Maintenance is often considered by the management as just another expense which is associated to the failure in operational technology and devices. However, in the recent years, the management had realised the importance of maintenance as it contributes various added values to business processes such as preservation of assets, reduction of cost through optimising maintenance and prevention of malfunctions and breakdown. Nowadays, the advancement of technology and the innovation of internet of things (IoT) had shifted the maintenance strategy into a more advance approach called the predictive maintenance. What are the definition and types of predictive maintenance?
Predictive maintenance or in short PdM is a type of maintenance strategies that focuses in preventing downtime. This strategy involves the use of monitoring equipment such as sensors and smart technologies to identify parts of machine with the likelihood to become malfunction and provide notification to the maintenance team during the operation process. There are various types of predictive maintenance that can be carried out depending on the factory operations. The types of predictive maintenance include:
When machine is running, it produces vibration. Vibration analysis refers to a process that monitors vibration data within the running machines such as the levels and frequencies of vibration. In vibration analysis, the gathered data will be compared to the acceptable operation vibration limits of the machine. The breaching of this limits shows that the health condition of the machine is declining.
There are two methods of gathering data through acoustical analysis which are sonic acoustic analysis and ultrasonic acoustic analysis. Sonic acoustic analysis focuses on obtaining data from low-and high-rotating machinery. The example of data obtained by sonic acoustic analysis is the lubrication levels of equipment. On the other hand, ultrasonic acoustic analysis gathers data from the sound created by machineries with the range of frequency that cannot be heard by human ears. For example, the data on the level of stress and friction of equipment.
Through infrared analysis, high temperature condition that is emitted due to worn out equipment and malfunction electric circuit are detected using infrared cameras.
In conclusion, unexpected downtime is the source of headache to organisation. Therefore, based on the definition and types of predictive maintenance, it is most certain to say that it is a great move for every organisation to implement predictive maintenance as their future maintenance strategy.
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