Trends in data collection for a predictive maintenance programme

Implementing a proper predictive maintenance strategy is a great idea, but you will never succeed if you are not using the information to take the right steps. It's true that maintenance, operations and reliability engineers are reading and interpreting the information, but you still need to translate this data into action.

Yet some reliability engineers have never used the information provided by the su condition monitoring equipmentThis wastes a substantial portion of data that could be used to develop and refine maintenance and reliability plans and strategies.

The predictive maintenance solutions should not necessarily be on their own. In order to create a greater understanding of the plant and its overall maintenance, the predictive maintenance systems can be integrated into higher-level systems. CMMS/EAM software and historians are the preferred systems for many maintenance managers to achieve this.

The greatest value that predictive maintenance tools can provide is the element of time. Time allows planning, scheduling, and ensuring the execution of the repair at minimum total cost and minimum total downtime.

Why does the predictive maintenance programme sometimes get lost in the shuffle?

Often what happens is that some of the best and brightest maintenance technicians are given responsibility for predictive maintenance. They perform brilliantly but in obscurity because they are not aware of their achievements.

Then they are changed, replaced by other technicians or assigned other tasks. Technology is put on the shelf and sometimes not used for several months, if at all. The consequence is that assets slowly deteriorate and decision-makers do not notice the lack of attention from predictive maintenance specialists until things are really bad.

Therefore, their recovery is an uphill battle. Many organisations do not have succession planning and retention initiatives and are surprised when they lose predictive maintenance specialists.

We see an increase in the use of online wireless data collection and the cloud for technologies such as mobile phones and tablets. vibration analysis. Communication links for smartphones, tablets, personal computers will be commonplace within two to three years.

These technologies are being used by very few yet, they are underestimated and hardly used today, sensors capable of detecting and transmitting machine condition data will be increasingly used, no longer requiring an operator making rounds or a predictive maintenance technician in the field carrying tools measuring from point to point.

We will now see technicians who are more specialised in information analysis and decision-making. They will invest their time in actions of greater value to the company. There is now a closer relationship between supervisory control and data acquisition. This will accelerate as cloud and advanced analytics gain acceptance.

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