Abstract: A method to set up the parameters of solder paste screen printer while in a new product introduction (NPI). The method includes establishing a solder-printing database of a predetermined product and a database of different specifications of products, and training a first prediction model by reference to a solder paste screen printer (SPSP) and a solder paste inspection (SPI) based on the solder-printing database. A second prediction model is trained by reference to the SPI based on the database of different products. The method further includes predicting parameters for products with different specifications under multiple sets of printing parameters based on the first and second prediction models. An objective function based on the predicted measurements is established, and a specification of a product and a printing expectation parameters are input to the objective function for outputting many sets of printing-suggestion parameters of the new product.

Abstract: A method for finding manufactured or to-be-manufactured products for defects includes obtaining basic information on processing history of products passed by each manufacturing machine at each processing workstation, and obtaining processing factor information of same, where each product is passed by a defect detection workstation after the product is passed by at least one processing workstation. The method includes obtaining quality information detected by each defect detection workstation. The method determines one or more problem manufacturing machines at one or more problem processing workstations according to the basic information on processing history and the quality information of the products. The method further determines one or more processing factors which influence the problem manufacturing machines according to the processing factor information of each manufacturing machine and the quality information of the products.

Abstract: An abnormality monitoring method includes obtaining multiple target machine process parameters that affect a measurement value of a preset product at a first measurement point of the preset product, constructing a measurement value prediction model corresponding to the first measurement point, calculating a degree of fit of the measurement value prediction model, aggregating the degree of fit of the measurement value prediction model, the estimated value of the first measurement point, the target machine process parameters corresponding to the first measurement point, and the parameter coefficients of the target machine process parameters, repeating the above steps for each of multiple measurement points, calculating an influence degree index value of each machine, process parameter, and outputting warning information of machine process parameters that exceed a first preset influence degree index value.

Abstract: A method for classification parts and components of a manufacturable device and a system of processing data relevant to such parts obtains data of the components, the components comprising many different types of parts to be assembled together. A clustering model can cluster the data to each cluster and the labeling module would label for the data in each cluster. A classification model classifies and assembles data into data classes that are labeled, also indicating assembly of the different types of components. The disclosure also provides an electronic device and a non-transitory storage medium.

Abstract: A method for finding manufactured or to-be-manufactured products for defects includes obtaining basic information on processing history of products passed by each manufacturing machine at each processing workstation, and obtaining processing factor information of same, where each product is passed by a defect detection workstation after the product is passed by at least one processing workstation. The method includes obtaining quality information detected by each defect detection workstation. The method determines one or more problem manufacturing machines at one or more problem processing workstations according to the basic information on processing history and the quality information of the products. The method further determines one or more processing factors which influence the problem manufacturing machines according to the processing factor information of each manufacturing machine and the quality information of the products.

Abstract: A method for carrying out measurements on a virtual basis to decrease the frequency of taking and analyzing actual physical samples and interruptions caused thereby includes obtaining production information of at least one production device; and generating prediction data of measured products and unmeasured products using the production information and a prediction model, the prediction data comprising critical dimension data of the product. A virtual metrology device and a computer readable storage medium are also provided.

Abstract: A method to set up the parameters of solder paste screen printer while in a new product introduction (NPI). The method includes establishing a solder-printing database of a predetermined product and a database of different specifications of products, and training a first prediction model by reference to a solder paste screen printer (SPSP) and a solder paste inspection (SPI) based on the solder-printing database. A second prediction model is trained by reference to the SPI based on the database of different products. The method further includes predicting parameters for products with different specifications under multiple sets of printing parameters based on the first and second prediction models. An objective function based on the predicted measurements is established, and a specification of a product and a printing expectation parameters are input to the objective function for outputting many sets of printing-suggestion parameters of the new product.