Condition Based Maintenance (CBM)

What needs to be considered in order to successfully carry out predictive maintenance?

When deciding whether to implement a condition-based maintenance tool (CBM) or a predictive tool (PrM), important decisions have to be made in advance. Ultrasound or vibration? Infrared or oil analysis) Motor current testing or precision alignment?

A good CBM program starts with a detailed assessment of the equipment in terms of probability and severity. Once the responsible staff has determined which equipment is most critical, the organization recognizes and understands the nature of the failures and seeks to reduce them over time. On this basis, the team is able to identify the appropriate CBM technology to detect various faults early enough – so the maintenance team can plan repair or replacement decisions in good time to avoid serious faults and safety risks in the longer term.

Predictive maintenance is based on monitoring the systems and evaluating standardized operating parameters. This is the basis of downtimes and how they can best be avoided.
However, it is not necessary to switch off the machines during the evaluation – at least not with RevoCheck.

The use of condition-based maintenance of equipment offers several advantages – especially in a production- and equipment-intensive environment.

  • Reduced (unplanned) downtime and man-hours as faults are predicted before they even occur
  • Increased time between maintenance as repairs are only carried out when needed
  • Reduced production downtime as the CBM works while the plant is running
  • Fast diagnosis = reduced costs
  • Effectively managed stock levels as spare parts only need to be used for emergency situations
  • More predictable working day due to reduced equipment downtime

Predictive maintenance is usually associated with challenges such as higher investment costs for technologies and additional training. Ultimately, however, it brings a considerable return on investment in the long term:

  • Machine conditions are known at all times
  • Reduced malfunctions thanks to single intervention in emergencies
  • Damage to various components is already known in the initial phase so that replacement can be carried out at the most cost-effective time
  • Shorter repair times
  • Root cause of chronic failures and hidden faults are more easily identified
  • Reduced number of spare parts
  • Reduced insurance premiums
  • Increased investment security

Why do CBM programs usually fail?

There is usually a lack of clear goals and expectations:

  • Maintenance staff usually do not have enough time to learn the CBM tool
  • Root cause analyses should be operationalized to incorporate found cases into the tool
  • All stakeholders must be made aware of the necessity

The positive economic benefits of predictive maintenance are beyond doubt, as demonstrated by surveys of companies from various industries that have already implemented these tools. Additional best practice information for CBM programs can also be found in industry resources such as the Society for Maintenance & Reliability Professionals (SMRP) Best Practices Metrics.

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