Feature sponsored by Test & measurement
out maintenance programs in far less time, yet be far more effective in their results. Using and analysing data ML and AI to identify in advance equipment that is likely to cause problems not only has the advantage of identifying likely problem areas before they occur, but they also pinpoint and – importantly – confirm those potential problem areas in a way that keeps multiple teams from running into and across each other, either by looking in the wrong places, or chasing issues that are non-existent.
STILL, THERE ARE ISSUES
It is important to acknowledge that predictive maintenance is not necessarily a guarantee of water conservation and future supplies. Such programs do not just implement themselves. They require corporate vision and a champion among those who run an operation. And it is not always an easy sell, often for one reason: Although predictive maintenance is proven to work, it requires lots of data. And this is where some implementations stall. Where, and how do you store, and process all that data? For how long? At what cost? Who ‘owns’ it?
FORTUNATELY, NEW DATA STORAGE AND MANIPULATION SOLUTIONS ARE NOW AVAILABLE
Numerous solutions are readily available, but many require a degree of expertise to evaluate and implement that many companies lack internally. Even decades of
46 June 2023 Instrumentation Monthly
experience in water treatment, processing, distribution and conservation can be questioned in the face of how that experience might apply to deployment of new IoT technologies and techniques. There is a gap between those legacy preventive maintenance techniques and those who know how modern predictive maintenance can deliver advantages that preventive maintenance no longer can. The wisdom lies in partnering with someone who knows the difference. Fortunately, suppliers such as ABB, which designs and manufactures devices and data- gathering technologies for today’s users have long been conscious of the necessity of making the transition to Industry 4.0 as seamless as
possible, going to great lengths to devise and deliver solutions that provide measurable results.
THE TIME TO CONSERVE WATER IS NOW A new generation of sensors and instrumentation that use ML and AI analyse, learn from and action data as they operate in real time every day are steadily improving our ability to meet the water demands of the near future. However, the pace of predictive maintenance programs must be stepped up to increase efficiency, reduce cost and, most important, secure long-term availability of one of our most precious life-sustaining resources.
ABB
www.abb.com
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