continuously during the workweek, for a total of 120 hours of capacity per week. The shop efficiency (the percent of total time available for production), which accounts for setups, changeovers, and maintenance, averages 70% with a standard deviation of 5%, which r educes the weekly capacity. Six key parts are produced, and the plant has three different types of machines to produce each part. The machines are not interchange-able as they each have a specific function. The time to produce each part on each machine varies. The mean time and standard deviation (in hours) to produce each part on each machine are shown below:Mean TimePart TypeMachine AMachine BMachine C13.52.6 8.923.42.5831.83.512.642.45.812.554.24.328644.328Standard DeviationPart TypeMachine AMachine BMachine C10.150.120.1520.150.120.1530.10.150.2540.150.150.2550.150.150.560.150.150.5The forecasted demand is shown belowPart TypeDemand (Parts/Week)14221836465666Machines A and B only require one person to run two machines. Machine C requires only one person per machine. Develop a simulation model to determine how many machines of each type and number of employees will be required to meet the forecasted demand. 414 Chapter 12 Monte Carlo Simulation and Risk Analysismiscellaneous products. Each is sold in 55-gallon drums. The selling price and unit manufacturing cost are shown below:ManufacturingProduct TypeSelling Price/drumCost/drumIndustrial CleaningAlkaline Cleaner$700.00$275.00Acid Cleaner$600.00$225.00Neutral Cleaner$450.00$150.00Chemical TreatmentIron Phosphate$920.00$400.00Zirconium$1,350.00$525.00Zinc Phosphate$1,400.00$625.00OtherSealant$850.00$350.00Rust Prevention$600.00$260.00Fixed costs are assumed normal with a mean of $5 million and a standard deviation of $20,000. Demands are all assumed to be normally dis-tributed with the following means and standard deviations: Product TypeMean DemandStandard DeviationIndustrial CleaningAlkaline Cleaner5,000100Acid Cleaner2,000500Neutral Cleaner5,000350Chemical TreatmentIron Phosphate5,500250Zirconium2,800130Zinc Phosphate4,350300OtherSealant8,000350Rust Prevention4,250250The operations manager has to determine the quan-tity to produce in the face of uncertain demand. One option is to simply produce the mean demand; depending on the actual demand, this could result in a shortage (lost sales) or excess inventory. Two other options are to produce at a level equal to either 75% or 90% of the demand (i.e., find the value so that 75% or 90% of the area under the normal distribution is to the left). Using Monte Carlo simulation, evaluate and compare these three policies and write a report to the operations manager summarizing your findings.Case: Performance Lawn EquipmentOne of PLEs 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, PLEs management is considering a policy to run a second shift the next day if inventory falls to 50 or below at the end of a 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 fundamen-tal equation that governs this process each day isending inventory=beginning inventory +production-demandDevelop 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. Explain and summarize your findings in a report to the plant manager and make a recommendation as to how many shifts to plan in next years budget.