In many industries, people need to know what the mean time between failures is for a particular system. MTBF prediction isn't perfect, but it's highly effective at scale. If you're wondering why MTBF prediction and calculation matter, study these four common use cases.
One of the most common use cases for MTBF calculation is maintenance. Manufacturers often have machines that require periodic attention. Knowing the MTBF for a system allows them to schedule maintenance with an eye toward the expected failure time. Technicians can refit the system and put it back into operation. Overall, this reduces the number of unexpected failures and ensures that the manufacturing line will be online longer.
Understanding the role of MTBF also allows you to schedule maintenance across a factory or fleet in a more orderly manner. A trucking company, for example, can pull rigs off the road based on how close they are to their MTBF figure. This reduces the risk of fleet disruptions because the vehicles are always operating with a low expectation of failure.
Comparing the known MTBF figure between two possible options can inform purchasing decisions. If you're trying to decide between two relatively equal pieces of machinery, the decision may hinge on which one will require less maintenance. A company buying used hardware also can use the MTBF prediction to determine if a sale price represents good value.
A company's products can create exposure to liability risk. Suppose a company has introduced a new vehicle, and the vehicle's real-world MTBF performance doesn't match the predictions. The company could assign investigators to see if something is wrong with the vehicle or if drivers are using it in unexpected ways. This might trigger a recall, but doing it quickly also can keep a company's liability risk down.
Data gleaned from MTBF calculations also can support your defense in a lawsuit. If a party asserts that your firm was negligent in putting a product on the market, you can show that the data reflects a reasonable expectation of failure.
Selling or Decommissioning Old Hardware
Knowing when to sell your hardware is important. A data science company might decommission its hardware based on an MTBF calculation. It can recoup money from old systems while ensuring that newer systems will keep their servers running for years to come. Likewise, establishing a replacement cycle can stabilize the company's annual outlays for hardware.
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29 March 2023
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