Industry 4.0 has a blind spot: human beings.
People still perform 72% of factory tasks. Even in an age of robotics and IIoT, people are the main contributor to value—and, alas, to variability. Unfortunately, techniques for measuring human effectiveness haven’t materially changed in a century. They remain manual and impossible to perform at scale. People are effectively invisible to analytics. Read more: The 100-year-old problem in manufacturing
Drishti digitizes the tasks performed by people.
Imagine if you could perform time and motion studies on every single cycle. Or use AI to help operators perform with greater precision. Or play back video of every cycle ever performed in your factory. That’s what Drishti does. Using AI, machine learning and computer vision, Drishti turns human actions into data.
Why Drishti matters
Don’t think about stations. Think about lines. And then, think bigger. Drishti unlocks the dataset you’ve always wished you had. It’s about percentage points, not basis points. Manufacturers use Drishti for true digital transformation across productivity, quality and traceability. And operators use it to become more competitive in an increasingly automated world.
Without Drishti, you focus on spot improvements. A station here, a line there, a week of kaizen once a year. Drishti gives you the data to find solutions at scale. You can quantify true cycle time, you can balance your lines… well, that’s just day one.
Without Drishti, you have a massive quality overhead. Some customers tell us that 39% of their resources are devoted to checking people’s work. Drishti gives you the insight you need to move closer to the purest ideal of lean manufacturing: that deviations should be addressed at the source. And your quality investment shifts accordingly.
Without Drishti, you have to painstakingly reconstruct past events. Root cause analysis takes weeks. Cause and effect are never certain. Remedies are overly broad, and still not effective. With Drishti, you can review video of every unit assembled. Traveling through time within your factory is as simple as using YouTube.