AW: What are the best practices to follow when implementing robotic systems to ensure safety?
AG: A best practice is to use digital twin and 3D simulation technologies to include safety considerations and definitions as part of the initial robotic task planning. This ensures an optimal design and avoids rework on the shop floor that would balance the task optimization with safety requirements.
For example, process simulation software with robot safety management can provide a comprehensive solution that supports all capabilities, ensuring end-to-end safety in robotic operations design. Leveraging these capabilities during planning and process development helps validate safety concepts, visualize safe spaces and safety-wrapped robots, and analyze them against safety standards and rules.
JBJ: The best practice is to follow state-of-the-art industry standards such as the ISO 10218 series, which integrates safety design concepts throughout the entire life cycle of the machine design. This includes risk assessment, safety specification, system design, validation testing, installation and maintenance activities.
AW: What strategies should be employed for continuous monitoring and maintenance of robots to ensure ongoing safety?
EF: I recommend these three strategies:
- Use sensors and IoT devices on the shop floor to monitor the condition of machinery in real-time and analyze the data from these sensors to identify patterns and predict when maintenance is necessary.
- Implement vision systems and other sensors to enhance the machine’s or robot's ability to detect and avoid obstacles.
- Employ digital twin technology, simulation and advanced software for continuous monitoring and predictive maintenance to identify anomalies and schedule repairs before issues arise.
JBJ: The primary strategy has been to follow the robot manufacturers instruction handbook for guidance on manual inspection and preventative maintenance intervals. These traditional preventative maintenance strategies are still necessary, but often require shutdown of the robot cell and result in a higher likelihood of unplanned maintenance.
Additionally, predictive maintenance techniques are important to ensure ongoing safety integrity. By using control system data to monitor robot performance, common failures can be identified before they occur. For example, detecting minor deviations in robot position and repeatability can be a sign of robot joint or brake wear. Once these deviations go outside acceptable limits, appropriate maintenance measures can be taken.
AW: What are the most common challenges manufacturers face when ensuring robot and machine safety, and how can they overcome them?
JBJ: as per OSHA, human error contributes to most safety incidents in the workplace. To overcome this challenge, a proactive safety culture is necessary. This includes comprehensive safety awareness, technician training, safe work practices and safety policy enforcement.
A proactive best practice is to consider the risk assessment as a living document. With good near-miss documentation practices and ongoing risk reduction monitoring, manufacturers can stay on top of potential gaps in safety and close them before problems occur.
EF: For robots, defining the safety settings and rules for the robot controller and the PLC to make sure all safety scenarios and requirements are met, is the most common challenge manufacturers face. This is especially true when it relates to the positions and size of objects in the robotic cell. Here, again, I recommend use of digital twin and 3D simulation tools.
Listen to this Automation World podcast on industrial machinery best practice safety tips.