Date of Award
Master of Science in Chemical Engineering - (M.S.)
Chemical Engineering and Chemistry
Edward Charles Roche, Jr.
John E. McCormick
A. Monte Carlo computer program has been developed in which the optimum plant capacity is determined by comparing calculated profitability criterions for various plant capacities. The estimates for input variables are developed into probability distributions. This data is then used to calculate a probability distribution for a-profitability criterion. In this thesis approximately thirty input variables are developed into beta distributions. Each variable must be estimated with a ninety percent probability estimate, a most likely probability estimate and a ten percent probability estimate. The three level estimates for each variable completely describe the beta distribution. Approximately half of the beta distributions are used to generate time dependent models described by equations for industry demand, market share, selling price, plant learning, and variable costs. These models follow continuous exponential curves. The remaining distributions are used in determining investments, manufacturing costs and working capital. The procedure followed in the Monte Carlo program is choosing randomly selected values from each distribution and using these values to calculate profitability criterions. This procedure is repeated a large number of times resulting in a probability distribution for each profitability criterion. The profitability distributions are developed for various plant capacities and therefore, the optimum plant capacity is determined.
Monesmith, Frederick Louis, "The determination of an optimum plant capacity in a dynamic economy" (1974). Theses. 2181.