Case study : Rolls-Royce
DIGITAL TRANSFORMATION
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Increasingly we ’ re seeing the application of AI and machine learning to predictive maintenance , opening up new possibilities for keeping things in good repair . For instance , instead of the rigorous testing needed to produce information about when a machine is about to fail , data can be gathered over the lifetime and fed into models that learn what the limits are .
It ’ s here that IoT comes into its own , as Przemek Tomczak , SVP IoT and Utilities , Kx Systems , explains . “ Shifting data to a central processing resource - such as the cloud - for analysis can cause problems with latency , as effective predictive maintenance requires analytics to be performed at speed , on both historic and real-time data . It ’ s often preferable therefore for analytics to be performed at the edge .”
In its Predictive Maintenance 4.0 report , PwC identified four successive levels of predictive maintenance maturity , successively involving better usage of data . “ Visual inspections represent level 1 in this framework ; instrument inspections and realtime condition monitoring are associated with levels 2 and 3 . At level 4 big data analytics starts to drive decision-making . This is where the digital revolution meets maintenance . This level involves applying the power of machine learning techniques to identify meaningful patterns in vast amounts of data and generate new , actionable insights for improving asset availability .”
The importance of using previously untapped data was emphasised by Roman Gaida , Department Head of CNC Mechatronics Division EMEA at Mitsubishi Electric , who said : “ We found we could use data for predictive maintenance or stock estimation . We worked together with EY and said [...]: ‘ We have the knowledge and experience , you know how to create new designs and processes ’.” That assistance resulted in new supply chain , repair and ordering systems , which Gaida estimated have resulted in 20-30 % efficiency increases .
Case study : Rolls-Royce
According to the Royal Academy of Engineering , “ The monitoring of aircraft engines has allowed Rolls- Royce to develop new services around its products , improve reliability , predict when maintenance interventions are needed , and improve long-term business forecasting . As a result , reliability across the fleet of engines has increased by 73 % over a decade .” technologymagazine . com 55