As factories and manufacturing facilities have become “smarter” through sensors, robotics and other connected technologies, a potential trove of data has been created that can be mined for insights into bottlenecks and other areas of concern. improvement. Or maybe even just to speed up processes that would otherwise require significant manual work.
But much of this data generated is unstructured and not easy to leverage from the start. Although big data analysis has been a pillar of industries such as finance and logistics for years, it has not fully reached the manufacturing field. This has created a gold mine of untapped knowledge and, more recently, a nascent market for technologies designed to capture and make sense of a wide range of manufacturing data.
Last month, Oden Technologies, founded in the United Kingdom and now based in New York, raised a Series B round of 28.5 million dollars to stimulate the growth of its data analytics platform for manufacturers. Germany's Daedalus raised $21 million to apply ai to precision manufacturing factories. And Belgium's Robovision got $42 million to bring computer vision intelligence to industrial machinery.
Is now ai/”>EthonAI In turn, as the Swiss startup states ai/news/ethonai-closes-chf-15m-series-a-financing-round/”>Announced Thursday that it has raised CHF 15 million ($16.5 million) in a Series A financing round led by Index Ventureswith the participation of General Catalyst, Earlybird and Founderful.
EthonAI finds defects in products.
Founded in Zurich in 2021 by CEO Julian Senoner and CTO Bernhard Kratzwald, EthonAI can train ai models for specific use cases, for example in electronics manufacturing where the customer provides images of defect-free products and EthonAI . ai/products/inspector/”>Inspector The software can then identify surface defects in products during the manufacturing and assembly process. Apple recently acquired a company called DarwinAI that has a similar purpose, in terms of automating the visual quality management process in component manufacturing.
More broadly, however, EthonAI can combine data from across a company's entire manufacturing setup, from sensors to line stopsand create a picture of where they are performing well and where they are not, and even compare performance across multiple installations to see where there might be room for improvement.
In its three-year history, EthonAI has landed some pretty high-profile clients, including Siemens and chocolate maker Lindt.
Digging deeper into EthonAI's target markets reveals that semiconductor manufacturing is a particular area of focus, although the company has not disclosed any specific customers in this space. However, low performance is a known concern in the chip industry, where defects in the silicon wafers may affect the number of actual chips usable in post-production. Notably, Apple reportedly reached a deal last year with chipmaker TSMC that had apparently particularly low rates of return (only 55% at that time), with Apple reach an agreement pay only for good and known wafers. saving billions of dollars in the process.
EthonAI, for its part, says it works with a “leading semiconductor producer” that uses its platform to merge multiple data sets to perform analytics and detect previously unknown relationships between processes, equipment, and performance rates.
“Manufacturing is at a critical juncture, and companies that don't adapt to ai risk being left behind,” Senoner said in a press release. “Factories are producing mountains of data and ai is the key to unlocking insights that drive operational excellence.”
