Manufacturing robotics is to some extent following a similar path of advances to those in machining and fixed automation systems. Though the ROI is most easily measured in efficiency and cost savings, manufacturers are looking for robotic technology to help them resolve a pain point in their operation or to create new opportunities. It might be to link processes more efficiently or eliminate the need to outsource a specific function or two.
The growth path for small and medium-sized manufacturers (SMMs) with robotics is therefore increasingly focused on applications and added capabilities, not just efficiency and continuous improvement. The key to increasing adoption of robotics in SMMs is making the robots easier to use and re-use.
In essence, adoption is dependent upon robots having more human-like dexterity and self-control.
NIST Labs Has Designs on Making Robots Easier to Use
Scientists and engineers at NIST Labs are working to close a significant gap between cutting-edge technology and what is currently deployed on many manufacturing shop floors. This is largely due to the lack of measurement science to verify and validate emerging novel research and thus reduce the risk of adoption.
One of the priorities of NIST’s Intelligent Systems Division is the advancement of grasping, manipulation and safety performance that will enable SMMs to effectively deploy robot solutions. This work includes performance metrics, test methods and associated measurement tools that can become industry standards.
The research is advancing robotics in manufacturing by providing:
- Better repeatability so that robots can reliably perform movements and actions within an X,Y,Z coordinate system space
- Easier-to-use human machine interfaces (HMIs) for operators to program tasks and interact with robotics
- New designs for grippers that allow more precise, and human-like movements
- Better safety and situational awareness
Among the advances now reaching the shop floor is software in handheld HMI devices that translates human coordinate references (right/left, toward/away) into conventional cartesian X, Y, Z coordinates. This allows operators to more easily program collaborative robots.
