Economic in-line inspection sampling strategy with learning effects

摘要

This paper presents an innovative approach to a wafer inspection strategy that incorporates learning dynamics in semiconductor manufacturing factories. Using the data from fabrication lines (fabs) we demonstrate algorithms for computing the sampling strategy in terms of the percentage of wafers to sample for a process in different phases of a product life cycle. The average selling price and wafer starts per weeks are considered in the model. The paper provides an optimal solution methodology and concludes that the learning benefits of quality control activities may achieve the most cost-effective operations.