As factories and manufacturing facilities have become “smarter” through sensors, robotics and other connected technologies, this has created a potential treasure trove of data that can be mined for information on bottlenecks and other areas for improvement. Or maybe even just speeding up processes that would otherwise require significant manual work.
But much of this data that is generated is unstructured and not easy to tap into right off the bat. While big data analytics has long been a mainstay of industries such as finance and logistics, it has not fully penetrated the manufacturing sector. This has created an untapped gold mine of knowledge and more recently an emerging market for technologies designed to both capture and make sense of a vast array of production data.
Last month, UK-founded Oden Technologies, now headquartered in New York, raised one $28.5 million Series B round to stimulate development for the data analytics platform for manufacturers. Germany’s Daedalus raised $21 million to implement artificial intelligence in precision manufacturing factories. And Belgium-based Robovision secured $42 million to bring computer vision intelligence to industrial machinery.
Now is EthonAI’s series, like the Swiss startup was announced Thursday that it raised CHF 15 million ($16.5 million) in a Series A funding round led by Index Venturesfeaturing General Catalyst, Earlybird and Founderful.
EthonAI detects 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 Inspector The software can then detect surface defects in products during the manufacturing and assembly process. Apple recently acquired a company called DarwinAI that serves a similar purpose, automating the visual quality management process in component manufacturing.
More broadly, however, EthonAI can combine data from all of a company’s manufacturing facilities, from sensors to the line stopsand build a picture of where things are and aren’t working well — and even compare performance across multiple facilities to see where there might be room for improvement.
In its three-year history, EthonAI has amassed some pretty high-profile clients, including Siemens and chocolatier Lindt.
Research into EthonAI’s target markets reveals that semiconductor manufacturing is a particular area of focus, although the company has not disclosed specific customers in that area. However, low performance is a known concern in the chip field, where defects in silicon wafers may affect the number of actual usable chips after production. In particular, Apple reportedly reached an agreement last year with chipmaker TSMC that apparently had particularly low rates of return (only 55% at the time), with Apple closing a deal only pay for known good wafers — saving billions dollars in the process.
EthonAI, for its part, says it’s working with a “leading semiconductor producer” that uses its platform to merge multiple data sets to conduct analysis and identify previously unknown relationships between processes, equipment and yield rates.
“Manufacturing is at a critical juncture, and companies that fail to adapt with AI risk being left behind,” Senoner said in a press release. “Factories produce mountains of data, and AI is the key to unlocking that information to drive operational excellence.”
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