| Project/Area Number |
10650108
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
機械工作・生産工学
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
SAITO Yoshio Tokyo Institute of Technology, Professor, 工学部, 教授 (00108218)
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| Co-Investigator(Kenkyū-buntansha) |
INABA Chikao Tokyo Institute of Technology, Research Associate, 工学部, 助手 (10223231)
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| Project Period (FY) |
1998 – 1999
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| Project Status |
Completed (Fiscal Year 1999)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 1999: ¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 1998: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | Single Batch Production / Evaluation of KANSEI / Learning Control / Wire Cutting / Genetic Programming / Simulated Annealing / シュミレーティドアンニーリング / 生産システム / 感性工学 / ロボット加工セル / 粘土 / クレイモデル |
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| Research Abstract |
There are many intelligent subjects in a manufacturing system, and it is important to control a machine tool for an appropriate cutting condition. Moreover, to construct a single batch production system it is necessary to make a clear sensing and decision making system based on evaluation process for KANSEI. Analyzing the knowledge of skilled workers, determinations are conducted with the intuitive decision procedure using both of genetic programming and simulated annealing method. The lerning process of human is mainly dependent on the relationship between an action and its result, that is correspondent to the analyzed data and evaluation results. In this field, the genetic programming and simulated annealing are significantly available to apply to a practical case like a single batch production.
Therefore, an intelligent decision making method for settle an actual cutting condition was developed in this project, considering the conceptual construction method with self learning process for autonomous robot machining cell system. Fundamental research was carried out regarding to the 6-axis industrial robot and sensing system. Through a numerous practical experiments, the validity of proposed system has been proved with valuable results.
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