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Plug-and-play automation systems can be rapidly set up to meet sudden surges in demand - and quickly reconfigured when needs change.
Whether you turn to news outlets, tech magazines, or academic sources for insight, you're likely to hear that the COVID-19 pandemic is going to drive massive growth in automation, especially via robots. 1 The arguments in favor of this view seem reasonable: Main Street might look dead, but companies that provide shippable goods have been facing double, triple, or even 10 times their previous demand. Robots, the thinking goes, should be able to reliably do that repetitive physical work when many workers aren't safely able or willing to set foot in the building. What's more, access to the technology is getting less expensive, with "robots as a service" models allowing companies to pay per touch rather than dipping into precious capital reserves. And robots are becoming more capable.
In just the past few years, for example, we've seen a small number of companies building and selling AI-enabled robots to pick things out of bins, handle parts, tend machines, and test the latest electronics. This is impressive because it's high-mix work - that is, the products, the work conditions, the processes, and the final output shift regularly but also in surprising ways. Until recently, this made automation via robotics a nonstarter, because previous approaches to things like object detection, grasp detection, and placement verification relied on stable products, conditions, processes, and outcomes. Now? Toss some new objects into a bin, change the lighting, change their position and orientation, and these leading-edge systems can often handle it. Robotics companies are making similar advances in automating other physical jobs, such as materials transport, sorting, and palletizing. 2 So why wouldn't robots start flying off the shelves?
Because successfully putting robotics into production is a complex undertaking, and most companies aren't equipped to implement and benefit from these advanced systems. As we've studied how organizations and front-line workers are adapting to next-generation, AI-enabled robotics in manual work throughout the U.S., we've found that successful adaptation is rare. That stands to reason. History and decades of research tell us that when a qualitatively new form of automation comes along - anything from punchcard-driven looms to automated call patching -...