The Payoffs of a Facilities Predictive Maintenance Plan

Because they operate as small cities, infrastructure can comprise a large percentage of an industrial sites’ budget. When systems are installed, they are functioning at peak performance. Over time, however, performance naturally degrades.

As this happens, you have two choices:

1. Let performance slowly deteriorate until the system requires full replacement/restoration

2. Invest smaller amounts of money over time to maintain high-performance levels for as long as possible.

Pay now or pay later: You can spend pennies on the dollar today for preventive maintenance, or spend much, much more for a new system down the road.

How Facilities Predictive Maintenance Plans Work

  • Shive-Hattery assesses infrastructure conditions and potential problems on your industrial site
  • Your team is provided with a customized capital improvement plan
  • Ideas are presented about how (and where) to make room in your budget for maintenance
  • Shive-Hattery acts as an extension of your staff, following and regularly updating the capital improvement plan

A facilities predictive maintenance plan can help industrial sites make smart infrastructure investments at the right times to get as much operating life as possible out of each system. To develop a facilities predictive maintenance plan, the existing industrial infrastructure is  assessed, and a roadmap for each system is created to:

  • Pinpoint system deficiencies and shortcomings
  • Calculate projected system lifecycles
  • Propose improvements to lengthen system lifecycles
  • Prioritize repairs and improvements

Pay Now: Maintain the Infrastructure

  • Systems are maintained for efficiency and better-operating conditions
  • Downtime risk is lower
  • Problems are detected and addressed early on
  • System lifecycles are extended for as long as possible
  • Reduce expenditure by investing over time to sustain performance

Pay Later: Neglect the Infrastructure

  • Systems aren’t maintained or kept in prime operating condition
  • Processes become inefficient
  • Downtime risk is higher
  • Problems aren’t caught early (if caught at all)
  • System lifecycles are shorter
  • Large capital investments are necessary to replace or restore systems