This article was originally published in the March 2022 edition of MRO Management Magazine
by Jason Holland
Data is the foundation of any predictive maintenance solution – and massive amounts of it are generated on each flight, particularly on digital, new generation aircraft. But this data is only useful when it is properly analysed, interpreted and communicated between stakeholders.
Predictive maintenance solutions take information from component sensor data and maintenance history logs to estimate when parts will need to be repaired or replaced, explains David Purfurst, global pre-sales director at software company Rusada. “With this information, maintenance can be planned and executed ahead of component failure, as opposed to after it. This reduces the occurrence of costly unscheduled maintenance and AOGs, which in turn reduces the amount of inventory required to be held in reserve for such events.”
As with any other sector, though, the Covid-19 crisis disrupted predictive maintenance’s growth trend, especially as reduced airline operations were less prone to unplanned maintenance. But could the crisis also have spurred additional interest in the extra efficiencies to be gained from predictive maintenance?
“We are seeing both [scenarios],” says Rusada’s Purfurst. “Some operators took advantage of their downtime to review their IT landscape and bring on new efficiencies wherever they could. Others had to slow down their plans in this area and focus on other things. Which of these camps they fell into really depended on their financial situation, the amount of staff they were able to retain during the pandemic, and what other projects they had in progress. What we have seen in the last six months is an increase in the desire to get IT projects of all types going again. As a result, we have had four customer go-lives in the past four months, with many more planned throughout the year.”
Aside from the technical challenges, the success of predictive maintenance in the future will also be determined by the ability for partners across the industry to collaborate.
Rusada’s Purfurst says there is still an unwillingness from many operators to share their data, “especially with people who may be their direct competitors, but there is also a growing number who see the advantages it can bring”.
He adds: “I think as perception changes, partnerships will be struck to facilitate the sharing of data, and this will greatly benefit all involved. Obviously if there is a simple and easy way to facilitate this with software, it will remove one of the reasons not to do it. We are currently investigating different ways in which this could be done on our ‘ENVISION’ solution and determining how best to proceed.”
While there have been many positive developments in predictive maintenance, there remains a long way to go before its full potential is reached.
Artificial intelligence (AI) is one area that can help it get there, supporting human experts and engineers in their daily work and helping companies better understand the data.
Purfurst says AI could ultimately be used “to turn predictive maintenance into ‘prescriptive maintenance’, to the point where your software system will be able to advise precisely where and when maintenance should be executed based on a whole myriad of factors from across the operation”. But he cautions that while there are many exciting innovations waiting in the wings, the adoption of IT solutions in aviation has been “slow historically, so we will have to be patient”. That said, he thinks, “the industry seems to be moving faster than at any point before towards new technologies, so hopefully we will be able to see these used widely in everyday scenarios in the not-too-distant future”.
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