Fundamental Study for the Construction of Monitoring and Recovering System in Automated Manufacturing System
Project/Area Number |
09650149
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
機械工作・生産工学
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Research Institution | Kansai University |
Principal Investigator |
YANO Akishige Kansai University, Faculty of Engineering, Professor, 工学部, 教授 (40067533)
|
Co-Investigator(Kenkyū-buntansha) |
YAMAGUCHI Tomomi Kansai University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (10268310)
HIGUCHI Masahiro Kansai University, Faculty of Engineering, Professor, 工学部, 教授 (50067732)
|
Project Period (FY) |
1997 – 2000
|
Project Status |
Completed (Fiscal Year 2000)
|
Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2000: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1999: ¥100,000 (Direct Cost: ¥100,000)
Fiscal Year 1998: ¥300,000 (Direct Cost: ¥300,000)
Fiscal Year 1997: ¥2,800,000 (Direct Cost: ¥2,800,000)
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Keywords | Monitoring system / Sound of machining / Automatic conveyance system / Scheduling for conveyance / Neural-network / Autonomous moving / Group intelligence / Inspired system / 搬送 / スケジューリング / 移動ロボット / 遺伝的アルゴリズム / 協調 / 自立 / 知的行動 / 自律 / モニタリング / 研削加工 / 共同作業 / 行動創発 / 音認識 / 学習 |
Research Abstract |
The goal of this research is the acquisition of fundamental technologies that are essential to the construction of monitoring and recovering system in an automated factory. Many researches for automated manufacturing have been studied. However, most of these researches are the development of NC machines, automatic assembly machines and material handling, and a little ones are the study of monitoring systems, which are indispensable to the avoidance from troubles in a manufacturing process. So we grappled with the development of monitoring system to machining process and intelligent conveyance system in order to construct precise and practical monitoring/recovering systems and we acquired three results. First, we developed precise monitoring system to machining process by using sounds. The precise monitoring system for tool conditions, particularly tool wear, by using sounds has been hardly developed. In our system, the frequency of peculiar sound spectrum is input to neural-network and tool conditions can be recognized precisely. Secondly, we proposed behavior-inspired system, which referred to protein-translated process by DNA in the cell. This system can inspire new and complex behaviors, like avoidance from obstacles and going to a goal, from only a few basic programs. Thirdly, scheduling system of conveyance in a factory was developed. In this system, each of multiple locomotive robots can be assigned works of conveyance so as to finish all works with high performance. First, each robot schedules works individually. Next, all robots communicate each other to decide the most efficient schedule for all works of conveyance. We confirmed the efficiency of this system by simulations and experiments, in which compact locomotive robots were actually applied to it.
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Report
(5 results)
Research Products
(9 results)