If you are a manufacturer with machinery of any kind, you are constantly assessing your assets to ensure that everything is working correctly so that production will run smoothly. Performing routine scheduled preventive maintenance helps keep everything in proper operational mode.
Although ‘proper operation mode’ is the standard, we all know unexpected things happen – oil leaks, a screw vibrates and loosens, gear seize – and this creates a failure, leading to downtime and production disruption and sometimes panic.
When failures in repairable systems happen, the urgency is to get operational as soon as possible. Once operational again, sometimes the problem moves to the back burner 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 correction has been lost and repairs are once again initiated.
The third time the asset fails leaves everyone scratching their head and wondering how long the asset will work this time.
One way to help with this situation is to discover the mean time between failures (MTBF), a key production indicator. Mean time between failures is the predicted elapsed time between failures of mechanical or electronic assets and helps assess the anticipated operating life of the equipment.
A great many items, connectors and common standard semiconductors have established MTBF life figures provided, but these are still just estimates.
MBTF is a prediction of the reliability of a product between failures or conditions that place the system or asset out of service and in need of repair. Failures that can be ignored or allow the asset to continue without repair are not considered failures for this calculation.
MTBF is usually based on an established analysis model. Various such models exist where MTBF is specified with a duty cycle parameter and may include a broad array of factors specific to an asset and its use.
The 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 needs to be recorded, as well as the time span between the failures.
MTBF is then calculated using a complex arithmetic mean. The easiest way to acquire the MTBF is to enter your data into your CMMS and have the system provide that information on a dashboard, so that analysis for the user – and management – is easily available and downtime can be minimized.
With this information readily available and continuous report analysis, product reliability can become the standard, along with continuous production.
How to improve MTBF
It seems obvious to say that increasing MTBF increases the uptime of equipment, but it is important to mention nonetheless.
Thanks to the advent of computerized maintenance management systems (CMMS) and enterprise asset management (EAM) software, companies can actually manage equipment maintenance in an efficient manner more easily.
Maintenance management software generates reminders when maintenance needs to be performed, which helps extend the life of equipment. When implemented correctly, CMMS software can be utilized to analyze maintenance costs and identify areas for improvement.
In order to improve MTBF, the first step is to ensure you have accurate data. CMMS software not only stores all equipment data (date purchased, manufacturer’s guidelines, etc.), it also stores work history (preventive maintenance, work orders, etc).
The final step, which is easier said than done, is using that data to be proactive with performing maintenance. With some analysis, it may be determined that an older piece of equipment has more uptime and requires fewer repairs than a newer model. As a result, equipment replacement could be postponed and funds could be allocated toward other expenditures, such as capital improvement projects.
Alex Williams is the Director of Sales and Professional Services at DPSI, a provider of computerized maintenance management systems (CMMS) and enterprise asset management (EAM) software.