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Manufacturing robotics is following an innovation path similar to machining and fixed automation systems. Though the ROI is most easily measured in efficiency and cost savings, manufacturers are also looking for robotic technology to help them resolve pain points in their operations and create new opportunities. Examples include linking processes more efficiently or reducing the need to outsource functions.
The growth path for small and medium-sized manufacturers (SMMs) with robotics is 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. Specifically, adoption is dependent upon robots having more human-like dexterity and self-control.
Making Robots Easier to Use
To better support small and medium-sized manufacturers, scientists and engineers at the National Institute of Standards and Technology (NIST), specifically NIST Labs, are working to close a significant gap between cutting-edge technology and what is currently deployed on many manufacturing shop floors. This gap is largely due to the lack of measurement science required to verify and validate emerging research which reduces adoption hesitancy and risk.
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 focusing on:
- 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; and
- 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. Improvements in programming with HMIs have allowed some robots to be programmed by welders who model the movements and actions for the process in question.
Robotic Assembly Next
Early adoption of robotics in manufacturing has focused on repetitive tasks that do not require special skills or provide added value. Examples include palletizing, loading / unloading, material handling and case packing (Figure 1).
Figure 1: The most popular robotic applications by usage.
At this time, assembly operations account for only 2 percent of robotic applications, though NIST researchers and industry experts believe it holds much promise for widespread adoption among SMMs as manipulation technology improves. Likely areas for expanding assembly work include:
- Connecting electrical components;
- Threading and inserting fasteners; and
- Wire routing.
One of the challenges for robotic assembly is the multitude of variables that must be accounted for when performing complex operations. For example, the optimal force required for a gripper to pick up and move a part might not be the same as the force needed for a threading operation later in the production. As tactile sensing improves, robots will be able to grip everything using the proper force, potentially reducing the steps needed for that production process.
NIST Labs work includes innovative designs utilizing six-axis force and torque sensors for grasping, including mechanisms that mimic human hands.
Dexterity and Versatility
NIST Labs are working on about a dozen test methods for gripping and manipulation using the Institute of Electrical and Electronics Engineers standards platform for the four most common types of robotic grippers:
- Vacuum – A standard end-of-arm tooling used for flat, smooth surfaces, often used in palletizing and packaging
- Pneumatic – Also known as “bang bang grippers” for the noise made in industrial operations, this versatile type often is used for small objects in pick-and-place operations
- Hydraulic – The strongest — and messiest — of industrial grippers
- Servo-Electric – Highly flexible and cost effective, these allow for different material tolerances when handling parts
NIST Labs work includes innovative designs utilizing six-axis force and torque sensors for grasping, including mechanisms that mimic human hands. 
These advancements are increasingly emerging on shops floors and feature:
- Customizable end effectors that can easily be removed and replaced;
- Improved dexterity with three-finger adaptive grippers, capable of manipulating fragile items and minimizing tool changes;
- Robotics using machine learning from intelligent sensors on grippers to teach themselves how to approach objects; and
- Grippers combining multiple technologies, including vacuum grippers with fingers or two separate arms, and gripper configurations at the same workstation to allow for multiple tasks, increasing both speed and reliability.
Keys to Success
One of the appeals of robotics is that a robot can be built and programmed to do almost anything. However, unlike fixed automation systems, there is a tradeoff between robotics functionality and ease of use. The more functionality you build into a robot, the more environmental considerations must be taken into the conditional requirements, which makes it more difficult to program and integrate the robot into operations for additional tasks.
Small-batch planning can also be difficult with robotics if manufacturers do not have the right support system in place, including the right staff. Robotics adoption will increase when SMMs understand how robotics systems, with the proper set up and programming, save retooling costs. It is not out of the question that manufacturers with 10 or fewer employees will robotics expert on hand to assure overall equipment effectiveness.
Robotics Guide
To increase the use of robotics technologies for manufacturing operations, especially among SMMs, Catalyst Connection, part of the MEP National Network, has put together an easy-to-understand guide to robotics. It identified a number of keys to success for exploring the use of robotics in manufacturing. Recommendations include:
- Identify resources, including an internal champion, to get the level of support required;
- Identify your needs or pain points;
- Prioritize supporting tools
- ID manufacturing examples
- Start small and keep it simple
- Build a business case, but be sure to factor in 2x–4x hardware costs for tooling, accessories and the complexity of integration.
MEP Centers Can Help
For small-to-medium manufacturers, the initial deployment of robotics systems can be intimidating. For US companies, the experts at a local MEP Center are ready to help you explore — and potentially adopt — robotics. Connect with them to see how robotics can help you expand your business by adding new functionality.
Information about NIST Labs research provided by Elena Messina, Jeremy Marvel and Joseph Falco.
Editor’s Note: This article was republished with permission from National Institute of Standards and Technology’s Manufacturing Extension Partnership (NIST MEP).
About the Author:
Andrew Peterson is a general engineer in the National Institute of Standards and Technology (NIST) Manufacturing Extension Partnership’s (MEP) Extension Services Division who facilitates efforts to improve advanced manufacturing technology services and supplier scouting services among other focus areas. He started at NIST in November of 2019 with the goal of providing professional engineering services to the MEP National NetworkTM in a variety of focus areas. Prior to joining NIST, Andrew worked as a compliance engineer in for a medium sized manufacturer in the bottled water industry. Andrew holds a Master of Engineering degree in mechanical engineering from the Rochester Institute of Technology as well as a Bachelor of Science degree in mechanical engineering from Marquette University.
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