Discourse domain based dynamic division and learning fuzzy scheduling rule mining method

A dynamic fuzzy and fuzzy technology, applied in control/regulation systems, instruments, adaptive control, etc., can solve problems such as difficult to obtain scheduling schemes

Active Publication Date: 2015-06-10
正大业恒生物科技(上海)有限公司
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Problems solved by technology

For the above-mentioned microelectronics production line scheduling problem on a large scale, it is difficult to obtain a satisfactory scheduling scheme by using the above sched...

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  • Discourse domain based dynamic division and learning fuzzy scheduling rule mining method
  • Discourse domain based dynamic division and learning fuzzy scheduling rule mining method
  • Discourse domain based dynamic division and learning fuzzy scheduling rule mining method

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Embodiment Construction

[0109] The dispatching method of the present invention relies on the relevant data acquisition system, and is realized by a dispatching system client and a dispatching server. The schematic diagram of the hardware and software architecture of the present invention in actual microelectronics production line scheduling is as follows: figure 1 As shown, the embodiments of the present invention are as follows.

[0110] Step (1): collect the above-mentioned number of processes, number of varieties, process path of each Lot and the number of Lots included, number of machines, processing menu and processing time of each operation on each machine, and Setup for switching between menus on each machine Scheduling-related information including time, maximum batches of each menu on each machine, etc. are stored in the scheduling database, and an instance of the microelectronics production line scheduling problem to be solved is formed;

[0111] Step (2): Initialize, set the following ba...

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Abstract

The invention relates to a discourse domain based dynamic division and learning fuzzy scheduling rule mining method and belongs to the field of advanced manufacturing, automation and information. The method is characterized in that an attribute discourse domain dynamic fuzzy division method is raised, and a novel fuzzy scheduling rule form and Aprior algorithm based fuzzy scheduling rule intelligent mining method is given based on the dynamic fuzzy division method. In each fuzzy scheduling rule, each condition attribute has two linguistic variables to be output as a classification label to be used for representing the scheduling priority of two to machining operations. The corresponding attributes of the two linguistic variables are subjected to discourse domain division through simple fuzzy scheduling division dynamic fuzzy division, and a harmony search algorithm is designed to perform optimization learning on key parameters. A good scheduling effect can be produced by applying the method to the microelectronic production line scheduling problem with the minimum average running time serving as the scheduling target.

Description

technical field [0001] The invention belongs to the fields of advanced manufacturing, automation and information, and in particular relates to a fuzzy scheduling rule mining method based on domain dynamic division and learning for microelectronic production lines with batch characteristics. Background technique [0002] Aiming at the large-scale microelectronics production line scheduling problem with batch characteristics and the scheduling goal of minimizing the average flow time, there are mainly the following types of scheduling methods: precise optimization methods, heuristic scheduling rules, intelligent optimization methods, etc. For the above-mentioned microelectronics production line scheduling problem on a large scale, it is difficult to obtain a satisfactory scheduling scheme by using the above scheduling method. Therefore, it is of great significance to propose a scheduling method with better performance for the above-mentioned microelectronics production line sch...

Claims

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Application Information

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IPC IPC(8): G05B13/04
Inventor 刘民刘涛郝井华
Owner 正大业恒生物科技(上海)有限公司
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