23, March 2017
Collaborative Robotics Enabling Manufacturing Workforce and Productivity Growth
Guest blog post by Jeremy Marvel, research scientist and project leader at the U.S. National Institute of Standards and Technology (NIST).
In early 2016, the International Organization of Standardization (ISO) published ISO Technical Specification (TS) 15066, which outlines safety requirements for collaborative robots. The American National Standards Institute, ANSI, adopted ISO/TS 15066 later that year as ANSI/RIA Technical Report R15.606 (RIA is the Robotic Industries Association). These documents outline safety functions that maintain a safe distance between people and active robots, and limit the transfer of forces and pressures should contact between a person and a robot occur. Robots that adhere to these requirements are considered inherently safe.
Leading up to these publications, sales of robots designed and marketed as being “collaborative” had been rising steadily. This market growth has since increased, and is projected to continue increasing well into the next decade with double-digit annual growth.
What is driving this growth? To what tasks are collaborative robot technologies being applied? And most importantly, what are the impacts of using collaborative robots?
Collaborative Robots as a First Step Toward Automation
The technology is deceptively straight-forward. These are, for all intents and purposes, industrial robots. Yet, on average, collaborative robots are lighter, cheaper, and consume less power than their traditional industrial robot brethren. Their safety and ease-of-use, however, are what set them apart.
Collaborative robots are purpose-driven machines intended to ease the burdens of integration and control. Featuring direct lead-through programming and graphical user interfaces, collaborative robots are designed to enable non-expert users to train robots without requiring advanced degrees or expertise in proprietary programming languages. Some even feature advanced artificial intelligence to provide online parameter optimization and adaptive behavior in the face of process uncertainty.
Many collaborative robots are also outfitted with advanced sensor systems that enable off-the-shelf functionality. Camera-integrated collaborative robots can recognize and track objects, and the force-sensing that drives the robots’ soft touch can also be applied to part fitting and assembly. Advances in adaptive gripper technologies also enable robots to grasp a wide variety of different objects gently—yet firmly—without requiring complicated algorithms or tool changers.
The resulting product is a safe, adaptive robot that is easy to integrate. It moves somewhat slowly and is typically limited to lifting objects between 11 and 30 pounds, but it is repeatable, and will work tirelessly day and night.
Collaborative Robots as a Workforce Enabler
It is easy to imagine dozens of applications for which collaborative robots could benefit virtually any shop floor. Yet, the tasks for which collaborative robots are used primarily are those that require light-duty, repetitive automation with high turnover. Specifically, they are being put to work doing material handling and tending jobs that do not directly benefit the manufacturing process.
Simply put, collaborative robots are tools used to augment and enhance the capabilities of the workforce. They are used to offload the monotonous tasks that might otherwise fill workers’ days. Picking and placing parts, packaging finished goods, and loading and unloading machine tools are not value-added applications for skilled labor. With collaborative robots taking over some of these dull and dangerous jobs without requiring fencing, the workforce is left to focus their trade skills on more productive tasks.
Robotics and Industry Growth
Industries benefiting from collaborative robots include automotive, aerospace, food and beverage, and plastics. Most collaborative robot installations see a return on investments within one year. Moreover, studies indicate the growth of robotics use in general has led to net increases in manufacturing employment and factory output worldwide. Many of the new jobs created are attributed to the introduction of new products and services, which was enabled by the use of robotics and automation.
What does this mean for collaborative robots and the future of manufacturing in the U.S.?
The face of manufacturing is evolving, becoming increasingly lean and agile. The workforce must become more technologically adept to keep up. The U.S. Bureau of Labor Statistics predicts that the number and the salaries of many engineering and technician jobs will continue to grow through the coming years. With the increasing reach and pervasiveness of the Industrial Internet of Things, every aspect of manufacturing is on its way to being fully connected, monitored, and optimized. These advances in process flow monitoring and optimization, in turn, reduce waste, increase reliability, and prevent costly errors and logistical delays.
Collaborative robots are just one part of this new face of manufacturing. The entire U.S. manufacturing supply chain is slated to grow with the technology, with an increasingly skilled workforce producing better quality goods cheaper, faster, and more efficiently than they are now. This, in turn, drives innovation and competitiveness.
The post Collaborative Robotics Enabling Manufacturing Workforce and Productivity Growthappeared first on the Manufacturing Innovation Blog.
About the Author: Jeremy Marvel
Jeremy A. Marvel is a research scientist and project leader at the U.S. National Institute of Standards and Technology (NIST) in Gaithersburg, MD. Dr. Marvel received the bachelor’s degree in computer science from Boston University, Boston, MA, the master’s degree in computer science from Brandeis University, Waltham, MA, and the Ph.D. degree in computer engineering from Case Western Reserve University, Cleveland, OH. Prior to NIST, Dr. Marvel was a research scientist at the Institute for Research in Engineering and Applied Physics at the University of Maryland, College Park, MD. He joined the Intelligent Systems Division at NIST in 2012. His research interests include intelligent and adaptive solutions for robot applications, with particular attention paid to human-robot and robot-robot collaborations, multirobot coordination, industrial robot safety, machine learning, perception, and automated parameter optimization. Dr. Marvel currently leads a team of scientists and engineers in metrology efforts at NIST toward collaborative robot performance, and developing tools to enable small and medium-sized enterprises to effectively deploy robot solutions.