The invention relates to the technical field related to process parameter management, in particular to a multi-
modal data driven foamed aluminum process parameter optimization method and
system, and the method comprises the steps: obtaining a foamed aluminum process parameter set, and configuring a process
feature vector; according to the
porosity standard deviation, the density uniformity index and the modified
compressive strength variable coefficient of the foamed aluminum finished product, a
melt temperature regulation and control subsequence and a
foaming agent adding subsequence are determined, a control
instruction set is generated in combination with a process
feature vector, and synchronous issuing is performed by using an
industrial Internet of Things gateway. The technical problems that foamed aluminum technological parameter optimization mostly depends on
single parameter adjustment, the matching degree of parameter adjustment and finished product
quality characteristics is low, and foamed aluminum production stability is limited are solved, collaborative optimization of
melt temperature adjustment,
foaming agent adding and mold pressure adjustment is achieved, a control
instruction set is generated, and the production efficiency is improved. Therefore, the
porosity standard deviation of the foamed aluminum finished product is reduced, the density uniformity index is improved, and the technical effects of process stability and finished product quality consistency are improved.