A method and system for predicting loom completion based on loom capacity

Abstract

The invention discloses a method and system for predicting loom start-up based on loom production capacity, which belongs to the technical field of textile weaving and is used for collecting production data in a weaving workshop; using a pre-established data cleaning algorithm to clean the production data to obtain effective production data samples According to the production data sample set, calculate the production capacity sample set in the process of warp beam processing; use the binary clustering algorithm to cluster and calculate the production capacity sample set to obtain the production capacity coefficient; according to the production capacity coefficient and the production capacity sample set, calculate the loom machine forecast time. The present invention reduces the workload of manually confirming machine time in the weaving workshop and improves the timeliness of the loom preparation process, which is of great significance in improving on-site production efficiency, saving production time, ensuring product delivery, and improving enterprise benefits.

Description

technical field [0001] The invention relates to the technical field of textile and weaving, and in particular, to a method and system for predicting the loom of a loom based on the production capacity of the loom. Background technique [0002] Most of the existing looms involved in the production of the textile industry do not have a machine prediction device or the machine time calculation does not introduce a shrinkage rate that conforms to the workshop site, resulting in inaccurate machines. Therefore, at present, before the end of the production of the loom beam, the textile production personnel completely judge when the loom is ready based on the experience and the condition of the warp beam. This method has the following defects: manual patrol of the weaving production workshop and recording, the required labor cost Large; production practitioners who have experience and can accurately judge the machine time are hard to find in the labor market; 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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