(85f) Determination of Optimum Storage Size for a Supply System Via Stochastic Simulations

The same industrial chemicals and gasses may be supplied to variety of customers which demand different reliability/cost structures. Therefore, the supply systems need to be ?tuned? to satisfy specific customer demands. Adding storage to a process is one way to increase the reliability of supply without changing manufacturing process. However, for these processes the exact analytical calculation of the reliability may be impractical due to complex operational logics coupling with storage. We used stochastic simulation techniques to calculate reliability of various supply systems and their optimum storage sizes. In this work, we present three real world examples: F2, H2, and O2 productions. Each of these production processes has different components and operating procedures. Reliabilities of important components are calculated from historical operational data. Then, these reliability data is used to model and simulate various supply system configurations using a Monte Carlo simulation/modeling method. Our method allows us to model realistic operational logics and to obtain flexible outputs to present complete reliability state of a supply system.