Intelligent decision method based on artificial intelligence technology and ROPN technology

A technology of intelligent decision-making and artificial intelligence, applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve the problems that the POPN model cannot be realized, the granular computing cannot overcome the deadlock problem, and the real-time decision-making cannot be realized, so as to prevent The effect of system resource deadlock, improving self-learning, enhancing the ability of rapid response and self-evolution

Active Publication Date: 2020-01-10
埃克斯工业有限公司
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AI Technical Summary

Problems solved by technology

[0008] In view of the problems of the above research, the purpose of the present invention is to provide an intelligent decision-making method based on artificial intelligence technology and ROPN technology, to solve the deadlock problem in the actual production process that cannot be overcome by granular computing in the prior art; the POPN model cannot realize decision-making The results are optimized, and the real-time decision-making cannot be realized, resulting in problems such as the given decision is not practical.

Method used

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  • Intelligent decision method based on artificial intelligence technology and ROPN technology
  • Intelligent decision method based on artificial intelligence technology and ROPN technology
  • Intelligent decision method based on artificial intelligence technology and ROPN technology

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Embodiment

[0042] Taking semiconductor production as an example, see Y.Qiao, N.Q.Wu, and M.C.Zhou, “Real-time scheduling of single-arm cluster tools subject to residency time constraints and bounded activity time variation,” IEEE Transactions on Automation Science and Engineering, vol.9, no.3, pp.564-577, July 2012.

[0043] Taking the single-arm manipulator combined equipment scheduling problem with time constraints as an example, the ROPN model construction method and process are introduced, and detailed demonstration and analysis are made on the time characteristics of the scheduling process, real-time control rules, and wafer dwell time delay. Based on the analysis, four feasible scheduling algorithms under different production conditions are obtained.

[0044] For ease of understanding, the production conditions are abstracted as a, b, c, d, e, and f below, and the scheduling scheme is represented by capital letters such as A, B, C, D, E, F, and G, and the following assumptions are ...

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Abstract

The invention discloses an intelligent decision method based on an artificial intelligence technology and an ROPN technology which belongs to the field of artificial intelligence technologies, such asa granular neural network, the reinforcement learning, etc., and the ROPN industrial system modeling technology, and solves the problem that the granular calculation in the prior art cannot overcomethe deadlock during an actual production process. The method comprises the steps of constructing an ROPN model based on the acquired real-time data of an industrial system and an ROPN technology; constructing a granular neural network decision model, namely an intelligent production scheduling model, based on the acquired historical data of the industrial system and the granular calculation, and training the intelligent production scheduling model through the subsequently acquired historical data of the industrial system after the model is constructed to obtain a trained intelligent productionscheduling model; and based on the ROPN model and the intelligent scheduling model, deciding the problems to be decided, the real-time data of the industrial system, the problem data in the real-timescheduling problems and the historical data of the industrial system to obtain an optimal scheduling scheme. The method is used for obtaining the optimal decision during the industrial control and scheduling process.

Description

technical field [0001] An intelligent decision-making method based on artificial intelligence technology and ROPN technology is used to obtain the best decision in the process of industrial control and scheduling, and belongs to the field of artificial intelligence technology such as granular neural network and reinforcement learning and ROPN industrial system modeling technology. Background technique [0002] Artificial intelligence technology is one of the cores of the new generation of information technology. It is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is regarded as an important driving force for a new round of technological revolution, industrial optimization and upgrading, and an overall leap in productivity. It is an important strategic tool to win the initiative in global technological competition. [0003] At present...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/04G06N3/08
CPCG06N3/08G06Q10/04G06Q10/0631G06Q50/04Y02P90/30
Inventor 刘斌李杰乔岩李倓宋泰然郭宇翔曹健孙国龙周孟初
Owner 埃克斯工业有限公司
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