<![CDATA[Waste management has become a crucial issue due to the lack of adequate tools, with workplace accidents continuously rising in this industry. According to data from the ILO, there were 2.78 million deaths due to work-related accidents and diseases in 2017, an increase from 2.33 million in 2011. In the waste management sector, workers face injury risks such as fractures, eye damage, and spinal problems, with potential hazards arising from landfill collapses, fires, and getting caught in processing machines. This research aims to design an automated poka yoke system for waste shredding machines to enhance occupational health and safety (OHS) at TPS3R (3R Waste Management Facility). The methods used include the design and testing of a sensor-based automation system to prevent work errors. This system employs photoelectric proximity sensors and inductive proximity sensors to detect hands and metals entering the machine. Testing shows that the photoelectric sensor detects objects at distances of 5-25 cm in the organic and inorganic shredding area with a success rate of 100%, while the inductive sensor successfully detects metals such as screwdrivers, iron plates, and cans. The results of this study indicate that the implementation of an automated poka yoke system can minimize the risks of workplace accidents and machine damage due to human error. Additionally, this system is effective in enhancing operational safety.]]>
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