Big data must first be segmented into smaller sets to create meaningful intelligence for logistics, MRO and supply chains.
That was the verdict of Greg Hoggett of aviation specialists AJW Group, following a panel sessions entitled ‘Getting smarter with digital aircraft’ at MRO Europe 2019.
“The big things that came through from the conversation was actually how do we see the benefits that the operators are getting from big data on aircraft in terms of operational resilience and how do we translate that into how are we going to manage it within the supply chains, both in logistics and MRO.”
He said the industry was still in the early phases of learning how to use big data: “We’re very much in the infancy of that process. We’re trying to learn how to work with that data, we’ve trying to learn how to actually interrogate that data and put it into some useful, meaningful intelligence for us.”
Segmentation is key to innovation
He added that usable data would come from a variety of different sources: “We’ve got the data from the aircraft, we’ve also got data from our workshops, data from the manufacturers from the airframers. It's about being able to segment and actually innovate from the data that is useful to us. So, everything from being able to predict and prevent an unscheduled disruption at the airline level and how that then translates into looking into to our intelligent workscoping with our workshops as well.”
Hoggett said there although it could be said that there was too much information, using small data sets and then testing and improving these would prove to be the starting point which would create a meaningful approach for the use of big data within logistics and supply chains. Working with repair shops and OEMs would also help them to adapt and adopt to predictive maintenance and airworthiness.
“There is a lot of data, that’s for sure, and its actually about how we take a meaningful approach to working with smaller sets at this moment in time.”
Hoggett added adopting a different way of working, towards predictive maintenance and airworthiness as well as getting the right people – technicians, mechanics and also data scientists - would be the biggest challenge for the industry in the coming 18 months.