Connecting operational technology (OT) and information technology (IT) has long been a goal for manufacturers to drive greater insights across their operations. Today, at the International Manufacturing Technology Show, Google Cloud is announcing an update to our Manufacturing Data Engine (MDE) to help bridge this divide and deliver greater productivity, innovation, and profitability to the industry.
We have now established initial technical foundation extensions for the Manufacturing Data Engine, Google Cloud’s signature manufacturing solution, to integrate with Cortex Framework, a packaged solution of reference architectures, deployment accelerators, and integrated services designed to speed up cloud deployments. Connecting IT data from Cortex Framework to OT data in MDE will provide manufacturers a holistic view of their factory and business operations that’s built on AI-enabled analytics and insights. This release will provide an initial set of features for MDE to support technical interoperability required for broader IT and OT use cases.
Historically, manufacturers have faced a disconnect between their physical machines (OT) and the data they generate (IT). This separation has led to siloed teams and inefficiencies. Bringing the two together provides the opportunity to apply analytical and AI tools to industrial data, which can help unlock new levels of automation and valuable insights for enterprises.
Connecting OT and IT data faster
Today, MDE is Google Cloud’s cornerstone solution for acquiring, processing and analyzing factory OT data. Cortex Framework helps customers accelerate business insights into their enterprise IT data, enabling better business outcomes, with less risk, complexity, and cost. With MDE joining the Cortex Framework solutions portfolio, manufacturers have access to a powerful combination of solutions to connect and harness the full potential of IT and OT information on a consolidated Google Cloud data and AI platform.
This powerful combination enables manufacturers to drive a more comprehensive view of their factory operations, uncover hidden insights, and drive intelligent decision-making by more easily collecting and processing multimodal data from machines, sensors, and cameras using MDE and then contextualizing it with data from core enterprise applications like SAP, Oracle, and Salesforce — as well as other external datasets via Cortex Framework.
Manufacturers can now achieve a holistic view of their entire operations, perform data visualization and analysis, and more effectively leverage AI on and off the factory floor.
This combined offering builds on successes like those achieved at companies like Tyson Foods, where MDE is already processing and contextualizing factory OT data. With Cortex Framework, manufacturers are enabled with access to additional IT data.
Accelerating operational excellence
With OT and IT data consolidated on Google Cloud, manufacturers also have the opportunity to accelerate operational excellence with smarter data- and AI-driven insights. By building on MDE and Cortex Framework — in combination with supporting services like BigQuery ML, Vertex AI, Gemini, and Timeseries Insights API — customers can tackle pressing industry challenges such as:
Linking the enterprise to factory floor insights: Contextualize shop floor data with enterprise data sources (e.g. production, supply chain, customer service, marketing) with MDE and Cortex Framework to identify new insights whether from marketing, sales, distribution, production, finance, or more.
Gaining end-to-end process insights: Connect sales orders to production orders, and then to overall equipment effectiveness and purchase orders, and get a holistic view of end-to-end processes.
Driving accurate and timely overall equipment effectiveness analytics: Monitor and optimize equipment and plant performance, availability, and quality at scale with actionable insights to drive production improvements and meet business requirements.
Operating more sustainably: Analyze telemetry data for utility consumption and waste to reduce costs and meet environment, social, and governance (ESG) goals. Combine transaction data from ERP with ESG data from partners like Dun & Bradstreet to elevate vendor performance management processes to new levels.
Innovating with AI on top
Faster root cause analysis with machine-level anomaly detection: Analyze telemetry data streams with self-training anomaly-detection machine-learning models to quickly understand where anomalous data was created by specific machines and/or processes providing a critical head start on root-cause analysis for faster corrective action.
Proactive and automated maintenance activity: Inform plant maintenance processes on transactional maintenance systems with AI-generated predictions for machine service needs via integrated telemetry and sensor data – helping to reduce downtime and maintenance costs.
Flexible and scalable visual quality control: Train and continuously improve vision AI models on Google Cloud, deploying them on the edge and ingesting the data back to the cloud for scalable and flexible analysis of quality assurance trends and easy access to details of specific defects and component quality.
By harnessing the power of data and AI, manufacturers can unlock new levels of agility, resilience, and competitiveness.
Come visit our Google Cloud at booth #236709 at IMTS to learn more.
