Overview Case Study: GAF
In the challenge GAF put forward in the context of the Made Smarter Technology Accelerator programme, GAF was looking to employ machine vision and sensor technology to assess product conformance to specification, characterising surface anomalies and identifying the process conditions when they occur, and evaluating whether critical machine components are appropriate to continue using.
To address this challenge, we partnered with Dakota Systems, a pioneer and expert in digital transformation and smart manufacturing. Since 1999, Dakota Systems has been a trusted partner for global, engineering-driven brands such as Nokia, Motorola, United Airlines, Shure, Siemens, and John Deere. In collaboration with Dakota Systems, zetamotion created a unique product conformance solution for GAF.
Using cutting-edge AI and modern sensor technologies, this novel product replaced tasks and techniques typically carried out by human inspectors, helping to create higher throughput and consistency, while reducing material wastage and production downtime.
Through this project, we learned that:
- Labour cost for manual QC in manufacturing is skyrocketing in industrialised countries.
- Computer Vision and AI has been commoditised, shifting value to customised solutions.
- Global manufacturers are looking to customised solutions that will give them a competitive edge, rather than purchasing the same computer vision QC solution available to their competitors.
- The current competitive landscape for computer vision quality assurance is a crowded space filled with many companies overstating the capabilities of their products while offering trivial solutions.
Following the success of our current large-scale pilot, our technology is scheduled to be deployed to all of their 28 factories in the US.
GAF is projecting a 99 per cent reduction in QC assessment time.
GAF is projecting a 90 per cent reduction in assessment error.
GAF is projecting a 10% reduction in overall waste.
We are also currently working with manufacturers in the UK, helping them to eliminate inspection errors, accelerate their production speed, and significantly reduce material waste, thus improving their bottom line while contributing to their goals toward Zero Waste and Zero Carbon.