Industrial operations are often located in harsh environments. And for many companies, connecting to remote assets and securely transferring operational data remains a significant challenge. Typical solutions merely aggregate and filter data prior to sending to the cloud. Predix Platform offers a unique approach. Comprised of two software stacks, one for edge and one for cloud, they work together as one—enabling data ingestion, analysis, intelligence gathering, and control at the place where it's needed.
Benefits of edge-to-cloud technology
Unreliable connectivity, lack of near real-time control, the high cost of moving large volumes of data, managing thousands of devices, and meeting industry regulations are challenges that Predix Platform addresses. Predix Edge technology provides the necessary capabilities to connect to an asset, perform analysis, securely transfer data to Predix Cloud, and manage the lifecycle of devices. Predix Cloud provides hyper-scale elasticity, mission-critical availability, and security support for data at rest and in motion.
Right placing intelligence
Predix Machine powers Predix Edge technology's ability to run workloads in close proximity to assets and data. Typically embedded as a software-stack within an intelligent device, Predix Machine can run on a wide variety of hardware-ranging from sensors, controllers, gateways, to edge servers-supporting a tiered set of features. It also provides security, certificate management, authentication, and governance services.
Connect to GE and non-GE assets
A Predix Machine-enabled device bi-directionally connects to industrial assets to collect data and send control events/signals. It supports OPC-UA, Modbus, and MQTT and can be extended to support proprietary protocols. Predix Machine also supports connections to historians, and offers a Kepware option for additional connectivity. Direct-to-storage ingestion options are supported in the Predix Cloud for historian, time-series, and Blob data.
Process data at the edge
Predix Machine incorporates a complex event processing (CEP) and machine learning engine. Analytics can be authored in the cloud then deployed and run at the edge. When applied to data at the edge, operational analytics ensure the efficient operation of assets by detecting and acting upon anomalies. Those analytics can be improved over time based on historical analysis in the cloud to direct prescriptive controls and signal predictive maintenance alerts.
Manage edge devices
Predix Edge Manager offers operators a unified view to manage the entire lifecycle of hundreds of thousands of Predix machine enabled devices. Predix Edge Manager enables tasks such as enrollment, provisioning, monitoring, configuration, update, and deployment of applications and analytics across the entire device fleet. Operators can schedule tasks to be performed on a single or a group of devices and execute custom commands.
Purpose-built for industry
Predix cloud provides hyper-scale elasticity, mission-critical availability, and security support for data at rest and in motion. It can handle vast amounts of industrial Internet information, while also managing customer SLAs, security, support, governance, compliance, and export controls.
Predix Connectivity offers seamless, secure, and reliable end-to-end communication between Predix Edge devices and Predix Cloud over various access networks, including fixed line, cellular, and satellite communication. This allows customers to securely connect existing infrastructure-and new deployments-to the cloud for data ingestion, running analytics, remote device monitoring, and management.
Predix Platform's asset model is a critical platform component that drives differentiation. The model describes the structure of subsystems, subassemblies, and components of a unique asset. Thus, the asset model provides a unified construct to turn asset data into intelligence, which can be utilized across multiple systems and applications. The asset model can be extended and reused through digital twin technology, providing a single source of truth about the asset.
Asset-centric digital twins
Better understand, predict, and optimize the performance of your assets through software representations.LEARN MORE
Build, test, and run industrial IoT solutions via high-control and high-productivity development paths.LEARN MORE
Analytics and machine learning
Develop machine learning analytics with a rich set of industrial grade analytic libraries and framework.LEARN MORE
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