Predictive Maintenance in the Public Sector

New sources of information about machine conditions from the Internet of Things (IoT) give government agencies the opportunity to take a more proactive approach to maintenance.

IoT sources can collect and exchange public sector data across a broad array of capital projects, including roads, bridges, transit and mobility systems, airports, and ports spanning many different kinds of agencies.

Benefits of Predictive Maintenance in the Public Sector

When the U.S. Department of Energy released its study, “Operations & Maintenance Best Practices - A Guide to Achieving Operational Efficiency," the agency concluded that an effective predictive maintenance program is 8 to 12 percent more cost-effective than a program that relies solely on preventative maintenance, and can deliver potential value and savings as follows:

  • 10% return on investment
  • 20% - 25% increase in production
  • 35% - 45% reduction in downtime
  • 20% - 30% reduction in maintenance cost
  • 70% - 75% elimination in breakdowns

Predictive Maintenance in the Public Sector: Is IoT Enough?

When a part sensor generates data to tell us a particular part on an airplane is wearing and will need to be replaced, is that all we need to know?

The reality is that we need more information. Government entities need to address the maintenance of the aircraft in the most efficient and optimal manner in order to minimize impact on mission readiness. This requires more data that goes deeper!

Other information we need to know includes:

  • Where is the airplane headed?
  • What is the replacement part?
  • Who is best equipped within that region to perform the repair?
  • How quickly and at which location can we bring these assets together?