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Well-designed database structures and traceability mechanisms are essential for reliable, scalable manufacturing and test systems built in LabVIEW. This session covers two complementary aspects of SQL database design in the context of LabVIEW applications: table architectures for organizing data efficiently and supporting long-term scalability, and line traceability for tracking products, components, and process data across a production line. Attendees will gain a practical understanding of how thoughtful schema design and traceability implementation, integrated with LabVIEW, work together to ensure data integrity and process visibility.
Hi, I am one of the LabVIEW developers working at the ARAV Systems.
Atharva Yeole is an Application Engineer at ARAV Systems with over 3 years of technical experience in test automation and engineering software development. He specializes in Hardware-in-the-Loop (HIL) systems and Automated Test Equipment (ATE), building robust, scalable test solutions using LabVIEW and LabVIEW Object-Oriented Programming (LVOOP). Atharva is well-versed in National Instruments (NI) tools and brings strong expertise in Git version control and Jenkins-based CI/CD pipelines to streamline development and deployment workflows. Passionate about bridging hardware and software engineering, he is excited to share his insights and experience at the GLA Summit.
