Abstract: An operation method and an operation device for operating a real-time discussion window are provided. The operation method for operating the real-time discussion window includes the following steps. A discussion topic is obtained from an initiator. A participant candidate list is provided. The participant candidate list includes a plurality of non-player characters. A participant suggestion list is provided from the candidate list according to the discussion topic. At least one of the non-player characters is added into the real-time discussion window according to a selection result of the initiator. At least one relevant technical person is invited into the real-time discussion window. The discussion topic is discussed in the real-time discussion window. A discussion report is automatically generated according to the discussion content in the real-time discussion window.

Abstract: An operation method and an operation device for operating a real-time discussion window are provided. The operation method for operating the real-time discussion window includes the following steps. A discussion topic is obtained from an initiator. A participant candidate list is provided. The participant candidate list includes a plurality of non-player characters. A participant suggestion list is provided from the candidate list according to the discussion topic. At least one of the non-player characters is added into the real-time discussion window according to a selection result of the initiator. At least one relevant technical person is invited into the real-time discussion window. The discussion topic is discussed in the real-time discussion window. A discussion report is automatically generated according to the discussion content in the real-time discussion window.

Abstract: 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.

Abstract: An equipment sensing circuit board and an operation method thereof are provided. The equipment sensing circuit board equipped on a semiconductor equipment includes a main sensor, a backup sensor, a first electronic fuse, a second electronic fuse, and a multiplexer. The main sensor and the backup sensor are used to monitor the operation of the semiconductor equipment to output a main sensing signal and a backup sensing signal respectively. The first electronic fuse is disposed on the main sensor to output a first status signal. The second electronic fuse is disposed on the backup sensor to output a second status signal. The multiplexer is connected to the main sensor, the backup sensor, the first electronic fuse and the second electronic fuse. The multiplexer selects to output the main sensing signal or the backup sensing signal according to the combination of the first state signal and the second state signal.

Abstract: 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.