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The manufacturing labor gap shows no sign of slowing down according to a report by Deloitte Consulting and the Manufacturing Institute. It expects that the available manufacturing jobs will soar from 522,000 at the end of 2018 to 2.4 million by 2028. Robotic automation is being touted by many as a potential solution to this growing problem. However, before robots can cure the labor ills, it’s essential to recognize the barriers that must be overcome.
Robots and Manufacturing
Robotic automation has been around for several decades, and there are presently more than two million industrial robots at work. Currently, most robots operate in caged environments as there is a trade-off between safety around people and production speed. This, coupled with the vast amount of programming required to integrate robots, has constrained their wider adoption. For example, in assembly-line environments, robots are currently programmed to perform repetitive tasks on parts that are always in the same position and orientation. Before robots can bridge the growing labor gap, they need to be able to mimic the way people work on assembly lines. This will require them to cope with a more dynamic environment, such as parts not being perfectly oriented, while operating at viable production speed. As technology advances, robots will be able to carry out a much more extensive range of complicated and intricate tasks at a much faster pace.
So, what is holding robotic automation back?
The Safety Factor
Robots cannot currently navigate around obstacles in their environments at speed. Therefore, they are sequestered in cages to minimize the barriers entering their work area. This is the biggest challenge that must be solved before manufacturers can expand the role of robotic automation and help address the labor gap. As robots become smarter in the coming decades, they will be able to recognize when people and other machines are within their environment and work in harmony with them. This will allow them to take on more tasks and operate at a much more productive pace, finally delivering many of the much-touted efficiencies.
The Programing Hurdle
Robots are inherently more complex to deploy than software systems, and as a result, the pace of adoption has been much slower and very expensive. Robotic automation today requires a vast amount of programming to integrate within manufacturing workflows. Every single assembly line decision requires extensive programming and rigorous testing to make sure each decision outcome is addressed while the robots are not in production. As robots become smarter with specialized software and hardware, coupled with machine learning and sensors, it will be much easier to integrate them into more industrial settings. Robots will be able to recognize, learn, grip, and react quickly, which will significantly expand the range of actions that they can carry out, and it will also slash the programming burden.
Man & Machine: Working Together in Harmony
Robots and people are unable to work together at a productive pace today due to safety concerns. As robots become smarter and more flexible, they will be able to work near people and other robots at an efficient pace. Robots will be able to take on more complicated tasks such as cleaning, as well as more physical tasks, including harvesting, bending or kneeling. When this occurs, people will be able to focus on higher-value work. However, the dystopian vision of a fully autonomous manufacturing plant currently seems improbable. Human intelligence and flexibility will still be an essential component that automation will not be able to replicate for at least a decade.
The role of robots in manufacturing is still relatively limited. If robots are to solve the growing labor shortage in US manufacturing, then they will need to significantly expand both the type of tasks that they can carry out and the speed at which they do so. Robots will need to operate safely as well as understand and react to unplanned variables at speed. This will require robots to be more dexterous, flexible, have spatial awareness, and of course, the ability to learn. Until robotic automation conquers these hurdles, it will remain a band-aid rather than a cure for the widening labor gap.