Testing | 2 MINUTE READ

Testing: AI Vision Software for Improved Production Line Quality Control

Neurala’s newly launched VIA software said to enable manufacturers to boost throughput, quality and production speed with finite resources. 


Facebook Share Icon LinkedIn Share Icon Twitter Share Icon Share by EMail icon Print Icon

An integrated solution to help manufacturers improve quality inspection on the production line while scaling to meet product demands, branded the VIA (Vision Inspection Automation) software, has been launched by AI software company Neurala, Boston, Mass.  

Said Neurala co-founder and CEO Max Versace. “Historically, AI (artificial intelligence) has been too expensive or complex to deploy at scale in a manufacturing environment. As the world approaches a new normal, manufacturers are facing irregular patterns in consumer demands, and heightened pressures on machine utilization, production efficiencies and quality control – and they need to address all of this with fewer people on the factory floor. Vision AI will be key in enabling manufacturers to answer the call of demand, increasing productivity and maintaining their competitive advantage as requirements continue to shift. We’re proud to launch Neurala VIA to give customers the option to finally deploy vision AI without requiring massive amounts of data, expensive hardware or specialized AI expertise.”

The VIA software reportedly enables manufacturers who have not worked with AI before to train and use vision AI to identify defects in products or packaging on the production line. And, with the ability to run directly on existing hardware on the factory floor, VIA makes AI accessible to industrial automation users who prefer not to rely on internet access or connectivity to the cloud. As a result, manufacturers can keep their data on the factory site, without concerns about privacy or lag time that are typically associated with cloud deployments. VIA provides:

 ▪  ROI: With less data required and faster training, VIA automates quality inspection processes that were previously not viable – improving inspection rates, decreasing human intervention, and allowing smaller batches to be inspected.

 ▪  Optimization: Allows production facilities to avoid wasted resources by catching defects early.

 ▪  Flexibility: Ability to train and run multiple AI models, compatible with any GigE camera and mid-range industrial PC.

 ▪  Anomaly Recognition: Identifies any product that deviates from the “acceptable” images without having to collect images of defective parts.

Summed up Versace,“In today’s climate, there is a clear need for an integrated solution that allows manufacturers to quickly adapt to changing markets within the constraints of their environment. VIA will meet that need, while giving manufacturers a flexible solution that will allow them to continuously adapt – whether that’s introducing new products into production, or adapting to irregular patterns in consumer demand that will arise in the new normal.”

Related Topics


  • Industrial CT Scanning Speeds Mold Qualification

    Qualifying a mold often can take weeks and involve several costly and time-consuming steps.

  • How to Get Better MFI Results

    The MFI test is used widely among the various segments of the plastics industry. The difficulty is that any two labs can easily come up with different results, making it difficult to determine whether a material meets a desired MFI spec. Here are some reasons why such discrepancies occur and what can be done about them.

  • How to Buy Universal Testing Machines

    More processors today are buyingso-called ‘universal’ testers to measure tensile, flexural, compressive, and shear properties for materials evaluation, application development, and quality control. Advanced electronics have improved these instruments’ performance and ease of use—and even led to lower prices.