Highlights: Compressed air strategy was evaluated as a grain entrapment prevention method. Nozzle types affected compressed air efficiency. Open ½ inch nozzles performed best. Mid-scale experiment confirmed compressed air utility in breaking grain clumps. Dust, fungal, and noise levels exceeded maximum limits during operations, and PPE must be worn properly before using compressed air to break grain clumps.
Abstract: Grain entrapment, a severe and often fatal agricultural hazard, continues to pose a significant challenge in grain storage and handling. These incidents are often due to out-of-condition grain blocking outlets, leading to workers frequently entering the grain bin to dislodge grain. This study evaluates the utility of compressed air as a preventive measure to break up grain clumps located at bin outlets by conducting pilot and full-scale experiments using an air compressor. This study also evaluated potential hazards due to the use of air compressors. Three nozzle types were tested: open ½ inch, Crimped ½ inch, and the AirSpade. The findings indicated that the open ½ inch nozzle was the most efficient, with an average clearing time of 15 minutes per run, outperforming the crimped and AirSpade nozzles. Noise levels during operation ranged up to 105 dBA, with dust and fungal spore concentrations exceeding safety limits inside the grain bins and returning to acceptable levels shortly after operation. Full-scale testing indicates that compressed air can be useful in unclogging bins. The study underscores the potential of compressed air to enhance grain handling safety, offering practical safety recommendations and suggesting the need for further research to optimize and standardize its use in preventing grain entrapment.
Highlights: ½ open nozzle and ½ crimped nozzle were the most effective nozzles in removing out-of-condition grain clumps. ½ open nozzle and ½ crimped nozzle effectiveness were significantly correlated with the hardness of the grain clump. High pressure compressed air could be an effective method for breaking grain clumps stuck in the center sump. A shop air compressor is not effective in breaking up out-of-condition grain clumps.
Abstract: Grain entrapment is an agricultural injury in which a person enters a grain bin or silo to dislodge a blockage caused by out-of-condition grain and becomes partially or fully entrapped or engulfed in grain. Each year in the US, approximately 33 grain entrapments occur, where roughly 50% of the entrapped people die. In 2022, at least 42 individuals were entrapped with grain, the largest number of incidents since 2010, when 60 incidents were reported. The persistence of this issue despite substantial investment in training programs highlights the urgent unmet need for testing alternative prevention solutions to reduce grain entrapments. This study aims to test and validate the effectiveness and safety of using high-powered air compressors as tools to break apart out-of-condition grain blockages. A small-scale experiment was conducted with an air compressor and five different nozzles. The effectiveness of each nozzle was measured against hardness, moisture content, and percent grains in each clump. The ½ inch open nozzle and ½ inch crimped nozzle were found the most effective nozzles in reducing the size of grain clumps. Both nozzle results were highly correlated with the hardness of the clump. Results indicate that compressed air could be an effective solution to address grain clumping and blocking auger sumps.
Highlights: Thermal infrared array sensors can detect simulated human presence at distances up to 3m. Simulated human models for testing thermal infrared arrays need to be heated. Testing models should be designed to incorporate clothing, PPE, and features that change heat distribution. It is critical to match the pixel observable area and the expected size of heated regions at critical distances.
Abstract: This project consists of two sets of experiments using low-cost thermal infrared arrays-the TPAM 166 L3.9 array and the AMG8833, which were operated as 16-pixel arrays. These sensors were tested to determine how well they detected a simulated human model. The TPAM 166 L3.9 was tested with a heated, water-filled, clothed model representing a standing adult human. The AMG8833 was tested with a heated and non-heated version of the ISO 18497 simulated human model, which represented a seated human. These sensors were able to respond to heated models at distances up to 3 m from the sensor. The unheated human model did not produce a response. For heated models, the strength of the detection increases at shorter distances if the warmest parts of the model were visible to the sensor. As the warm parts of the model approached the sensors, the number of pixels impacted and the temperatures that they detected increased. However, detection decreased as the simulated human model approached at distances less than 1.5 m if the sensor was focused on a clothed section of the model. For deployment, the pixel observable area should match the expected size of heated regions considering PPE, clothing, and operational considerations. It is critical to consider pixel observable area and pixel response levels rather than the sensor level characteristics, as detection will occur at the pixel level.
Highlights: Five annual training topics were: Year 1) Tractor/Equipment Roll-Over Hazards, Year 2) ATV/UTV Operation Hazards, Year 3) Tractor/Equipment Operation Hazards, Year 4) PTO/Entanglement Hazards, and Year 5) Agricultural Machinery Transport Hazards Associated with Use on Public Roadways. To assess the influence of agricultural machinery safety training, student work-based, journal reflections were collected through the Agricultural Experience Tracker to qualitatively describe their production-based agricultural experiences. Most student journal entries focused on machinery operations.
Abstract: The Supervised Agricultural Experience Safety Award program was launched with Montana, Utah, and South Dakota agriculture teachers. A combination of video conferencing and in-person training workshops were offered to school-based agriculture teachers in Montana, Utah, and South Dakota. Zoom webinar workshops were held with teachers during the COVID-19 pandemic. The five annual training topics included: Year 1) Tractor/Equipment Roll-over Hazards, Year 2) ATV/UTV Operation Hazards, Year 3) Tractor/Equipment Operation Hazards, Year 4) PTO/Entanglement Hazards, and Year 5) Agricultural Machinery Transport Hazards Associated with use on Public Roadways. To assess the influence of agricultural machinery safety training, students' journal reflections were collected through the Agricultural Experience Tracker. Students' production-based agricultural experiences were coded by USDA National Agricultural Statistics Service (NASS) Commodity Codes, describing students' safety reporting using Supervised Agricultural Experience (SAE) journal entries, and quantifying teachers' workshop participation. A total of 2,257 journal entries were reviewed from Montana, Utah, and South Dakota. A total of 760 unique student journal entries were associated with a teacher participating in the training program. Most student journal entries focused on machinery operations. A total of 49 journal entries specifically reported safety. A total of 203 journal entries recorded the use of tractors. A total of 160 agricultural production work entries (38.8%, n = 412) noted crop production as the agricultural production work experience. The results provide recommendations for developing an application model for translation using an FFA award structure.
