Intelligent production line cloud auxiliary self-organizing dynamic reconstruction method and application thereof

Abstract

The invention discloses an intelligent production line cloud auxiliary self-organizing dynamic reconstruction method and application thereof. The method comprises the steps that PA serves as a bid inviting manager to initiate a task notification message; after receiving the task notice, the MA and the SA evaluate the capabilities of the MA and the SA; the PA makes a corresponding decision according to the received feedback message until a Bid message is received, and determines a candidate bidder; the PA and the CA exchange information by using a Request message and an Interaction message, search reachable sets of the CA, and construct a transmission path between a starting point and an ending point by using common elements existing among the reachable sets so as to transmit the PA to a target position; under the condition of a plurality of MA or SA competition tasks, the optimal one is selected as a winner through priority multi-factor decision making, efficient dynamic reconstructionis achieved among the workpiece, the equipment, the conveying device and the cache device through self-organization, the scheduling efficiency and effect are improved through cloud centralized coordination, and efficient mixed flow production of various products is achieved.

Description

technical field [0001] The invention relates to a flexible production line resource scheduling method, in particular to an intelligent production line cloud-assisted self-organizing dynamic reconfiguration method and its application. Background technique [0002] Intelligent manufacturing is oriented towards personalized consumer demand, and it is necessary to require intelligent production lines to be highly flexible to meet the needs of multi-variety, small-batch, and mixed-flow production of customized products. Therefore, intelligent production lines generally have redundant processing equipment and mesh material conveying paths in structure; in terms of control methods, they generally have complex resource scheduling mechanisms, dynamic reconfiguration mechanisms, and fault-tolerant mechanisms. Therefore, the demand for flexible manufacturing leads to greater complexity and uncertainty in software and hardware for intelligent production lines than traditional assembly l...

AI Technical Summary

Problems solved by technology

Therefore, the demand for flexible manufacturing leads to greater complexity and uncertainty in software and hardware for intelligent production lines than traditional assembly lines.

[0003] Compared with the central control system, the self-organizing system based on intelligent negotiation has better flexibility, dynamics, and fault tolerance, and can better adapt to the distributed characteristics of the system, but it is difficult to achieve global performance optimization; although the global control of the cloud layer has It is beneficial to achieve global optimization, but its flexibility is poor, making it difficult to adapt to a fast and dynamic manufacturing environment

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