Food & beverage operations teams have needed a more productive and effective way to track inspections of storage tanks, manufacturing lines, visual QA processes and packaging operations. Today, reliability and maintenance teams waste valuable time organizing and searching through unaggregated and difficult-to parse visual sensor data located across multiple users and systems. These inspections are often limited and reactive, with results that identify costly repairs that are often caught too late.
In this guide, see how Kespry Perception Analytics can enrich visual sensor data to better improve the knowledge graph by creating a geotagged, historical repository for visual data that
leverages machine learning to detect issues. This enables teams to easily analyze multiple sources of data across assets, track trends over time, and be proactive on repairs when issues start to arise, minimizing downtime.