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CORRECTIVE MAINTENANCE

Corrective maintenance is defined as maintenance which is carried out after failure detection and is aimed at restoring an asset to a condition in which it can perform its intended function.

The steps in the corrective maintenance process are, following failure, diagnosis (elimination of the part causing the failure), ordering the replacement part, testing of function and finally the continuation of use.

Advantages of Corrective Maintenance are:

  • Lower short term costs
  • Minimal planning required
  • Simpler process

Disadvantages of Corrective Maintenance are:

  • Unpredictability
  • Paused operations
  • Equipment not maximized
  • Higher long-term costs

The best industry 4.0 solution to counter these disadvantages is Predictive Maintenance.

PREDICTIVE MAINTENANCE

For optimal performance, all factory machinery needs to be maintained and companies often have maintenance agreements in place, usually with the original machine manufacturers or their approved service network. Whilst useful, these agreements are largely service-interval schedules, which don’t take into account actual usage and do little to prevent unplanned downtime. This is the widely-used preventative and reactive maintenance model.

Predictive maintenance is more proactive, analysing the huge volumes of available machinery data to give you a better understanding of the ongoing health of your machines and pre-empt failure. This maintenance approach opens up opportunistic possibilities in machinery management, allowing you to adapt and enhance your existing maintenance arrangements. By analysing data to predict when machinery will break down, companies can remove surprise failures and reduce downtime, scheduled maintenance and the routine replacement of parts that may in-fact be perfectly healthy.

READ ABOUT PREDICTIVE MAINTENANCE

Download the “Harness The Power of Prediction: Maximize ROI With The Right Condition Monitoring Solution” Whitepaper to learn:

  • The obstacles manufacturers need to overcome
  • How the arrival of smart technologies has helped tackle some of these challenges
  • The potential impact predictive maintenance can have on ROI

Enter your information below to download now!

WATCH HOW PREDICTIVE MAINTENANCE WORKS

TRUSTED BY

SKF, Siemens, GE, Schneider Electric, Nissan, Tata Steel, Smufit Kappa and many more…

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THE RESULTS

  • 85% improvement in downtime forecasting accuracy
  • 50% reduction in unplanned machine downtime
  • 55% increase in maintenance staff productivity
  • 40% reduction in maintenance costs

Read about Predictive Maintenance

Download the “Harness The Power of Prediction: Maximize ROI With The Right Condition Monitoring Solution” Whitepaper

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