Improving throughput and decreasing costs
Forget station-by-station process improvement. AI-powered production finally lets you scale.
To improve a process, you must first measure it. On most manual assembly lines, this means engaging in manual time-and-motion studies.
These studies result in datasets that are too small and tainted by observation bias, with significant opportunity cost for any engineer investing their time.
But there hasn’t been an alternative.
AI-Powered Production drives line optimization
The core promise of AI-Powered Production is that routine data collection on manual assembly lines can be automated.
Drishti provides engineers with complete datasets of activities, not sampled activities. Each data point is backed by video.
This frees your people to devote much more time to identifying and realizing improvement opportunities. You can stop going station-by-station and start scaling for greater impact.
Users include:
- Process engineers for richer data on line operations, without manual measurement
- Product designers for better design- for-manufacturing techniques
- Line supervisors / team leaders for live line monitoring and problem resolution
Customer story
A tier-one supplier making car safety equipment deployed Drishti on a highly manual assembly line to understand the sources of variability and stoppages.
Drishti’s AI measured 525,147 work cycles over 3 months, providing a dataset with far greater fidelity for kaizen efforts.
With this much data, it was simple to pinpoint the problems and run improvement experiments. As a result, the customer improved throughput by 21% on a line that had previously been considered optimized.
Use case
Use case
What the press says
Just a few things you can do with continuous time study data
Line balancing and variability reduction
More effective process design
More efficient kaizen events
Faster standardized work analysis
Richer shift handover/passdown
Faster recovery from line stoppages
Accelerated NPI (New Product Introduction)
Benefits of AI-Powered Production
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