Paper Title
Reliability-based Performance Measure for Stochastic Networks

Many solar photovoltaic manufacturing networks, including the network transferring solar wafers into operational solar cells, can be modeled as stochastic networks with reworks. An important performance measure for such stochastic networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that a great deal of previous work publications, containing at least twenty-one examples, provide incorrect values of the system reliability. The erroneous results are due to the inconsistency of discrete-entity examples and continuous-flow analysis. The author recently published the Song Rule, which provides the correct analytical system-reliability value for stochastic networks, but is limited to only one production line, and is computation¬ally inefficient. The proposed rule has advanced the field of stochastic network performance. The work combines tools involving probability, reliability, and computer simulation so as to enable analysts to: (i) identify and improve upon certain incorrect /inferior methods that have found their way into the literature, and (ii) perform precise calculations with respect to network reliability for general stochastic network systems with multiple production lines and multiple reworks. Index terms - Solar Photovoltaic Networks, Solar Cells, System Reliability, Analytical Re¬sults, Discrete-event simulation