Predictive maintenance & condition monitoring

Does wireless monitoring mean the death of the walkaround?

n an ideal world, manufacturers would know exactly how long their product would take to make, it would always be consistent and of the highest quality and there would never be any machine downtime issues. In actuality however, there are constant operating challenges for maintenance teams to overcome to ensure maximum overall equipment efficiency (OEE). Over the years, condition monitoring technology has played its part in helping maintenance teams to maximise OEE. For as long as there have been machines, people have understood the need to monitor and maintain them. However, while the principle of industrial plant asset management remains constant, the methods have evolved over time. According to research carried out in 2016,


just over half of US companies (55 per cent) still had a ‘run to failure’ approach to maintenance. Although many manufacturers across the globe see run to failure maintenance as a cost- effective strategy, unplanned breakdowns can cause significant cost, maintenance and production disruption. This ineffective ‘wait until it breaks’ approach to maintenance has been replaced by many manufacturers with a more proactive, preventative maintenance approach. In fact, ABI Research has forecast that in 2026,


manufacturers and industrial firms will be spending £15.4 billion on data management, data analytics and associated professional services . With preventative maintenance, regular maintenance tasks are scheduled to reduce the possibility of asset failure. Although this method increases asset life span, encourages efficient productivity and reduces unplanned downtime, it does not consider asset wear or the time required to schedule and assign tasks. The time invested in scheduling, preparing and delegating team tasks is significant, but it has proved a more cost-effective strategy than the run to failure approach. However, more and more manufacturers are increasingly seeing the benefits of conducting maintenance based on trends within asset data – a strategy known as predictive maintenance. Predictive maintenance uses insights gained

from machine data to forecast when a problem is going to arise with a machine, allowing maintenance to be performed before the problem escalates to machine failure. At the heart of this is condition monitoring - the practice of collecting and analysing data on specific operating parameters from a machine. The future of maintenance strategies however is being transformed still further by digitalisation.

THE CHANGING FACE OF MAINTENANCE MONITORING When it comes to condition monitoring, the ongoing digital revolution in industry is set to transform both sides of the cost benefit equation. This is going to drive a big shift in the way companies collect data on their machines, and what they do with that data once they have it. To understand asset condition, technicians collect and track tangible data on a host of physical parameters and see how that data changes over time. In many industries, routine measurement of temperature, vibration and lubricant condition for example, have become standard practice. To discern the condition of a machine, the data can be collected in two fundamental ways: manually or automatically. When maintenance teams use the manual approach, they are equipped with handheld devices and they subsequently walk the floor, measuring and recording parameters during routine inspections. When the process is automated, permanent sensors are installed on all key machines, transmitting data across a network. This automated process has seen significant progress over recent years, thanks to mesh networks and

October 2020 Instrumentation Monthly

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