• Novice
  • Aware
  • Competent

Predictive Models for Other Primary Failure Modes

There are several ways an asset can fail to provide its required level of service or reach the end of its effective life.

Depending on the type and situation of the asset, the likely failure modes should be identified in the attribute database.

Decisions can then be made on the type of modelling that will identify the likely timeframes for the various failure modes.

The ability to quickly interface with the historical asset data will assist this process.

Failure modes include:

  • Lack of Capacity - the growth in demand has or will outstrip the asset's ability to provide the service required
  • Inefficiency - due to technological change, the asset could be replaced effectively by an updated asset
  • Obsolescence - due to a lack of spare parts etc. the asset can no longer be maintained
  • Level of Service falls below acceptable levels - reliable performance cannot be achieved without excessive maintenance or renewal costs.
  • Structural Integrity - the age of the asset is such that it reaches the end of its effective life and mortality failure occurs
  • Lack of Utilisation - The organization's objectives, strategies, needs or core activities no longer require the asset and it can be disposed of
  • Operator Errors - Human judgment error can often result in the early failure of an asset. eg. not following optimal maintenance practice on plant and equipment or wrong operational procedures. Effective asset management requires that this type of failure mode be recognised and appropriate treatment strategies be applied.

These failures should be capable of being modelled by one of the following methods:

  • Set estimated remaining life
  • Modelled against growth in demand
  • Set condition decay model.


The primary functionality is covered by:

  • Enable the predictive modelling of the three key failure modes
    • Condition decay (physical integrity)
    • Performance (reliability/availability)
    • Capacity (demand utilisation failure)
  • Enable the prediction of the time in which failure is most likely to occur or accommodate two scenarios - high or low - for each of the above failure modes
  • Analyse treatment options.

For the condition decay module, the following inputs must be included:

  • Do nothing period
  • Maintenance related activities
  • Rehabilitation activities
  • Replacement activities
  • Accept inputs to the module from associated activities eg.
  • Condition monitoring activities (MMS)
  • Failure records and analysis (MMS)
  • Asset utilisation (operating system records, SCADA).
  • Treatment options/costs.

After predicting the failure mode of an asset, it is necessary to assess the treatment options and their costs.

The treatment options/costs module should have the functionality to:

  • Determine the options as appropriate to the conditions of the assets or the likely failure mode
  • Allow the benefits to be derived from the various options
  • Accept input from associated activities, eg. risk analysis, condition module
  • Select the option that will result in the lowest cost in terms of the net present value.

After assessing the options available, the system should be able to determine the option that:

  • Has the lowest life cycle cost for the asset
  • Will provide the highest level of service acceptable by the customers.

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Knowledge Management / EDC System   Primary Information Systems