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Run-to-failure is a poor strategy

Many companies don't manage their aging assets. They let them fail and then replace them. This strategy of running to failure, coupled with the typical preventive maintenance (PM) approaches, opens the company to several unpleasant risks: first, the opportunity to replace an asset before it fails, thereby avoiding a costly recovery, is lost; second, as assets age together, the chance of their failing in groups increases, with potentially devastating cash flow consequences; third, there is very little understanding of the actual condition of the asset inventory, so any company policies are not based on realistic considerations--which opens up the possibility of any number of surprising and, almost surely costly, outcomes. What is known is that the assets will fail. What is not known is when and with what consequences.

What We Do

We provide an analytic methodology that identifies the optimal (least cost) policy for managing an inventory of aging assets. The policy specifies when to replace an asset, when to repair or refurbish an asset, and when to test an asset. Testing is an interesting aspect of the optimal strategy, because the test result can reveal valuable information about the condition of the asset. It is the present condition of the asset that helps one forecast the future behavior of the asset. It is the forecast of future behavior that indicates what to do with the asset at any time.

The methodology is based on company-specific data and judgment about the behavior of the asset. We have made the data-gathering requirements as simple and straightforward as possible. This methodology substitutes mathematical sophistication for reams of data. The methodology is implemented in very easy-to-use software.

The Benefits

We answer the following questions.

• What is the optimal replacement strategy for a given asset?
• How will the asset population evolve over time with this strategy?
• What are the cash flows associated with the optimal policy?
• How does an alternative strategy compare with the optimal strategy. What are the population effects and costs of this strategy?
• In particular, what are the consequences of continuing to run to failure?
• What are the possible futures of one asset over time?
• A test is available. How much is it worth? Is the cost of the test justified?
• What is the least-cost testing strategy?
• How sensitive are the results to test accuracy? How much would a more accurate test be worth?
• What is the overall economic value of a proposed testing program?
• How sensitive are the results sensitive to assumptions about replacement, failure or testing costs?
• How sensitive are the results to failure rate data or assumptions?
• If we extend the study period, do the results change materially?
• Is the policy sensitive to the discount rate?

Applications

The methodology has been applied to the electric power industry, with particular attention to managing populations of transformers, underground cable, and wood poles. The cost savings are significant. There is no restriction whatsoever on the asset type or industry. The methodology is universally applicable.