# mtbf calculation for software

MTBF = (8,760 hours – 35 … As mentioned, MTBF is a measure of reliability, and the more reliable our systems are, the more efficiently a business can operate. So, if I know the failure rate of my system is 500 FPMH (failures per million hours), then the MTBF of my system is equal to 1 / 500 failures / 1,000,000 hours, or 2000 hours. Because this is a forward-looking approach, it can only ever be approximate, and needs to take into account all factors affecting the situation and use appropriate predictive modelling methods. It can only provide an estimate of the likelihood of future failures, and only when used with appropriate statistical models. This information can be used to measure the decrease in reliability that can occurs as an asset ages and determine when a decision is made to replace a piece of equipment. Mean time between failures is the average – or mean – time that elapses from one unplanned breakdown to the next, under normal operating conditions. There are three main approaches to calculating Mean Time Between Failures. As you can see from the example above, the repair time is not included in the calculation of MTBF. A primary goal for all businesses is to maximise output and minimise downtime and mean time between failures is a useful metric to assess the reliability of the systems that support your operations. Reliability is also an important consideration during the product design process, where MTBF estimates can help improve reliability before a product is even made. By continuing to use this site you agree to this. Following is the list of useful converters and calculators. By keeping MTBF high relative to MTTR, the availability of a system is maximised. This means that the average time between failures of this the machine is around 578 hours, or just over 5 weeks, under typical operating conditions. This indicates that on average my system will fail every 448 hours of operation – not that it will fail precisely at 448 hours. MTBF is generally calculated over a period of time that includes multiple failures – either multiple failures of a single asset or single failures of multiple assets of the same type – so that an arithmetic mean or average of the time between disruptions can be determined. Some people get confused and think that MTBF is actually a measure of useful life. We have a total time of 4 weeks x 7 days x 24 hours x 150 belts = 100,800 hours minus the 200 hours of repair time = 100,600 hours of uptime, with 50 failures in total. Once a non-repairable asset fails it is considered to have reached the end of its useful life. Useful converters and calculators. For example, a typical MTBF vs. Time plot in RGA will be: Figure 3: MTBF vs. Time Plot for a Repairable System . © 2020 Relyence Corporation All Rights Reserved. This is a very simple example of calculating MTBF. Mean time between failures is a metric that’s only used for repairable systems. The key difference between MTBF and MTTF is that MTBF applies to repairable systems, while MTTF is for non-repairable equipment. Reliability Prediction software is the most efficient way to calculate failure rate and MTBF. Sure, it might have “just been” a worn out part or a random occurrence, but take the time to look for systemic issues that might have contributed to the failure, that you can address. You can calculate MTBF with a physical product, such as a car part, or a hard drive, you can physically test until failure, and do it enough times to statistically derive the MTBF. The best way to calculate an accurate MTBF for a specific piece of equipment or software is to measure its performance in day-to-day use in an organisation. In one year, the system faced 2 breakdowns, once for 12 hours and once for 23 hours, for a total unplanned downtime due to breakdowns of 35 hours. Watch the video to learn more.