Fact – since the earliest deployments of cameras in factories, machine vision solutions for manufacturing have been difficult to scale and manage.
Just as variations in manufacturing processes can lead to quality issues, variability among machines producing parts has made scaling machine vision a challenge. Systems were and continue to be designed on a machine-by-machine basis to account for unique conditions in and around each machine. Inconsistency in these solution designs means inconsistency in the data (images) they generate making the raw data challenging to analyze and readily use. While some vision software products help with data usability, they do not consolidate and standardize data which is often a requirement for machine learning applications.
Our Senior Director of Product & Innovation, Josh Pickard recently attended the EVMA’s 6th European Machine Vision Forum in the Netherlands and talked about how Eigen’s outcome-driven solution design approach helps manufacturers to overcome variability and make scaleable and centrally managed machine vision solutions a reality.
Check out Josh’s presentation here.