The invention belongs to the technical field of
industrial Internet of Things and intelligent manufacturing, and particularly relates to an intelligent
ranking method and
system for garment production based on
the Internet of Things. The method comprises the following steps: retrieving matched candidate genotypes from a production mode
gene map
library and analyzing the candidate genotypes into an initial
ranking scheme; calculating a personnel-equipment-process collaborative
adaptation degree coefficient of each
station in the scheme; an optimization objective function fusing the collaborative
adaptation degree, the historical environment
adaptation degree and the production constraint is constructed, and an optimal
ranking scheme is solved and output by adopting an improved
genetic algorithm; and dynamically constructing a process flow
potential energy field in production execution, and generating and executing a task
shunting scheduling instruction according to a
potential energy gradient. According to the method, the whole-process intelligent ranking from historical experience reuse and global multi-objective optimization to dynamic real-time scheduling is realized, the technical problems that production scheduling depends on experience, the optimization objective is single and dynamic response is insufficient in the flexible clothing
production line are effectively solved, and the production scheduling efficiency, the
production line balance rate and the
system adaptive capacity are remarkably improved.