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Uninterrupted Operations Through Responsive Maintenance

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The reliability of Panasonic’s rugged mobility devices enables real-time data and preemptive troubleshooting in the field. This article describes how manufacturers can use sensors, data, and analytics for predictive maintenance.

When large-scale manufacturers take a reactive approach to maintenance—only servicing equipment after a breakdown—it leads to increased operational costs and raised cost of lost opportunity. By leveraging big data analytics from their equipment and using global management dashboards, manufacturers will be able to not only respond to emerging situations, but eventually lead repairs that occur before systems malfunction.

Scenario: On The Field: Remote Synchronous Field Maintenance

Rob, the maintenance manager for a large-scale commercial elevator vendor, oversees service and operations over a densely populated metropolitan area. The elevators in his network are equipped with internet-enabled sensors, allowing them to transfer specific service data and analytics to Rob’s dashboard at headquarters. With remote access to the elevators’ KPIs, maintenance history, service needs and other aggregate data analyses, Rob can efficiently deploy his team to ensure continuous and safe operations.

  1. Rob’s KPI dashboard informs him that several elevators across the city are due for maintenance. One elevator alerts Rob that it is experiencing unusual amounts of noise during normal operations.
  2. The elevator dashboard assigns a field worker, Nico, to perform a service check on the elevator based on his appropriate skill level, equipment and current location. This not only conserves fuel efficiency out on the field, but ensures a quick, frictionless maintenance experience—effectively reducing costly downtime.
  3. When Nico arrives, he connects with Rob via a pair of voice-enabled smart glasses. Working in tandem, the two determine the problem is with the elevator’s thrust bearings.
  4. Rob can see that Nico doesn’t have an inductive absorber on his truck, which is required to fix the issue, but that another technician who is in the area has the part on hand. Kassidy receives an alert and is immediately dispatched to Nico’s location. 
  5. Both Rob and Nico can view her progress in real time on a map. Nico is able to begin the initial repair work in anticipation of her arrival using the AR function on his glasses to guide him through the necessary steps.
  6. After installing the new inductive absorber, the elevator recommends that Nico secure the elevator grounding to prevent any additional electrical noise that may contribute to improper elevator diagnoses.
  7. Back at HQ, Rob is alerted to another elevator that has signaled it is due for maintenance based on a repeated pattern of service behavior.
  8. Seeing that this particular elevator has had a history of overvoltage, Rob conducts a remote power quality survey to view a visual thermography of the elevator’s current heat expenditure. According to this survey, the elevator is experiencing rising temperature in its motor as a result of a vulnerable fuse. Rob sends a service notification to Paul, who is servicing a nearby elevator.
  9. With the diagnostic knowledge in hand, Paul is able to quickly replace the fuse before it leads to a tripped circuit.

Highlighting The Opportunity

“The ability to predict failures and be able to offer an initial level of service, and at the same time, being able to think about how to build a better experience in the future.”

Colin Masson. Director of Manufacturing Industry Solutions, Microsoft Cloud & Enterprise

“This ability to see what’s happening in real time, storing the data, and then analyzing that data gives manufacturers an opportunity to predict potential outcomes. With this kind of information, they can then put in safeguards and plan more effectively for problem resolutions.”

Bill Moffett. Global Industry Senior Product Marketing Manager, Microsoft

“Maintenance profits, through optimized spare parts inventories and dynamic prioritization, may result in gains of 10-20%.”

Digital Factories: The Renaissance of the US Automotive Industry. Fraunhofer Institute for Manufacturing Engineering and Automation (IPA), Roland Berge, 2016.

What Trends Are Driving This:

  • Predictive Analytics
  • Preemptive Troubleshooting
  • Responsive Optimization
  • Onboard Collaboration

 

This article was written by Travel Editor and Emily Wasik from PSFK and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to legal@newscred.com.

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