This invention discloses a
furnace temperature control method, relating to the field of
intelligent control of
electronic packaging welding processes. The method includes: collecting real-time temperature data and
welding process parameters of the substrate to be welded, and acquiring post-weld deformation data; aligning and fusing the real-time temperature data, process parameters, and deformation data to extract key features of the
furnace temperature curve, and constructing a data
record set by associating them with the deformation of corresponding measuring points; based on the data
record set, establishing a quantitative prediction model using
regression analysis or
machine learning algorithms; under preset process constraints, optimizing the
furnace temperature curve
setpoint with the predicted warpage as the optimization objective, calculating the corresponding predicted warpage using the quantitative prediction model, generating the optimal furnace
temperature curve setpoint, and sending it to the
welding equipment for execution. By constructing a quantitative prediction model using temperature data from sensitive points and post-weld deformation, the optimal furnace
temperature curve is generated through reverse optimization to suppress welding warpage.