PAM is PAM Analytics’ innovative decision support Predictive Asset Management system for optimising infrastructure asset management. It uses predictive analytics and discrete event simulation (a form of simulation in which, in this case, maintenance interventions (the events) are simulated as pulses on defined assets at defined times rather than as continuous events) to optimise asset performance at individual asset level and at the operational, tactical and strategic levels with respect to the assets’ maintenance and replacement costs, and the consequence costs of asset failure.

PAM enables organisations to gain insight and understanding into the causes of asset failure and so change their asset maintenance procedures and possibly some assets to optimise their asset management policy, mitigate the risk of future asset failure and extend asset lifetimes.

PAM is a complete system and consists of a number of modules for loading and preparing the data right through to viewing the results. PAM has four output modules (Asset Key Performance Indicators, Asset Deterioration Curves, Predicted Maintenance Interventions and Asset Survival Simulations) and each one has its own visualisation component for viewing and exporting the results.

Operational Benefits of PAM

Asset Safety  

• fewer safety related failures and service interruptions

Asset Performance

• higher asset availability (reliability)
• increased asset longevity

Asset Management Costs        

• lower asset maintenance costs
• fewer asset replacements and lower asset replacement costs
• lower consequence costs resulting from asset failure due to, for example, flooding, pollution and service interruption

Use of Organisation Resources         

• staff freed up to work on proactive maintenance or in other areas of the organisation.

The following documents can be downloaded on the left.

• Introduction to PAM provides an introduction to PAM. The appendix has a brief introduction to survival analysis (the failure model in PAM).
• 12 Key Questions on PAM answers 12 key questions on PAM.
• Asset Criticality, Redundancy and Risk of Failure Scores discusses asset criticality, shows how PAM models asset redundancy and defines asset risk of failure scores.
• Example PAM Results presents sample results from the Predicted Maintenance Interventions and Asset Survival Simulations modules.
• Data Preparation, Exploratory Data Analysis and Predictive Asset Management describes the role of data preparation and exploratory data analysis in analytics projects and how they are applied to predictive asset management.
• The Predictive Analytics Cycle and PAM describes the four types of analytics in the predictive analytics cycle and how PAM applies them.