课题基金 / 基金详情

Cooperative Research on Intelligent Manufacturing Techniques

Cooperative Research on Intelligent Manufacturing Techniques
智能制造技术合作研究
批准号:
10044173
负责人:
YOKOTA Takao
金额:
$4.42万
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (B).
财政年份:
1998
资助国家:
日本
项目状态:
已结题
起止时间:
1998 至 2000

项目摘要

项目成果

YOKOTA Takao的其他基金

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相关文献

中文摘要
翻译
该合作研究项目的目的是利用遗传算法(GA)、神经网络(NN)等人工智能(AI)技术开发智能制造技术,包括生产调度、工艺规划、最优设施选址、制造单元设计与控制、从CAD数据中识别特征、制造信息网络设计等。在第一年(1998),我们研究了多产品制造系统的基本制造技术,并建立了一些多产品制造系统的模型。研究了遗传算法、神经网络等人工智能技术的基本机理和特点。第二年(1999),提出了基于遗传算法和神经网络的生产调度问题、工艺计划问题、最优设施选址问题、制造单元设计与控制问题、CAD特征识别问题、制造信息网络设计等问题的求解方法。在过去的一年(2000),我们将基于人工智能的方法应用于生产调度、工艺计划、最优设施选址、制造单元的设计与控制、CAD数据的特征识别、制造信息网络设计等实际尺寸问题,最终对所开发的方法进行了评估。并对本次合作研究项目做了最终报告。
英文摘要
The purpose of this cooperative research project is to develop intelligent manufacturing techniques, which are for production scheduling, process planing, optimal facility locating, design and control of manufacturing cells, feature recognition from CAD data, design of manufacturing information network, and so on using Artificial Intelligent (AI) techniques such as Genetic Algorithm (GA), Neural Network (NN). We needed the research term of three years to accomplish the above purpose.In the first year (1998), we investigated basic manufacturing techniques for multi-product manufacturing systems and developed some models for such systems. And fundamental mechanisms and properties of AI techniques, such as GA and NN, were investigated. Further, we applied GA and NN for basic scheduling problems, such as Job-shop Scheduling Problem (JSP) to verify the performances the techniques.In the second year (1999), we developed some solution methods based on GA and NN for production scheduling problems, process planing problems, optimal facility location problems, design and control problems of manufacturing cells, feature recognition from CAD data, design of manufacturing information network. And evaluated the solution methods developed through many test problems to verify efficiencies of the methods.In the last year (2000), we applied the AI-based methods for real-wold size problems of production scheduling, process planing, optimal facility locating, design and control of manufacturing cells, feature recognition from CAD data, design of manufacturing information network to finally evaluate the developed methods. And we made final report of this cooperative research project.
期刊论文(58)
专著(0)
科研奖励(0)
会议论文
T.Yokota,T.Taguchi and M.Gen: "A Solution Method for Optimal Cross Section Design Problems of Simple and Multiple Beams Using Genetic Algorithms"Beijing Mathematics. 4・2. 75-84 (1998)
T.横田,T.田口,M.Gen:“利用遗传算法解决简单多梁截面优化问题的方法”北京数学4・2(1998)。
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通讯作者:
Y.Tsujimura and M.Gen: "Parts Loading Scheduling in a Flexible Forging Machine Using an Advanced Genetic Algorithm"Intelligent Manufacturing. 10・2. 149-159 (1999)
Y.Tsujimura 和 M.Gen:“使用先进遗传算法的柔性锻造机的零件装载调度”智能制造 10・2。
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玄 光男,井田憲一: "Mathematicaニューラルネットワークと最適化" 共立出版, 164 (1998)
Mitsuo Gen、Kenichi Ida:“Mathematica 神经网络和优化”Kyoritsu Shuppan,164 (1998)
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T.Taguchi and T.Yokota: "GA-based Method for Optimal Design Problem of System Reliability with Interval Coefficients"Engineering Valuation and Cost Analysis. 3. 365-373 (2000)
T.Taguchi 和 T.Yokota:“基于遗传算法的区间系数系统可靠性优化设计问题的方法”工程评估和成本分析。
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共 45 条
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