Predictive maintenance in manufacturing

Challenge: A manufacturing company was spending in average 25% of their time in corrective maintenance. Today, this manufacturer sees maintenance as a strategic business function as opposed to a necessary evil. The challenge was:

  • Reducing both maintenance costs and downtimes
  • Optimising maintenance time windows and spare parts ordering
  • Increasing asset lifecycles.

Solution: SuperGraph Predictive Maintenance solution looked at the history of machine failures and compared with real-time machine sensor data to spot patterns and early warning signals before the breakdowns.

The solution provided:

  • Elimination of unnecessary maintenance tasks
  • Reduction in component replacement costs
  • Reductions in unplanned downtime
  • Reduction in breakdowns
  • Extension of asset lifecycles
  • Global optimised maintenance schedules including parts ordering.

Benefits: The number of breakdowns reduced with up to 70%, the downtime reduction was almost 30% with significant production increase. In addition, the cost of maintenance and parts was reduced due to optimised scheduling of efforts required.