The application discloses a
die casting machine parameter self-
adaptive optimization method and
system based on an
industrial internet, relates to the technical field of parameter optimization, and deploys an intelligent gateway and an
edge computing unit to collect process parameters, equipment states and
quality information of die castings of the
die casting machine in real time, drive state synchronization of corresponding digital twins, compare real-time states of the
die casting machine with standard states in a process
gene library, identify different types of disturbance events, adopt hierarchical collaborative decision-making, generate an optimization strategy sequence of parameters of the die
casting machine through
knowledge graph reasoning and a federal
global optimization model on an
industrial internet cloud platform, simulate and verify the optimization strategy by using the digital twins, select an optimal strategy to be converted into equipment control instructions, and issue the equipment control instructions to a target die
casting machine for execution. The application solves the problem that existing methods are difficult to adapt to dynamic disturbance events and cannot gather group experience for self-adaptive parameter optimization, and reduces the waste rate caused by fluctuations of the die
casting machine.