Automatic production scheduling optimization management information model based on big data analysis and processing technology

Abstract

The invention provides an automatic production scheduling optimization management information model based on a big data analysis and processing technology. The model based on the construction method comprises a customer requirement information collection module, a customer information processing module, a production plan scheduling module and an inventory classification module. The concrete steps include that customer requirement information is established; data are summarized to a data exchanger center to perform requirement classification processing on the customer information; current inventory rate is intelligently calculated, and corresponding customer order tasks are established; a production plan is issued; production is organized; product offline inventory classification (to be delivered) is performed; and the customer order production and processing tasks and product offline inventory classification are completed and the detailed data are returned to the data exchanger center to be stored, and the corresponding tasks are eliminated. The standby inventory coefficient is intelligently calculated, product demanding requirements of users are predicted and reasonable standby inventory is performed according to the product demanding habit of the users and various other factors so that the production and processing plan meeting the product demanding requirements of the users can be automatically arranged under the premise of guaranteeing supply.

Description

technical field [0001] The invention relates to an inventory optimization management system in a logistics distribution mode, in particular to an automatic production scheduling optimization management information model based on big data analysis and processing technology. Background technique [0002] Before the present invention was proposed, the traditional industrial fields generally carried out production capacity distribution according to the planned economic model. With the continuous increase of automobile production and sales and the increasingly intensified competition, production efficiency and cost control have become the endogenous driving force for the rapid development of automobile companies. In the traditional cooperation between steel and automobile companies, due to different production cycles and models, fluctuations in any link of the supply chain will have an unpredictable impact on the assembly of the final vehicle. Therefore, it is necessary to store a...

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Problems solved by technology

[0002] Before the present invention was proposed, the traditional industrial fields generally carried out production capacity distribution according to the planned economic model. With the continuous increase of automobile production and sales and the increasingly intensified competition, production efficiency and cost control have become the endogenous driving force for the rapid development of automobile companies. In the traditional cooperation between steel and automobile companies, due to different production cycles and models, fluctuations in any link of the supply chain will have an unpredictable impact on the assembly of the final vehicle. Therefore, it is necessary to store a large amount of To ensure accurate and timely supply of materials and parts, this not only inhibits the efficient operation of the supply chain, but also makes the operating costs of enterprises continue to rise, and cost pressures continue to exist for a certain period of time

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