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Organizations that manage critical infrastructure rely on a wide range of asset types to provide their services. These asset populations can include millions of assets of varying complexity and cost. Modeling asset condition and the related probability of asset failure is non-trivial and costly. Therefore, assets that require modeling are those whose failure will cause significant expense or risk to an organization, or where the cost of replacing the asset is high.
The goal is for organizations to maximize the value of their capital and operational expenditures over time. To do this, the risk of an asset failing to operate as desired must be modeled. Risk is defined as the probability of failure of an asset at a given point in time multiplied by the consequence (s) of such a failure. Models are classified into two categories:
1. Those that calculate asset condition and resulting probability of failure
2. Those that calculate the costs (both to the organization and society) of such failures
The benefit realized by performing an intervention on the asset at a given time is the predicted reduction in risk achieved by improving the asset condition, compared to not doing anything. The benefit is compared to the cost of the intervention to better understand the cost of action vs. inaction. The time at which an intervention provides the best value considers possible constraints such as limits on expenditure, performance KPIs, resources, etc.
This story is from the March - April 2024 edition of MACHINERY LUBRICATION INDIA.
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This story is from the March - April 2024 edition of MACHINERY LUBRICATION INDIA.
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