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Title: Failure rate monitoring in generalized gamma-distributed process Authors:  Niladri Chakraborty - University of the Free State (South Africa) [presenting]
Tahir Mahmood - The Open University of Hong Kong (Hong Kong)
Abstract: Technological advancement has brought revolutionary changes in product quality in today's time. Most of the manufacturing processes produce a large number of conforming items along with a few nonconforming items. In real-time monitoring of these highly efficient processes, monitoring time between events is a well-known approach in statistical process control literature. It is generally assumed that the time-between-events follows an exponential or gamma distribution. However, the generalized gamma distribution is often a more popular choice in modelling skewed data. In this context, we consider a two-sided monitoring scheme based on the generalized gamma distribution. Two-sided monitoring schemes for skewed distributions often encounter bias in their run length properties. Therefore, we address this problem with modified control limits in a more general distributional setup. A Monte-Carlo simulation-based study is designed, and computational results reveal encouraging performance properties. Practical applications related to monitoring renewable energy production and coal mine explosions have been considered.