| Project/Area Number |
25289018
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Production engineering/Processing studies
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| Research Institution | 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校(能力開発院、基盤整備センター) |
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Principal Investigator |
Furukawa Yuji 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校(能力開発院、基, 能力開発院, 教授 (10087190)
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| Co-Investigator(Kenkyū-buntansha) |
KANNO Tsuneo 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校, 能力開発院、基・能力開発院, 教授 (60648921)
WADA Masaki 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校, 能力開発院、基・能力開発院, 教授 (70648948)
OKABE Masayuki 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校, 能力開発院、基・能力開発院, 教授 (20152332)
FUWA Teruhiko 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校, 能力開発院、基・能力開発院, 教授 (70219137)
TERAUCHI Mina 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校, 能力開発院、基・能力開発院, 准教授 (40648979)
IKEDA Tomozumi 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校, 能力開発院、基・能力開発院, 准教授 (80648923)
NINOMIYA Keiichi 独立行政法人高齢・障害・求職者雇用支援機構職業能力開発総合大学校, 能力開発院、基・能力開発院, 助教 (20726335)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥18,590,000 (Direct Cost: ¥14,300,000、Indirect Cost: ¥4,290,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2014: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
Fiscal Year 2013: ¥9,360,000 (Direct Cost: ¥7,200,000、Indirect Cost: ¥2,160,000)
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| Keywords | 身体性認知科学 / 技能伝承 / 技能習得 / フライス盤 / 暗黙知 / 神経系 / 動作分析 / 視線解析 / 感性情報学 / 機械工作・生産工学 / 教育工学 / 認知科学 / モデル化 |
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| Outline of Final Research Achievements |
In manufacturing processes, worker recognizes machining environment by some senses, worker’s central and autonomic nervous systems respond to the environment, and worker's body moves. As a result, the environment changes again, and this cycle is repeated. The purpose of this study is to construct the data acquisition and transfer model for milling machine technology based on embodied cognitive science that gives consideration to a series of these processes.
We constructed a user model of milling machine skill based on the Rasmussen's S-K-R (Skill-, Rule- and Knowledge-based) model. In experiments we measured physiological signals (prefrontal lobe measurement using NIRS, heart rate, etc.), physical motion data, and eye movement data during milling machine operation to compare these characteristics of expert to experienced. These results suggest that the expert operates on the skill- and/or the rule-based mode, and experienced operates on the knowledge-based mode.
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