Abstract: An automatic optimization method and an automatic optimization system of a diagnosis model are provided. The automatic optimization method includes: obtaining equipment parameters; selecting a target model; selecting and converting a hyperparameter into a gene sequence, randomly generating a plurality of gene sequences to be optimized and adding them to a gene sequence set; performing a gene evolution process to generate a plurality of progeny gene sequences; performing a region search process on the plurality of progeny gene sequences to generate a plurality of new progeny gene sequences and add them to the gene sequence set; and in response to meeting the evolution completion condition, using the gene sequence set as an optimal gene sequence set for configuration of the target model and generation of a plurality of candidate diagnosis models.

Abstract: A machine diagnostic system includes a performance evaluating module, a machine adjusting module and multiple sensors. The performance evaluating module evaluates the performance value of a part of a machine prior to production and predicts whether the part can be used to complete multiple batches of semi-products. If yes, the machine adjusting module sets a set value of the machine so that the machine can complete the multiple batches of semi-products. When the batches of semi-products are processed by the machine, a real-time production data is generated. When the sensors detect that the real-time production data contains an abnormal state data, re-evaluating whether the machine can complete the remaining semi-products according to the set value. If yes, enabling the machine to continue processing the remaining semi-products according to the set value. If no, updating the set value of the machine.