GE Digital Unveils Industrial Software Solutions to Help Accelerate Digital Transformation

At its Minds + Machines conference, GE unveiled expansions to its suite of edge-to-cloud technologies and industrial applications, designed to help its customers further build an asset strategy. These additions to the GE Digital portfolio complement software applications that help to drive industrial productivity and extend these capabilities through its Predix application development platform for the Industrial Internet.

To help industrial companies get the most out of their industrial assets and drive better business outcomes, GE Digital introduced:

• New Predix Edge technologies to help accelerate computing at the edge;

• Predix platform combined with the Microsoft Azure cloud for enterprises;

• New Operations Performance Management (OPM) software to help bridge productivity from assets to operations;

• Enhanced Field Service Management solutions to help to improve its customer’s experience;

• Advanced App and Digital Twin Solutions, new platform tools to help simplify industrial app development.

   

New Predix Edge technologies

To help customers accelerate their edge strategies and add intelligence to assets, GE Digital is expanding its Predix Edge capabilities to help run analytics as close to the source of data as possible. Predix Edge gives customers with limited connectivity, latency limitations, regulatory or other constraints a way to deploy applications closer to the originating data – or at the edge. Enhancements include:

• Predix Edge Manager allows customers to support large fleets of edge devices – up to 200,000 connected devices from a single console.

• Predix Machine enables microservice-based applications to run at the edge on customers’ virtualized data center infrastructure or on server-class hardware from GE or its partners. This also supports Predix Edge Manager, which was previously available only as a cloud service.

• Predix complex event processing (CEP) allows for faster and more efficient analytics and other event processing at extreme low latency, available at the edge in Q1 2018.

   

These edge solutions can help companies move from intelligent asset management to automation to insights-led machine learning across a distributed system. One example is EdgeLINC, a comprehensive edge-to-cloud solution from GE Transportation integrated with Predix Edge Manager, Predix Machine and Asset Performance Management applications. EdgeLINC enables more efficient device management, configuration and streaming analytics when machines, such as rail assets, are constantly moving in and out of communication.

Predix Platform on Microsoft Azure

GE Digital and Microsoft are bringing together the industrial platform services of Predix with the enterprise-proven services of Microsoft Azure. Available in North America starting Q4 2017 and expanding globally in 2018, this partnership extends the accessibility of Predix to Microsoft’s global cloud footprint, including data sovereignty, hybrid capabilities and developer and data services, enabling customers to better capture intelligence from their industrial assets.

The partnership helps businesses to better connect their information technology (IT) systems with their operational technology (OT) by bringing a company’s systems and data together in a shared environment. While IT and OT have often existed in silos, Microsoft and GE are helping to bridge this gap and giving industrial customers a way to more easily help to improve performance, increase operational efficiency and accelerate the shift from automation to intelligence.

New Operations Performance Management (OPM) solution

Understanding how an asset operates and its maintenance needs is critical to help mitigating risk and improving productivity. Alongside its Asset Performance Management (APM) software, its core application deriving value from industrial assets, GE Digital introduced a complementary application that helps to improve the operational performance of assets, such as pumps, valves and heat exchangers, and helps to drive an asset management strategy.

This new Operations Performance Management (OPM) solution is designed to help industrial companies to increase revenue and margins, better optimize the throughput of industrial processes and help to make their sites more profitable. OPM uses real-time and historical data, along with advanced analytics, to help customers make better operational decisions. The solution provides an early warning if industrial processes deviate from plan, arms operators with the information and time to troubleshoot operational issues and helps them take preventative actions to better meet business goals.

GE Digital’s OPM software initially targets the mining industry and will expand to additional industries early next year. The OPM solution has already helped customers achieve improvements to revenue and profit including:

• platinum operator increased overall throughput by 10 percent, more consistently reaching maximum design capacity and increasing recovery by 1.5 percent.

• A large mining company achieved a 5.5 percent increase in throughput while consuming 2 percent less power.

A gold producer realized a 1.5 percent increase in recovery while reducing equipment-related costs through improved process efficiency.

Enhanced Field Service Management Solutions

With service technicians looking to embrace technology to improve their productivity and deliver a better experience for customers, ServiceMax from GE Digital’s field service management (FSM) solution announced several enhancements to its FSM suite, helping to enable greater efficiencies and bringing more advanced analytics to service operations.

Artificial intelligence-enabled predictive service times now integrate the Apache Spark AI engine to help improve service time estimates. Additionally, a new application integration solution enables service providers to launch and share FSM data with third-party mobile applications installed on the same device. New capabilities in schedule optimization allow for dependent job scheduling between work orders for multiple visits aimed at helping to improve first-time fix rates. As part of GE Digital’s FSM portfolio, these new features allow operators to further minimize downtime, optimize costs, reduce risk and improve productivity for services teams.

Advanced App and Digital Twin Solutions

GE Digital also introduced Predix Studio to help companies build and scale their own industrial applications and extend their Asset Performance Management (APM) suites. Available in Q1 2018, Predix Studio helps to simplifly the development process by giving customers the ability to extend applications and further empower individuals to build apps in a lower-code, higher-productivity environment. These individuals are often comprised of controls and reliability engineers, OT operators and line of business users with domain expertise but little or no coding experience. Using a mix of AI and machine learning, Predix Studio helps to automate the process of creating Industrial IoT apps, which can open app development to individuals without coding experience.

To help customers better capitalize on growth opportunities, GE created the Digital Twin Analytics Workbench, a solution that applies a library of algorithms and templates to help make it faster and easier for companies to build their own digital twins on Predix. GE’s experience in managing industrial assets has generated hundreds of millions of hours of machine data and a deep understanding of how machines perform in various conditions. Modeling that physical data into digital twin models allows GE to deliver applications that help better predict and improve the performance of physical machines.

The Analytics Workbench, currently a technology preview from GE Power, can be used to help augment existing digital twins with new data streams. For example, power producers using drones to inspect wind turbine blades, pipelines or fuel reserves can integrate visual inspection data into the digital twins they already use to manage generation assets and grid infrastructure. The Analytics Workbench also helps users implement machine learning capabilities that allow those models to further improve themselves over time.