Method and system for predicting whether weaving machine is available or not based on productivity of weaving machine

Abstract

The invention discloses a method and a system for predicting loom availability based on loom productivity, belongs to the technical field of textile weaving, and is used for collecting production data of a weaving workshop. Cleaning the production data by using a pre-established data cleaning algorithm to obtain an effective production data sample set; according to the production data sample set, a productivity sample set in the same warp beam machining process is calculated; carrying out clustering calculation on the productivity sample set by using a bipartite clustering algorithm to obtain a productivity coefficient; and according to the productivity coefficient and the productivity sample set, calculating the loom completion prediction time. The method reduces the workload of manually confirming the machine time in a weaving workshop site, improves the timeliness of the weaving machine preparation process, and has great significance in the aspects of improving the field production efficiency, saving the production time, guaranteeing the product delivery time, improving the enterprise revenue and the like.

Description

technical field [0001] The invention relates to the field of textile and weaving technology, in particular to a method and system for predicting the availability of a loom based on the capacity of the loom. Background technique [0002] Most of the existing looms involved in the production of the textile industry do not have a loom prediction device or do not introduce a shrinkage rate that meets the workshop site when calculating the loom time, resulting in inaccurate looms. Therefore, at present, before the production of the warp beam of the loom is completed, the textile production personnel judge when to stop the loom based on experience and warp beam conditions. This method has the following defects: manual patrolling of the weaving production workshop and recording, the required labor costs It is difficult to find production practitioners who have experience and can accurately judge the machine time; if the machine time is not judged accurately, if the machine time is ...

AI Technical Summary

Problems solved by technology

[0002] Most of the existing looms involved in the production of the textile industry do not have a loom prediction device or the shrinkage rate that meets the workshop site is not introduced in the calculation of the loom time, resulting in inaccurate looms

Therefore, at present, before the production of the warp beam of the loom is completed, the textile production personnel judge when to stop the loom based on experience and warp beam conditions. This method has the following defects: manual patrolling of the weaving production workshop and recording, the required labor costs It is difficult to find production practitioners who have experience and can accurately judge the machine time; if the machine time is not judged accurately, if the machine time is advanced, the warp yarn raw materials on the warp beam will not be used up, resulting in waste, causing enterprises Direct economic loss; if the judgment of the remaining machines is too late, it will lead to a delay in the production scheduling of the warp beam preparation workshop, and may cause the length of the remaining warp beams of the machine that needs to be tied is not enough to carry out the warp tying process. The warp beam is re-dened and adjusted on the machine, which reduces production efficiency and causes waste of manpower

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