The Industrial Digital Connection Point: Maintenance

The primary driver behind the push for digitizing industry operations today is maintenance. This holds true whether the industry is manufacturing, oil and gas or even rail transportation.

As the initial flurry of explanations and expectations for the Industrial Internet of Things (IIoT) began to settle about two years ago, it became apparent that the initial proving ground for IIoT—and industrial digitalization in general—would be maintenance. For many years before, automation suppliers had been touting the need to move from scheduled or reactive maintenance processes to predictive/proactive process based on data gathered from the assets themselves. Then the surge in interest around IIoT at the corporate level provided the necessary backing to prove out the IIoT/digitalization concept—and maintenance appeared to be the most logical proving ground because of the localized nature of the deployment and the potential for a substantial return on investment year over year.

This trend around IIoT, digitalization and maintenance didn’t just occur in the discrete manufacturing industries, however. It's also playing out in the oil and gas sector. And just last week, I learned that the same trend is also occurring in the rail transportation industry.

At the rail industry’s massive InnoTrans event in Berlin last week, I attended presentations by two of the largest technology exhibitors at the event —GE and Siemens; both of which focused on the application of digital/IIoT technologies to maintenance.

Network Disruptions
During the GE press conference, GE Transportation President and CEO Jamie Miller said the biggest rail industry concern is the “disruption to networks. An hour of delay costs thousands of dollars—and dozens happen every day.” The major causes of these delays are broken rails, damaged wheels and faulty track geometry.

To address this, GE is focused on “enabling self-aware trains in a connected ecosystem by linking the engine, rail and rail yard,” Miller said. “A self-aware train can gather information about itself and the environment in which it operates” to recognize and report on potential problems before they cause delays. “We’re now driving results with this approach, it’s not just a whiteboard concept” any longer.

As evidence of the real world application of these concepts, GE announced its first-ever European digital pilot withDB (Deutsche Bahn) Cargo, Europe’s largest rail operator. Deutsche Bahn is using GE Transportation’s RailConnect 360 Asset Performance Management to access locomotive health status updates to increase efficiency and spot repair issues before failures occur. According to GE, this is the first step toward self-aware locomotives and digitalization of the entire rail operation value chain.

Though focused on the rail industry, the similarities with GE Digital’s Brilliant Manufacturing Software Suite are apparent in that both are designed to connect and track data from a variety of sources to provide visibility into assets and operations. Both also leverage GE’s Predix software.

GE Transportation has also partnered with Intel to create GoLINC— a mobile data center that provides processing, wireless communication, networking, video and data storage. Amsted Rail, a global rail component manufacturer, has integrated GoLinc with its IONX Edge monitoring system to create its Car Integrity Monitor service. Using sensors mounted on railcars, Amsted Rail receives real-time notifications about the condition of railcar components, such as broken wheels, hot bearings and handbrake application.

Miller noted that GoLINC is currently being used on 6,000 locomotives and has been used in 1,400 rail car modernization projects. She emphasized that a critical aspect of GoLINC is its ability to modernize legacy rail assets without requiring owners to invest in entirely new assets to benefit from digitalization.

Like RailConnect 360, GoLINC is also leverages GE’s Predix technology.

Monitoring and Analysis as a Service
Siemens approach to digitalization for the rail industry combines data science with domain expertise. In his presentation at InnoTrans 2016, Gerhard Kress, director of Siemens Mobility Data Services, highlighted Siemens’ Smart Monitoring and Smart Data Analysis—a service enabled by Siemens Digital Services business of which Kress’s Mobility Data Services Center in Munich is a part.

Siemens Digital Services reportedly combines all of Siemens remote analytics and maintenance services on a single technological base called Sinalytics. The company says it has consolidated these activities on Sinalytics to connect the technological components needed for data integration and analysis, connectivity and cybersecurity.

Using massive parallel processing for scalable data storage and in-database analytics, Kress said the Siemens Sinalytics platform used by the Mobility Data Services Center relies on more than 200 CPU cores to handle all the data, analysis and data quality validations. He noted that analytics are conducted in the Sinlaytics database because there’s “too much data collected to be moved elsewhere for processing. Rail vehicles send between one and four billion data points per year—far beyond the amount of data transmitted in typical IT analysis applications.”

The Mobility Data Services Center is comprised of a team of data scientists, physicists, transportation engineers, computer scientists and mathematicians who analyze the diagnostic data being collected from rail vehicles and rail line infrastructure components. They then develop algorithms and models using machine learning, data analytics, mathematical and physical methodologies to provide secure forecasts for the future behavior of vehicles and components.

According to Siemens, “secure”—in this case—means a probability of well over 90 percent that the forecast will be accurate.

“Collecting and analyzing this train data ensures there are no surprises for the operator or the passenger,” Kress said. “The value to the operating company is improved maintenance, root cause analysis of failure, reduction of preventative maintenance cost, and increase in availability. Imagine having your assets be 100 percent available.”

Kress maintains this level of availability is possible and pointed to one example Siemens has been running in the field using Siemens Digital Services for more than 50 months without missing a failure.

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