About This Webinar
Machine vision systems for industrial manufacturing are typically isolated solutions to perform defect detection on a specific machine at a specific stage of a process. Yet in times of AI and Industry 4.0, machine vision has the potential to deliver more value to manufacturers.
Today manufacturers operating on multiple sites need vision systems that can be easily rolled out across lines and factories. They want to speed up the deployment of machine vision with deep learning models. Manufacturers also want to take advantage of the data captured by their vision systems to continuously improve their processes and prevent quality issues, not just detect them. In short, they want smart vision for the smart factory.
Making smart vision for the smart factory a reality requires a new approach to designing and deploying vision systems. This approach creates a repeatable blueprint for facilitating vision hardware deployments and configurations. It generates normalized digital records of parts produced on different machines and lines to make image data comparable and it integrates process data to perform root cause analysis of quality issues.
Smart vision systems allow manufacturers to easily scale across machines, lines, and sites and get more value faster. These systems do this by training and deploying one deep learning model across multiple machines, lines, and factories, while generating advanced analytics for process optimizations that can be implemented across the whole organization.
Join Barrett as she discusses how smart vision is finally making machine vision scalable and delivering value beyond defect detection.
*** This presentation premiered during the
2023 Vision Spectra Conference. For more information on Photonics Media conferences, visit
events.photonics.com.
About the presenter
As comfortable on the factory floor as in the boardroom, Erin Barrett spent the last five years gaining a deeper understanding of the manufacturing mindset, forging relationships, and closing deals with global manufacturers that informed Eigen’s long-term product roadmap as CEO.
While working on the front lines, she focused on generating repeatable revenue and expanding Eigen’s product portfolio. As sales grew for Eigen’s application-specific machine vision solutions, Barrett realized there was potential to sell Eigen’s software as stand-alone tools, expanding the customer base and creating additional revenue opportunities. While Eigen was expanding its customer base and scaling with global manufacturers, Barrett knew the company could not conquer the manufacturing world on its own. She developed an extensive partnership and channel strategy which now sees Eigen working closely with companies like Intel and AWS as well as a growing list of integrator partners.
Barrett leverages her entrepreneurial DNA and first-hand experience building businesses as she guides the Eigen team toward achieving its vision, mission, goals, and objectives. She continues to oversee the sales and marketing functions and works closely with the broader team to introduce their advanced machine vision software suite to the market.