MTBF prediction and calculation processes allow you to make determinations about the likelihood that a system will fail within a specified period. This has implications for manufacturing, computing, business processes, and many more fields. You might wonder how these calculations and predictions may be useful for your operation. Here are four common cases for employing MTBF prediction and calculation services.
Inspection, Repair, and Refit Cycles
One of the most common uses is to determine when to inspect and repair machines. A typical mining operation, for example, depends on keeping several large trucks running during periods of peak profitability. When demand is high, a mine wants to have trucks moving at nearly all times. However, downtime can be more damaging to profits than maintenance time. Consequently, a mining business may use an MTFB prediction model to schedule cycles of inspections, repairs, and refits to minimize periods where the trucks are out of operation. This also makes fleet availability more predictable because one or two trucks might usually be out of circulation at any given time.
A solid MTBF calculation can also serve as a marker for quality control. If a company knows that a system manufactured to certain specifications will fail at a certain rate, it can make assumptions about failure rates that exceed that figure. Whenever the company identifies excessive failure rates, it can check supplies, manufacturing processes, and other sources of defects. This can allow it to improve recall times and deal with quality issues faster.
While it's easy to focus on MTFB calculation techniques as a way to deal with machinery, it also is useful for improving processes. If you have an assembly line, you can calculate how often and under what conditions it will begin to experience more failures. This allows you to maximize output while also reducing the odds of catastrophic failures. Even if the process in question involves lots of people, the human element can lend itself to MTBF prediction within certain process models.
Budgeting, Upgrading, and Replacement Schedules
Knowing when things will likely fail also sheds light on the process of budgeting, especially as it applies to upgrade and replacement schedules. A server farm, for example, will want to swap equipment out before it begins to fail. However, the company will also want to maximize the value of each system before upgrading or replacing it. Using an MTBF prediction, the company can determine the appropriate time in each server farm's lifecycle to upgrade or replace its system.