Third-Party Predictive Maintenance via Edge Computing

Modernization projects and advancements in asset-management technology are making inroads into traditional industries, such as oil and gas.

When the mainstream media catches on to an industrial manufacturing or processing trend, it’s a special day. Sarcasm aside, the Wall Street Journal recently profiled Schneider Electric’s third-party predictive maintenance services via edge computing in remote oil fields. The oil/gas industry has been rebounding from low crude prices since 2014 and exploration and production (E&P) companies have been focusing on operational efficiencies since then — though the energy prices are now changing.

Edge computing — a good explainer on edge’s importance — is done at the device, such as a mechanical pump or valve, and companies are turning to service providers to reduce the amount of data going back to a centralized, supervisory control and data acquisition (SCADA) platform or enterprise application. The trend uses programmable logic controllers (PLC) to do the heavy lifting in the field, via increased processing power, as opposed to SCADA systems continuously polling devices in remote areas, where wireless can be spotty.

The WSJ article discusses Schneider Electric’s predictive maintenance service approach and interest in edge computing:

Schneider Electric in 2017 began experimenting with Microsoft Corp.’s Azure IoT Edge, which connects devices in the field to gateways and is an extension of its public cloud. A gateway, used in many edge computing scenarios, is a piece of hardware located physically near an object, which aggregates information from sensors, analyzes it with software, and pushes insights and data to a corporate cloud, when necessary.

Other automation vendors are advancing the third-party, remote servicing trend, such as Emerson, GE, Opto 22, Moxa, Honeywell and many others. The article cites that by 2021, according to Gartner, that 40% of enterprises will have an edge computing strategy in place, up from about 1% in 2017. That seems a bit fast, considering the slow uptake of IIoT strategies in 2015 and 2016.

Efficient Plant’s Take

Whether it’s energy, food/beverage, or traditional utilities, companies are recognizing predictive maintenance solutions are accessible and also realizing capital expenditures are lower due to the ability to use existing hardware/equipment on the plant floor. The key component is the advanced networking solutions, such as OPC UA and MQTT, that link the legacy equipment.