Abstract: The present application relates to automatic decision-making for welding. Multi-dimensional data cleaning is performed and dimensional data warehouse is established by processing, filtering and converting basic source data of welding nodes in a welding process for monocrystal pulling-up into data sets easily identified and marked and establishing respective models based thereon. Basic source data of a current welding nodes are obtained and converted into process parameters. The process parameters are compared with respective models in the dimensional data warehouse to obtain a first determination result. Data analysis is performed on the first determination result to determine whether the current welding process is abnormal to obtain a second determination result. Decision is made automatically based on the second determination result.

Abstract: The present application relates to automatic decision-making for pulling. Multi-dimensional data cleaning is performed and dimensional data warehouse is established by processing, filtering and converting basic source data of pulling nodes in a pulling process for monocrystal pulling-up into data sets easily identified and marked and establishing respective models based thereon. Basic source data of a current pulling nodes are obtained and converted into process parameters. The process parameters are compared with respective models in the dimensional data warehouse to obtain a first determination result. Data analysis is performed on the first determination result to determine whether an abnormality occurs in the current pulling process to obtain a second determination result. Decision is made automatically based on the second determination result.

Abstract: The present disclosure relates to automatic decision-making for re-feeding. Multi-dimensional data cleaning is performed and dimensional data warehouse is established by processing, filtering and converting basic source data of re-feeding nodes in a re-feeding process for monocrystal pulling-up into data sets easily identified and marked and establishing respective models based thereon. Basic source data of a current re-feeding nodes are obtained and converted into process parameters. The process parameters are compared with respective models in the dimensional data warehouse to obtain a first determination result. Data analysis is performed on the first determination result to determine whether an abnormality occurs in the current re-feeding process to obtain a second determination result. Decision is made automatically based on the second determination result.