Abstract

The reliability performance of Semiconductor Manufacturing Equipments (SME) is very important for both equipment manufacturers and customers. However, the response variables are random in nature and can significantly change due to many factors. In order to track the equipment reliability performance with certain confidence, this paper proposes an efficient methodology to calculate the number of samples needed to measure the reliability performance of the SME tools. This paper presents a frequency-based Statistics methodology to calculate the number of sampled tools to evaluate the SME reliability field performance based on certain confidence levels and error margins. One example case has been investigated to demonstrate the method. We demonstrate that the multiple weeks accumulated average reliability metrics of multiple tools do not equal the average of the multiple weeks accumulated average reliability metrics of these tools. We show how the number of required sampled tools increases when the reliability performance is improved and quantify the larger number of sampled tools required when a tighter margin of error or higher confidence level is needed.

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