Knitting MES production planning and scheduling method based on big data mining

Abstract

The invention discloses a knitting MES production planning and scheduling method based on big data mining, wherein the method belongs to the field of textile engineering application. The method comprises the following steps of S1, establishing a multidirectional knitting production data model; S2, establishing a big data analyzing platform based on a Hadoop distributed platform; S3, mining a planning scheduling restraining factor in a MapReduce frame by means of an Apriori correlation rule mining algorithm; S4, analyzing an order arranging priority according to a contract requirement; S5, integrating the arranging priority and the planning scheduling restraining factor, and obtaining an order arranging Gantt chart; and S6, performing real-time monitoring on ERP and ZigBee data, and when abnormities such as order delivery data change, knitting process updating and knitting machine sudden fault occur, dynamically adjusting a production plan.

Description

technical field [0001] The invention relates to a knitting MES production planning and scheduling method based on big data mining, which belongs to the field of textile engineering applications. Background technique [0002] In the entire production process of knitting enterprises, production planning management and scheduling work occupy a relatively important position, which is related to important data such as product quality, finished product grade, delivery cycle and equipment utilization rate. At present, most knitting enterprises still arrange production according to the experience of the workshop director or workshop dispatcher. Due to the large amount of orders and frequent changes in varieties, it is inevitable that order scheduling will not be timely, poor flexibility, and responsibility The division is not clear. Most of the production planning arrangements rely on paper documents to be passed from higher departments to lower departments. The review process is c...

AI Technical Summary

Problems solved by technology

At present, most knitting enterprises still arrange production according to the experience of the workshop director or workshop dispatcher. Due to the large amount of orders and frequent changes in varieties, it is inevitable that order scheduling will not be timely, poor flexibility, and responsibility The division is not clear

Most of the production planning arrangements rely on paper documents to be passed from higher departments to lower departments. The review process is cumbersome and the storability and traceability of paper documents are not strong.

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