Productivity gains reach 15% at apparel manufacturer’s assembly lines
The Problem
A Shareholder and Director of a very large apparel maker with 70,000 workers supplying global clothing brands approached Infolytx to help increase the productivity of their assembly lines. Existing processes relied on floor supervisors to track work stoppages and their root causes, whether mechanical failure, raw material shortages, or idle employees. Management wondered whether AI could augment these supervisors so that issues could be flagged earlier, more thoroughly, and without bias.
The Solution
The Infolytx team leveraged its expertise in Computer Vision to analyze the factory’s current surveillance footage and used specially enhanced Machine Learning models to monitor and alert factory supervisors via a mobile app when relevant stoppages were observed in the assembly line being analyzed. Fine-tuning the application led to the enthusiastic adoption of the solution among the floor supervisors.
The Outcome
A whopping 15% increase in productivity was noted when unmonitored lines were compared to the monitored lines after adjusting for external factors. Infolytx engineers trained appropriate Machine Learning algorithms to accurately identify work stoppages and then alert the relevant line supervisors.
The industrial client has now included Infolytx in key client meetings and signed on for additional work and POCs.