English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Ion implanter is critical to modern integrated-circuit (IC) manufacturing. Ion implanter requires a long process due to low acceleration and high concentration process, which results in low productivity and becomes a bottleneck in the semiconductor fabrication. Furthermore, the wafer is not re-workable if existing error operation either caused by the operator or the machine. Therefore, it is important to develop a real-time fault detection system to minimize the probable down time of the ion implanter. In this work, a real-time fault detection system, which is based on the Fuzzy Tree Classification Systems (FTCS), is proposed to monitor the operation of the Eaton NV6200A/AV ion implanter. Two datasets, the 26-recipe and the 42- recipe cases, provided by a renowned wafer foundry in Taiwan were used to test the performance of the proposed FTCS. The datasets were obtained through the SECS-II interface. Test results demonstrate that the proposed FTCS can work real-time for fault detection of the Eaton NV6200A/AV ion implanter.

Fuzzy tree classification system for fault diagnosis on Ion implanter