| Project/Area Number |
16K03848
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Management
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| Research Institution | Fukushima University |
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Principal Investigator |
DONG Yanwen 福島大学, 共生システム理工学類, 教授 (90292458)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | セル生産 / 適性 / GATB / ５因子モデル / 社会的比較 / 外れ値 / 人的要因 / 人的資源管理 |
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| Outline of Final Research Achievements |
As the performance of cell production systems depends largely on workers’ aptitude, we applied experimental study method to investigate the relationship between the performance of production cells and workers’ aptitude. We administered the Japanese General Aptitude Test Battery (GATB) and extracted a new score that correlates significantly to the workers’ performance in cell production and represents workers’ spatial aptitude. We also administered FFPQ-50 (a short form of Five Factor Personality Questionnaire), it is clear that unemotionality and introversion have a significantly positive correlation to the performance of production cells. Then we constructed classification models so that the workers with low aptitude can be identified. Furthermore, we have addressed the effect of social comparison in cell production systems and confirmed that announcing relative performance information can improve the performance of production cells significantly.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，一般職業適性検査（GATB）の適性得点から作業者の空間判断力を表す新たな適性指標を抽出し，また性格特性５因子モデルを初めてセル生産に適用し，作業効率にもっとも関連の強い適性を明らかにしたうえ，適性が顕著に低い作業者を判別する分類・学習モデルを構築したため，セル生産における作業者の適性に関する新しい知見を与え，一定の独創性と新規性がある。本研究で提案した分類・学習モデルは，作業者の適材適所を実現し，生産性の向上とストレスの低減に貢献できる。さらに，作業者同士の競争を促す社会的比較の適用結果は直接にセル生産現場で実用し，セル生産のさらなる発展に寄与することができる。
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