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CONVERGING: Safety Assessment and Monitoring

Safety Assessment and Monitoring

In the face of escalating competition in the manufacturing sector, it is important to acknowledge the significance of deriving valuable insights from real-time data for process optimization, efficiency augmentation, and safety assurance. By examining data amassed from various sources such as sensors, machines, and production lines, it is possible to attain a comprehensive view of operations and pinpoint areas that require enhancement.

In the prevailing manufacturing scenario, this data-centric strategy is geared towards efficiency, for instance, to identify bottlenecks or equipment malfunctions. However, data analysis can also be pivotal in bolstering safety within manufacturing environments. By tracking real-time data pertaining to machine performance and operator behavior, it is possible to, for instance, identify anomalies that could hint at potential hazards. This preemptive approach can result in the implementation of immediate remedial measures, averting accidents and ensuring the safety of our workforce.


In the manufacturing industry, safety is paramount, and real-time monitoring of safety risks is indispensable to prevent mishaps and protect workers. In line with the guidelines of CONVERGING, the development of a safety and monitoring module will devise a data analysis system that will perpetually monitor the safety of robotic applications in real-time, while adhering to the prescribed safety requirements and standards. The module will gather data from a wide array of sources, including sensors, machine-learning algorithms, and safety equipment.

The Safety Assessment and Monitoring module primarily monitors the status and behaviors of the SRP/CS of the CONVERGING system. It also archives safety-related data and events to facilitate the application of data modeling techniques for insight extraction through visualizations. This will contribute to creating a safer work environment for all employees and reduce the risk of expensive downtimes.

The SAM module complements the SRP/CS by facilitating real-time data acquisition and storage, along with a thorough analysis of system performance in relation to the SRP/CS. To accomplish this, the module leverages existing data from SRP/CS and interconnected devices, such as robots and human tracking, while adhering to several safety protocol requirements stipulated by relevant standards. Moreover, it offers a ROS API that enables the transmission of safety-related information to other systems for operation-related functionalities.