Connect with us


How Tech is helping factory workers enhance their efficiency




Assume you’re a worker on an automaker’s factory floor. Your profession entails following a set of instructions to assemble brake pads, but miss a vital step in the construction of one brake pad because it’s the end of your shift and you’re tired. The error goes unnoticed, and the brake pad is sent on to the next workstation, where it will be installed in the car and sent out into the world. The consequences of that minor blunder are enormous: It can be fatal for the car’s driver, and cost the company financially, besides ruining its reputation. 

Consider a scenario in which a monitor warns the worker just as he is about to make a mistake. He can fix it, finish the action, and go on. “Think of it like Word’s spell check feature. If you make a mistake, the software will show you a red squiggly line to indicate it. You make the necessary corrections and go on. After that, no one in the world knows you made that error,” says Prasad Akella, the creator of the world’s first collaborative robots, or cobots (collaborative robots), when working at General Motors in the 1990s. 

That’s exactly what Drishti, an American business created by Akella in 2016 and based in Bengaluru for R&D, is doing. Computer vision is used by a camera placed above each station on a production floor to collect workers’ movements. The continuous stream of video is fed into Drishti’s unique deep-learning software, which monitors the work of every floor employee. It can detect errors and inform workers in “near real-time” (within two to three seconds), as well as track how long it takes a worker to complete a task so that bottlenecks, if any, can be avoided. Drishti, on the other hand, employs technology to supplement rather than replace workers. 

To put it differently: just as Google mines text to derive insights, and Apple’s Siri parses voice inputs, Drishti is mining video streams, explains Akella. “It’s never been done before because it’s a hard problem to solve. But the opportunity is huge.” 

The real-world applications of this in time could be staggering, and we look forward to see what ingenious uses the world’s best minds come up with.