Google Cloud Furthers Visibility Efforts in Manufacturing

Google Cloud is one of many large companies looking further into supply chains and visibility with two new solutions, Manufacturing Data Engine and Manufacturing Connect. Visibility is a key trend in software for supply chains and manufacturing, and with Google's investment, could become much more sophisticated. The new products are aimed at merging areas that have been traditionally siloed in the past to create real-time factory floor visibility. 

Per PR Newswire: 

• Manufacturers are undertaking a massive digital transformation driven by rising customer expectations, supply chain volatility, shifting buyer behavior, and more. Yet, only 21% of manufacturers have active AI initiatives in production to help solve these issues. While data from disparate systems can be manually prepared for AI and analytics pilots, siloed data sets still need to be accessible centrally and in real-time to support production scale. Additionally, many existing AI and analytics solutions are designed to be used by data scientists and are not easy to use for manufacturing business leaders.
• Manufacturing Data Engine is an end-to-end solution that processes, contextualizes, and stores factory data on Google Cloud's market-leading data platform. It provides a configurable and customizable blueprint for the ingestion, transformation, storage, and access to factory data. It integrates key Google Cloud products, including Cloud Dataflow, PubSub, BigQuery, Cloud Storage, Looker, Vertex AI, Apigee, and more, into a manufacturing-specific solution.
• Manufacturing Connect is a factory edge platform co-developed with Litmus Automation that quickly connects to, and streams data from, nearly any manufacturing asset and industrial system to Google Cloud, based on an extensive library of more than 250 machine protocols. Deep integration with the Manufacturing Data Engine unlocks rapid data intake into Google Cloud for processing machine and sensor data. The ability to deploy containerized applications and ML models to the edge enables new dimensions of use cases.