SOMERVILLE, MA - December 14, 2022
Today, Tulip announced the launch of Computer Vision for Quality Insights solution on Amazon Web Services (AWS) which is available via the AWS Solutions Library, a resource for vetted solutions and guidance for business and technical use cases.
Manual inspection is both time-consuming and mentally intensive for operators – resulting in inspection bottlenecks and risks. Quality sampling practices are not acceptable for manufacturers with zero-error goals. Setting up and maintaining traditional machine vision inspection stations is expensive and impractical for high-mix manufacturing environments.
“This new offering allows manufacturers to leverage automated image analysis integrated with production tracking to better manage the entire process life cycle and better achieve zero defects at scale,” said Roey Mechrez, Head of Artificial Intelligence at Tulip. “This democratized approach allows manufacturers to deploy powerful technology without proprietary cameras or complicated vision configurations”.
To set this up, manufacturers need as few as 10 images with passing and failing visual inspections to train an anomaly detection model. Once trained, the model is ready for manufacturers to deploy it to the edge and detect anomalies. As part of a guided assembly workflow, operators need only to put the parts under a camera to check for defects before moving on. In addition to notifying the operator, Tulip can be configured to automatically log the defect with other product tracking information - accelerating root cause analysis.
Tulip customer Laerdal Medical leverages computer vision to drive efficiency in its operations by empowering its manufacturing engineers to build powerful apps using no-code computer vision. “Rather than using expensive proprietary cameras, rigid configurations and professional services, we set up and configured Tulip Vision on our own in hours and with off-the-shelf cameras,” said John Leahy, Engineering Project Manager, Leardal Medical.
“Flexibility, scale, and speed are some of the core reasons manufacturers look to the cloud,” said Grant Bodley, general manager, Industrials & Manufacturing at AWS. “We’re continuing to offer manufacturing customers step-change improvements rather than incremental ones. This solution underscores the efficiency of automated image analysis and highlights the opportunity to improve quality through machine learning.”
Additional vision capabilities available with Tulip can also act as an extra set of eyes to double-check work, automate steps, and capture data for guidance, compliance, and material tracking – freeing up frontline operators to focus on the most important aspects of their work. Tulip’s solution makes no-code computer vision a reality for frontline operations with many new features set to be released over the next few months.
Tulip, the leader in frontline operations is helping companies of all sizes and across industries, including complex manufacturing, pharmaceuticals, and medical devices equip their workforce with connected apps– leading to higher quality work, improved efficiency, and end-to-end traceability across operations. A spinoff out of MIT, the company is headquartered in Somerville, MA, with offices in Germany, and Hungary.
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