Parallel computing production scheduling system and method based on dynamic load

A parallel computing and production scheduling technology, applied in manufacturing computing systems, computing, computing models, etc., can solve problems such as the inability of static plans to adapt to resource changes, the disconnect between planning and manufacturing execution, and the inability of dynamic plans to adapt to the actual situation on site.

Pending Publication Date: 2020-07-28
华至云链科技(苏州)有限公司
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Static plans cannot adapt to dynamic resource changes; dynamic plans cannot adapt to the actual situation on site, which eventually leads to a disconnect between planning and manufacturing execution. The goal of this invention is to realize "real-time self-adaptation" between dynamic plans and dynamic resources

Method used

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  • Parallel computing production scheduling system and method based on dynamic load
  • Parallel computing production scheduling system and method based on dynamic load
  • Parallel computing production scheduling system and method based on dynamic load

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Embodiment Construction

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0032] like Figure 1-5 As shown, this embodiment is a parallel computing production scheduling method based on dynamic load, including a process encoder, a task priority decision maker, a task queue manager, a forecast solver, and a genetic algorithm solver. The process encoder Accepting the task flow, the task priority decision maker: by establishing a Bayesian decision-making machine learning model, the task queue manager prepares a task pool with priority attri...

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Abstract

The invention discloses a parallel computing production scheduling system and method based on a dynamic load. The system comprises a process encoder, a task priority decision maker, a task queue manager, a prediction solver and a genetic algorithm solver, the process encoder receives a task flow. The task priority decision maker is used for preparing a task pool with priority attributes by establishing a Bayesian decision machine learning model, the prediction solver is used for calculating the optimal predicted completion time of tasks, and the genetic algorithm solver is used for allocatingall tasks in the task pool to entity resource equipment and executing and feeding back the tasks. An artificial intelligence model chain is formed by constructing a Bayesian priority decision model, atask time self-learning prediction model and an optimization solver machine learning model based on a parallel architecture, resource load real-time tracking and feedforward prediction calculation are realized through a dynamic load table, and real-time autonomous resource allocation and scheduling of a task group are realized.

Description

technical field [0001] The present invention specifically relates to the technical field of discrete processing and manufacturing, in particular to a dynamic load-based parallel computing production scheduling system and method. Background technique [0002] In discrete manufacturing, especially in large-scale dynamic production scenarios, due to the complex working conditions of the manufacturing site, there are usually large deviations between the production plan and the actual execution results. Static plans cannot adapt to dynamic resource changes; dynamic plans cannot adapt to the actual situation on site, which eventually leads to a disconnection between planning and manufacturing execution. The goal of the present invention is to realize "real-time self-adaptation" between dynamic plans and dynamic resources. Contents of the invention [0003] The purpose of the present invention is to overcome the above-mentioned problems in the traditional technology, and provide ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/04G06K9/62G06N20/00G06Q50/04
CPCG06Q10/06312G06Q10/04G06N20/00G06Q50/04G06F18/24155Y02P90/30
Inventor 宛田宾袁泉李权威沈光明武文亚许保殿
Owner 华至云链科技(苏州)有限公司
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