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Ergonomic Postural and Biomechanical Analysis of Manual Weeding Operation in Agriculture Using Digital Human Models

机译:数码人模型手工杂草业务的人体工程学姿态和生物力学分析

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The agricultural land of India is approximately 181.95 million ha (55.3% of entire area) where the majority of the landholding (i.e. 78.92%) are in the category of a small and marginal group. Weed control is one of the most challenging and labour-intensive operations in agriculture utilizing about 20% of human energy and 25% of labour requirement. Further weeds alone reduce about 50-70% in crop yields. Manual weeding operation is most widely used by small and marginal landholding. Manual operation is associated with different types of health hazards, such as musculoskeletal disorders (MSD), pain in various body parts, injury, etc., among farmworker due to ignorance of the capabilities and limitations (anthropometric and biomechanical characteristics) of the potential user group in the design of tools and equipment. Moreover, practising manual and wheel hoe weeding required more human energy, i.e. vary from 300 to 400 man-h/ha and 50 to 125 man-h/ha, respectively. The present study attempted to evaluate existing manual weeding using wheel hoe in the digital environment, using digital human modelling (DHM) for the prevention of work-related musculoskeletal disorders. The DHM has become commonly used for human-centred product design. The DHM tools have the potential to analyse and improve the product before it's ever launched. Therefore, the emphasis in this paper is to investigate the postural and biomechanical behaviour in manual weeding practices for the various user group (i.e. 5th—95th percentiles) of Arunachal Pradesh. The outcome of the postural analysis found to be more discomfort rating for the larger group of population (i.e. 50th-95th percentiles) for male workers in wheel hoe operation. Further, the compressive forces on L4-L5 lumbar spines showed higher values for wheel hoe for both male and female. A similar type of approach using DHM for others existing agricultural tools and equipment would improve human comfort, safety and overall productivity.
机译:印度的农业用地约为18195万公顷(占整个地区的55.3%),其中大多数土地金属(即78.92%)处于小型和边缘集团的范畴。杂草控制是利用大约20%的人力和25%的劳动要求的农业最具挑战性和劳动密集型的行动之一。进一步的杂草单独减少作物产量的约50-70%。手动除草操作是由小型和边际土地融合使用的广泛应用。手动操作与不同类型的健康危害相关,例如肌肉骨骼紊乱(MSD),由于潜在用户的能力和限制(人体测量和生物力学特性)无知,在农业工部中,各种身体部位,伤害等。集团在设计工具和设备的设计中。此外,练习手册和轮子锄草化需要更多人类能量,即分别从300到400人-H / ha和50至125人-h / ha之间变化。目前的研究试图使用数字人类模型(DHM)在数字环境中使用滚轮锄头评估现有的手动杂草,以防止与工作有关的肌肉骨骼障碍。 DHM已常用于以人为本的产品设计。 DHM工具有可能在它推出之前分析和改进产品。因此,本文重点是调查各种用户组(即第95百分位数)阿鲁纳恰尔邦的手动除草实践中的姿势和生物力学行为。历史分析的结果发现,对于车轮锄头操作中的男性工人,对较大的人口(即50级 - 第95百分位数)更具不舒服的评级。此外,L4-L5腰椎上的压缩力显示出雄性和雌性的车轮锄头的较高值。使用DHM的类似类型的方法对于其他农业工具和设备,可以提高人类的舒适性,安全性和整体生产力。

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