Medical device assembly tends to be more error prone [1] than other discrete manufacturing sectors such as consumer electronics and home appliances, due to smaller lot sizes. First time yields remain between 60 to 85%, and manual-assembly related quality issues (human errors) are a major contributor to these poor yields. Emergency manufacturing requirements, such as recent needs to scale ventilator manufacturing for COVID-19 patients, cause yield and quality to be significantly worse.
Overall, the opportunity to improve quality costs for the medical devices industry is $4.75-$6B a year. In fact, costs of a single non-routine quality event, like a major recall, have been as high as $600M in medical device companies.
These stricter quality requirement imply an increased need to mistake-proof manual assembly processes in medical devices manufacturing. Our RetroActivity platform assists these manufacturers in three ways:
Due to regulations and ISO certification requirements, operators are often required to precisely follow a standard sequence of steps, and avoid batch assembly. Pathfinder, both with and without its projector integration has been deployed to encourage such compliance, and led to near 100% compliant results.
Pathfinder has been deployed on assembly of very small medical devices that can be sent inside the human body or transplanted into it. In these settings, Pathfinder is used with highly magnifying cameras including with microscopes, while the operator performs assembly also aided by magnifying glasses. We have also provided integrations with highly specialized instruments to achieve validation of certain steps. In a certain deployment where scrap rate was 30% and per unit cost in 1000s of dollars, customers were able to bring down scrap rate to under 5%.
Pathfinder has also been used when liquids and chemicals are involved in the assembly process. We are able to provide guidance on how to make computer vision validation work when transparent glassware is utilized in the assembly process; and help deploy digital Poka Yoke systems for these use cases as well.
It is critical to include all required components when kitting medical products e.g. Tourniquets, Shunt Kits, Stents, Perfusion Cannulas, and Catheters. In many cases, these kits are opened in emergency situations, and the medical practitioner cannot afford to have parts missing from the kits. Returns in these situations are not only bad for the bottom line in the short term, but the reputational costs of missing parts in Kits can be catastrophic. Pathfinder has been deployed in several medical Kit Packing use cases with success.
Huy takes our product roadmap and figures out what’s achievable with today’s AI advances, and what we need to invent to solve our customers’ pain points.
Huy led teams of scientists and engineers at NEC and invented technologies for driver assistance systems that are part of 500,000+ Honda cars. He is an inventor on more than 20 US patents, and his research papers are cited by every lab from MIT, Stanford, and CMU to Apple, Google, and Baidu.
Michael works closely with our marquis customers to understand their needs, and figures out the best solution that immediately adds dollars to their bottom line.
Michael has almost 20 years of enterprise sales experience. He has held sales leadership roles at pioneering AI and computer vision startups.
Andrey takes inventions and converts them into innovations. He leads our product engineering team to turn our scientific prototypes into robust customer-facing products.
Andrey co-founded and successfully exited a startup to immigrate to the US. He spent his next eight years building the core data science infrastructure for Amazon’s supply chain planning team, and the CV/ML infrastructure for Microsoft’s HoloLens organization.
Zeeshan focuses on delighting our customers by understanding their needs and defining product and strategy to meet and exceed these needs. He works closely with our sales leadership to grow our customer base.
Zeeshan was a scientific leader at Microsoft’s HoloLens division, where he invented AI technologies to assist frontline workers across industries. Earlier, he shipped IoT platforms and visual defect detection software for manufacturers at Siemens and MVTec GmbH.
