United Microelectronics Corp.

Te-Hsuan Chen

Ching-Pei Lin

Chung-Yi Chiu

Ji-Fu Kung

Ming-Wei Chen

Yi-Lin Hung

Chia-Wei Chen

Hsiao-Ying Yang

A training method of a semiconductor process prediction model, a semiconductor process prediction device, and a semiconductor process prediction method are provided. The training method of the semiconductor process prediction model includes the following steps. The semiconductor process was performed on several samples. A plurality of process data of the samples are obtained. A plurality of electrical measurement data of the samples are obtained. Some of the samples having physical defects are filtered out according to the process data. The semiconductor process prediction model is trained according to the process data and the electrical measurement data of the filtered samples.

Training method for semiconductor process prediction model, semiconductor process prediction device, and semiconductor process prediction method

An operation method and an operation device of a failure detection and classification (FDC) model are provided. The operation method of the FDC model includes the following steps. A plurality of raw traces are continuously obtained. If the raw traces have started to be changed from the first waveform to the second waveform, whether at least N pieces in the race traces have been changed to the second waveform is determined. If at least N pieces in the raw traces have been changed to the second waveform, the raw traces which have been changed to the second waveform are automatically segmented to obtain several windows. An algorithm is automatically set for each of the windows. Through each of the algorithms, an indicator of each of the windows is obtained. The FDC model is retrained based on these indicators.

Operation method and operation device of failure detection and classification model

Growing community of inventors

Tainan, Taiwan

Te-Hsuan Chen