Predictive maintenance technologies: How are they being implemented today?

How are predictive maintenance technologies being implemented in the average plant today? Through a survey conducted by Plant Services with maintenance and reliability professionals, we learned how each of them use predictive maintenance technologies in their facilities every day according to their own experiences and views.

Many of these facilities are on the cutting edge and already have some form of predictive maintenance in place. However, it is also true that still very few are using the vibration analysisas well as oil analysis or tests on electric motors.

With any predictive maintenance programmeIt is important to take a baseline reading to see how effective it is and where improvements can be made. When asked to rate the performance of their predictive maintenance technologies programme over the past 12 months, more than half admitted that their programmes need some improvement.

We are not really surprised by these results. Our engineers on the street observe that a considerable group of application programmes for predictive maintenance technologies have only the basic concepts and do not yet have the potential for refinement and optimisation.

For others, the predictive maintenance is a job and not a profession, so refinement and improvement are not among their main interests. In general, there are fewer professionals specialised in predictive maintenance than we would like to see.

This situation can be solved with more remote monitoring of machine and facility conditions. By collecting data wirelessly or wired, the need for highly skilled predictive maintenance technicians at each plant site can be reduced and instead use general maintenance and remote analysis technicians. In this way, efforts can be pooled to collect remote data, across many large plant sites, for analysis by a single, well-qualified individual.

Predictive maintenance technologies: their use in the future

Many plant engineers who are using predictive maintenance technologies are not taking the time to justify what they are achieving in terms of return on investment. They are not showing their superiors what they are achieving in terms that they understand.

As with any improvement, there are always hurdles to overcome when implementing or improving a predictive maintenance programme. While respondents acknowledged that many of their programmes needed improvement, they cited budgetary constraints and lack of executive support as two of the biggest obstacles that needed to be overcome.

While most respondents seemed to have taken a more traditional, i.e., less technology-driven approach to the use of predictive maintenance technologies, they were asked about which emerging technologies they would be considering including in their predictive maintenance initiatives. Within the next three years, many respondents plan to have analytics software, tablets, wireless connectivity for field workers, and predictive maintenance intelligence embedded in supplier equipment.

Technologies are becoming less stock costly in terms of needing capital investment, and being more capable and user friendly in terms of hardware and software. More and more companies want simpler equipment, especially vibration, so they can have their own staff collecting data with an external service provider analysing and reporting.

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