Meeting the plant reliability challenge

As economic conditions tighten, organisations are delaying the replacement of ageing assets. The challenge for maintenance engineers is keeping old machines running efficiently 

The economic downturn is bringing new challenges thick and fast, from inflation and higher interest rates to supply chain disruption caused by military conflicts in Europe and elsewhere.  

In a climate like this, many organisations will struggle to justify the cost of replacing ageing assets. That leaves maintenance engineers working hard to extend the reliability of old machines and trying to keep operations running smoothly. More than a quarter of respondents to the Industry in Motion report produced by RS and the Institution of Mechanical Engineers (IMechE) cited ageing assets as a key driver of unscheduled plant downtime. At the same time, more than half said the data they are currently measured on is not at all reliable.   

Tactics for increased reliability
Condition-based monitoring is important for increasing productivity and reducing unexpected breakdowns and downtime. It uses technology to monitor the performance of machines and plants without the need for regular manual inspections.    Sensors keep track of a range of machine performance parameters such as vibration, oil quality and running temperature, and continuously send this data to a monitoring unit. When a machine is found to be running outside expected parameters, early interventions can be made to prevent equipment failure and unplanned downtime.  

Condition-based monitoring enables an organisation to adopt a predictive maintenance approach driven by digital technologies. Connected devices and machine learning, operating within an Internet of Things (IoT) architecture, generate rich streams of data on plant performance.

While predictive maintenance is not a recent innovation, developments in data acquisition and analysis are a game-changer, says Richard Jeffers, Solutions and Technical Director at RS. “The cost of generating and processing data has dramatically reduced. You no longer need human beings to collect and interpret it – technology can do all that,” Jeffers notes.

“What hasn’t changed is the cultural shift required to derive value from data. You need an organisational attitude to data that values an engineer that operates in a calm environment because they’re in control, not running around like a superhero fixing broken things. Many businesses are still rewarding the hero culture, rather than rewarding the analytical culture.” 

When data is collected and analysed effectively, maintenance engineering can generate accurate forecasts to predict when intervention is required. Accurate planning of maintenance operations based on insights from data results in a more efficient and effective maintenance engineering strategy.  

Aligning maintenance engineering with business priorities
The requirement to keep old machines running reliably for longer is a consequence of changing business needs in uncertain economic times. Condition monitoring and planned maintenance are ways to help businesses reduce costs and raise efficiency. 

Maintenance engineering teams may also need a change of focus to deliver on new priorities in these challenging times. This could involve flexing their thinking and viewing their roles in the context of wider corporate objectives, suggests Maintenance Engineering Academic Dr Moray Kidd.

Dr Kidd also sees the need for a shift in mindset in the boardroom. “Maintenance engineering has historically been seen as an overhead,” he says. “But good maintenance engineering does not cost you – it should pay you. If it’s done well, it’s a sound investment.”   

 A sound investment in today’s economic climate would be a focus on maintenance engineering viewed in the context of wider business needs, Dr Kidd adds. “I think that’s going to be a popular approach, but it needs some nuance. A hybrid approach is where I think people should be moving to – matching up the corporate strategy with reliability-centred maintenance engineering.” 

Embracing digital technology
Data is now a significant differentiator for value creation and can help maintenance engineering teams that are increasingly expected to contribute to their company’s bottom line. This is why harnessing the power of digital technology in predictive maintenance strategies is a wise investment in difficult economic times. Demonstrating ways to reduce unplanned downtime and improve profit margins will be well received in the boardroom in an era when every cost must be justified.  

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