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Identifying safety strategies for on-farm grain bins using risk analysis

Abstract

The potential for grain bin accidents exists each year on Arkansas farms and farms across the nation. The trend toward increasing utilization of on-farm grain drying and storage could lead to an increase in grain bin accidents. The sharp contrast between a safe, efficient operation and one that leads to injury or death can be represented as sets of farmer-decisions and subsequent chance events. A model was constructed to define the risk associated with grain bin entry and inbin activity so that safety interventions could be identified and implemented to reduce the probability of injury and death. A survey was distributed to Arkansas grain farmers to gather data on the level of safety education, storage techniques, operations management, and other parameters. The data collected from the survey provided quantitative input of many of the model’s probability-distribution functions. Using a fault tree (with parallel modes of failure) in conjunction with a Monte Carlo simulation technique, we evaluated six safety intervention strategies and identified the one with the greatest potential for reducing the risk of serous injury or death. As part of senior design in biological engineering, plans are underway to design and test a probe that can locate and break bridged grain (a common risk factor in grain bin management) while working outside the bin on the ground

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