Highlights: Comprehensive view of occupational safety research: Prioritizing topics in robotics and autonomous machines. Barriers to safety research: Logistical, intellectual property, timeline, and funding challenges. Importance of surveillance or tracking system: Documenting fatalities, injuries, and near misses/good catches. Priority safety research needs: human-machine interaction, adoption of automation in the work setting, and surveillance/tracking. Collaboration with technology developers: Overcoming barriers and exploring emerging technologies and potential safety implications.
Abstract: In 2022, the SAfety for Emerging Robotics and Autonomous AGriculture (SAFER AG) Workshop was held to discuss and understand emerging challenges related to safety, occupational safety research needs, workforce implications, and other issues associated with robotics and autonomous machines in agriculture. This paper presents the major findings from the occupational safety research track of the workshop. This track identified existing hurdles to conducting occupational safety research including logistical barriers, intellectual property concerns, long timelines, and lack of funding. Considerations for developing a tracking or surveillance system for adverse events as well as exposure related to these technologies were also discussed, emphasizing the need for a comprehensive system. Finally, the priority occupational safety research needs identified during the session were related to human and non-human machine interaction, adoption of automation in the work setting, and event tracking/surveillance. To overcome barriers to research, collaboration between occupational safety researchers and technology developers is crucial. Enhancements to existing surveillance systems can facilitate better understanding of captured events. Additionally, prioritizing research on worker risk from robotics and autonomous machines in agriculture is essential. The integration of robotics and autonomous machines in agriculture has revolutionized the industry but requires evidence-based safety research, outreach, and education to ensure worker safety and health.
Highlights: Walnut dust is listed as combustible by OSHA. This designation could trigger requirements for walnut hullers and shellers to install expensive sprinkler systems and approved dust control systems. Recognized standard combustible dust screening tests showed that walnut huller and sheller dusts were not flammable solids and should not be considered combustible.
Abstract: Fires and explosions at agricultural facilities have been an issue across the world. While some agricultural industries like sugar and grain handling facilities have had issues with fires or explosions and have been subject to regulations on dusts for many years, many other agricultural processors have not. The U.S. Occupational Safety and Health Administration (OSHA) lists walnut dust as combustible. Some local governments and insurance companies have attempted to apply that designation to dust at walnut huller and sheller facilities. Facilities that generate potentially combustible dusts must abide by National Fire Protection Association standards that require expensive sprinkler systems and approved dust control systems and may have difficulties obtaining approval for building permits and insurance coverage. Tests following United Nations Manual of Tests and Criteria, Part III, Subsection 33.2.1, Test N.1, "Test Method for Flammable Solids" were conducted to determine the combustibility of dust samples collected at walnut hulling and shelling facilities in California. According to these tests following the UN method, the walnut huller and sheller dusts were not flammable solids and therefore should not be considered combustible dusts.
Highlights: Decrease fatalities and injuries in agricultural ATV incidents. Protect youth ATV riders in agricultural incidents Use engineering controls to reduce agricultural ATV crashes. Comprehensive perspectives on ATV incidents (Australia, Canada, Israel, Sweden, and the USA).
Abstract: All-terrain vehicles (ATVs) or quad bikes have raised serious concerns, especially in rural areas where they are used for occupation (i.e., agriculture and forestry) and recreation (i.e., hunting and recreational riding). ATVs are unstable vehicles, and their incidents have been linked to factors such as the rider's physical capabilities (such as strength, anthropometry, and visual acuity) and behavior, safety awareness (training), application of personal protective equipment, lack of protective structure, and regulations. This manuscript presents perspectives of ATV safety experts from several countries, including Australia, Canada, Israel, Sweden, and the USA. The topics include the state of the art in youth riders, engineering control methods, stability, protective structures, safety rating systems, training and education, personal protection equipment, and new regulations.
Highlights: The friction force is one of the important influence factors on tire slip, overturning, and rollover characteristics of tractors. The maximum static friction forces of three different tractors were measured on paved roads under various loading conditions. The prediction models of the previous study were improved through regression analysis for the measured data. The model that uses the front and rear axle's reaction forces as variables showed the highest prediction accuracy.
Abstract: The overturning and rollover safety of a tractor located on a slope is decreased by tire slip, which is affected by static friction force. Existing regression models for predicting the static friction force of tractors demonstrate inadequate accuracy, necessitating further refinement. Therefore, this study was conducted to improve the accuracy of the maximum static friction force prediction model developed in a previous study for tractors with a front-end loader. As a result of measuring the maximum static friction, it tended to increase as the rear ballast weight increased and to decrease as the payload increased. The accuracy of the regression models in this study was significantly improved compared to that in previous studies. The regression model that used the reaction forces of the front and rear axles as variables exhibited the highest accuracy, followed by the model using the rear axle reaction only. The reaction force of the rear axle had a greater effect on the maximum static friction than that of the front axle. The developed regression model will predict the maximum static friction force of a tractor with a front-end loader on paved roads with high accuracy using the reaction forces of the front and rear axles. Future studies will focus on extending these predictions to various soil types and under dynamic conditions.
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