If you’re a manufacturer of machinery of any kind, you’re constantly evaluating your assets to make sure everything is working properly so production runs smoothly. Performing routine scheduled preventive maintenance keeps everything in good working order.
Although the “correct mode of operation” is the norm, we all know unexpected things happen – oil leaks, a screw vibrates and loosens, a gear seizes – and it creates a breakdown, leading to downtime. stoppages and interruptions in production and sometimes panic.
When failures occur in repairable systems, the urgency is to make them operational as soon as possible. Once back up and running, the issue sometimes takes a back seat due to more pressing issues that have arisen.
When the next failure occurs on the same piece of machinery, some of the wisdom gained from the initial fix has been lost and repairs are started again.
The third time the asset fails, everyone scratches their head and wonders how long the asset will work this time.
One way to help with this situation is to find out the mean time between failures (MTBF), a key production indicator. Mean time between failures is the expected elapsed time between failures of mechanical or electronic assets and helps to assess the expected life of the equipment.
Many common standard items, connectors, and semiconductors have established MTBF life figures, but these are still only estimates.
MBTF is a prediction of a product’s reliability between failures or conditions that place the system or asset out of service and require repair. Failures that can be ignored or that allow the asset to continue without repair are not considered failures for this calculation.
MTBF is usually based on an established analysis model. There are various such models where MTBF is specified with a duty cycle parameter and can include a wide range of factors specific to an asset and its use.
MTBF is a parameter that expresses the average time between faults occurring in an asset, calculated over a given period of time that encompasses the dates of failure. As in the example at the beginning, each date of failure should be recorded, along with the time between failures.
The MTBF is then calculated using a complex arithmetic mean. The easiest way to acquire MTBF is to enter your data into your CMMS and have the system provide this information on a dashboard, so the analysis for the user – and management – is readily available. and that downtime can be minimized.
With this readily available information and ongoing analysis of reports, product reliability can become the norm, as can continuous production.
How to improve MTBF
It seems obvious to say that increasing MTBF increases equipment availability, but it is important to mention it nonetheless.
With the advent of computerized maintenance management systems (CMMS) and enterprise asset management (EAM) software, companies can actually more easily manage equipment maintenance efficiently.
Maintenance management software generates reminders when maintenance is due, helping to extend equipment life. When properly implemented, CMMS software can be used to analyze maintenance costs and identify areas for improvement.
In order to improve MTBF, the first step is to ensure that you have accurate data. The CMMS software not only stores all equipment data (date of purchase, manufacturer’s instructions, etc.), but also the work history (preventive maintenance, work orders, etc.).
The final step, easier said than done, is to use this data to be proactive in performing maintenance. With analysis, it can be determined that older equipment has more uptime and requires fewer repairs than a newer model. As a result, equipment replacement may be deferred and funds may be allocated for other expenses, such as capital improvement projects.
Alex Williams is Director of Sales and Professional Services at DPSI, a provider of computerized maintenance management systems (CMMS) and enterprise asset management (EAM) software.