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Making predictive maintenance more productive

31 July 2016

Predictive maintenance helps boost process efficiency by identifying problems early, and carrying out maintenance accordingly. It becomes much more productive when underpinned by robust, well-designed components, argues Phil Burge. 

With traditional maintenance regimes, overhauls are scheduled at predetermined times. This can result in parts being serviced – and often replaced – unnecessarily. It also fails to identify impending component failure.

Predictive maintenance uses an array of sensors and techniques to spot the early signs component failure which allows problems to be addressed at exactly the right time, rather than according to a fixed schedule.

It has been estimated that routine maintenance adds around 15% to the annual operating costs at an average food and beverage processor. The way to reduce these costs is not to cut down on maintenance – but instead to move to a more efficient way of doing it. A carefully planned predictive maintenance routine, for example, can help reduce maintenance costs, while boosting productivity – by helping to avoid shutdowns.

Of course, the food industry faces restrictions that are not seen in general industry – specifically that of enhanced hygiene, so predictive maintenance regimes need to be tailored to meet the requirements of food industry standards.

Predictive maintenance will take information from an array of fixed sensors to provide instant information on a machine’s condition. One variant uses vibration sensors to check the ‘health’ of bearings – an out-of-spec signal will indicate that they are beginning to wear – and will highlight whether failure is imminent.

Adding intelligence
A fixed sensor system can give process machinery – from filling stations to centrifuges –a degree of ‘intelligence’. The system gives operators an instant view of machinery conditions – including that of hard-to-reach components that would be impossible to monitor in any other way.

It is, however, important that an efficient predictive maintenance regime is underpinned by reliable components and systems, in order to ensure high standards.

A good example – which has become increasingly common in industry – is to perform automatic lubrication, rather than having a technician do it by hand. This is a more efficient solution which frees up the technician’s time for more pressing jobs. It can also do the job more accurately: technicians tend to over-lubricate components – which can lead to breached seals and product contamination.

In one example, a US pickle producer was finding it difficult to lubricate a newly installed palletiser. The system had around 150 lubrication points, of which 30 could only be handled when it was not operating. Bearings were failing frequently, and over-lubricated bearings often dripped onto cases before shipping. By switching to automatic lubrication – in this example, Lincoln Centro-Matic automated system from SKF was used, the company gained an extra 444 hours of uptime each year – for each of its six palletisers. Its investment was recouped in less than six months.

Rotating equipment can be a nightmare. Machines such as pumps, motors and fans can experience a variety of problems including high vibration and noise; failing seals; and elevated temperatures which can cause energy inefficiency, potential contamination and premature bearing failure.

Shaft misalignment
The root cause is often shaft misalignment. Solve this, and the problem is gone. Traditional methods to align a shaft – using a straight edge, thickness gauge, dial indicator, or even the naked eye – are time-consuming and imprecise. However, alignment-related reliability problems can be virtually eliminated by using laser alignment tools, which can detect and correct misalignment before it occurs.

Alignment problems were to blame for reduced equipment service life and increased downtime at a poultry processor. Using shaft alignment tool on 100 rotating machines resulted in a significant reduction in vibration – which helped to boost energy efficiency and reduce breakdowns. Overall, the system saved this company more than 15,000 Euros per year, in terms of reduced repairs, increased production time and greater energy efficiency.

Another poultry processor, working in a wet and aggressive environment, discovered the importance of selecting the correct bearings and seals. The company had been replacing hundreds of nickel-plated cast iron bearings every few months, because the harsh washdown conditions were causing them to rust – and washing away the internal lubricant. BY replacing its original bearing with SKF Food Line Y-bearing units – which combine stainless steel bearing inserts with multi-lip rubber seals – the company solved this problem.

The bearings are pre-lubricated with food-grade grease, so will not need to be re-lubricated. They last around four times longer than a standard bearing, which helps to cut replacement costs.

It is clear that predictive maintenance can make processing operations more productive. However, pairing this strategy with robust components and efficient systems, such as automatic lubrication, will contribute to even greater efficiency.

Phil Burge is country communication manager at SKF.

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