Asset Management Optimization with Predictive Maintenance – Digital way to Reliability

Maintenance optimization is the process of managing the performance objectives of an
asset. Carrying out proper maintenance of equipment and machinery improves its
productivity and efficiency. There are different ways of sustaining assets, such as corrective
maintenance, preventive maintenance, and predictive maintenance. On the other hand,
predictive maintenance is a technique that implements condition monitoring to ols to track the
performance of equipment. The equipment is studied during an operation to detect defects
and fix them before the machine fails (Ozekici, 2013).
The condition
monitoring tools used during preventive maintenance include the use of
sensors a nd the use of IT. Maintenance sensors monitor how the machines accelerate during
operation through vibrations (Dorf, 2018). The sensors are mounted to a very rigid part of the
device to ensure that the vibration signals are detected. Another critical eleme nt used during
predictive maintenance is the use of IT. Predictive maintenance using IT is done by storing
large amounts of data and running algorithms on several computers to detect the possible
failures in the equipment and the hazards they are likely to cause (Mobley, 2011).
Another method of maintenance optimization is preventive maintenance. It is
performed by team technicians on a piece of equipment to reduce the likelihood of it failing.
Like predictive maintenance, preventive maintenance takes place while the machine is still
working. The technicians implement software such as CMM software to ease optimization.
The software allows the oil industries to gather information about their equipment and
determine the triggers that may lead to system failure (George, 2016). Most industries prefer
preventive maintenance to any other type of maintenance optimization technique as it does
not require condition monitoring tools. The absence of the tools reduces the cost incurred
during equipment maintenance.