Annular RGV trolley scheduling method based on SVR model prediction

Abstract

The invention relates to an annular RGV trolley scheduling method based on SVR model prediction, and the method comprises the steps that RGV trolleys in an annular RGV trolley system start to go to all stations for work, and the specific work and position information of the trolley is obtained through an RIFD and an encoder, which are disposed on the RGV trolley; each station sends an applicationsignal request to call the RGV trolley to reach a corresponding position of the station to work, a pre-established SVR prediction model starts to record an application sending time point of each station after sending an application from each station for the first time, self training is completed, and prediction of an application signal generation moment of the station is realized; and reasonable scheduling is realized according to the predicted occurrence time of the application signal of each station and the position information and the working information of each current RGV. According to the invention, the uncertainty of station application signal generation is reduced, and the reasonable scheduling of RGV trolleys is feasible. And meanwhile, the trolleys on the annular rail can be reasonably dispatched, and the production efficiency of an assembly line is improved.

Description

Technical field [0001] The invention relates to an RGV trolley scheduling method, in particular to a circular RGV trolley scheduling method based on SVR model prediction. Background technique [0002] With the development of science and technology, smart devices are widely used in production and life, which greatly improves the efficiency of production and facilitates people's daily life. RGV trolley is a kind of intelligent equipment that should be used in the assembly line and logistics warehouse management of the processing workshop. In the workshop operation line, the problem of unreasonable scheduling of RGV trolleys led to low utilization of trolleys on the guide rails, long waiting times for some stations, and problems such as the inability of the trolleys to enter the stations due to blockage, which seriously affected the efficiency of production and processing. At the same time, each station of the assembly line has uncertainty about the order and probability of the app...

AI Technical Summary

Problems solved by technology

On the production line of the workshop, the unreasonable scheduling of RGV trolleys leads to low utilization of the trolleys on the guide rails, long waiting time for some stations, and the inability of the trolleys to enter the stations due to blockage, which seriously affects the efficiency of production and processing.

At the same time, each station in the assembly line has uncertainty in the order and probability of the application for the trolley, which makes it more difficult to rationally dispatch the RGV trolley.

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