The Future of Railway Maintenance with IIoT System Analytics

As rail systems become more complex, developing technology suites that allow for reliable predictive maintenance is more challenging than ever. Schedule-driven maintenance practices can result in expensive and unnecessary inspections early in a system’s life and are insufficient as the system ages and deteriorates.

Developing the technology suites that help passenger and freight rail companies keep the trains running on-time and the tracks in top working condition is what motivates our team in striving to connect the physical and digital worlds.

PARC’s MOXI™ IIoT System Analytics Solution

Through this work, a team of PARC engineers and researchers have developed  solution. When integrated with complex systems, MOXI reliably senses, models, detects, diagnoses, and recommends improvements and service actions to ensure upkeep of rail fleets and equipment.

By tapping into the Industrial Internet of Things (IIoT), the possibilities have never been greater as we embed physical objects with technology that allows cars and undercarriage assemblies and components, as well as control systems and equipment, to be monitored over the industrial internet, making rail transport companies smarter about maintenance, repair, planning, and overall system efficiency.

Because these customizable suites of technologies include visual representations of the conditions of the objects or systems they’re monitoring, it’s easier than ever for management and maintenance professionals alike to proactively see, in real time, what needs to be done, and when to keep their system running smoothly and without drag.

By developing the right model in coordination with maintenance, engineering and operations staff, the technology gives rail transport companies the ability to measure, store and act upon an increasing number of data sets that enhance passenger safety while reducing operating expenses.

To maximize the effectiveness of MOXI on a rail system, PARC’s team of engineers and researchers will work collaboratively with maintenance and operations staff on-site to customize sensors, models and UIs for complex systems. The modest investment in time and expertise more than pays off with high-accuracy analytics that on-the-ground teams can count on to proactively maintain and improve their systems upkeep.  The feedback from maintenance professionals and their supervisors has been overwhelmingly positive. It’s like making the switch from analog to digital, or from manual to automatic.

about our approach, and get details about our successful implementation with East Japan Railway.