Predictive maintenance & condition monitoring
Prescriptive analytics and the asset maintenance revolution
The latest advances in artifical intelligence, machine learning and data science is enabling the development of a new approach to maintaining and improving working processes: prescriptive analytics. Robert Golightly, senior manager of manufacturing at AspenTech, discusses the emergence of this new method
F
or decades, engineering companies have focused on how to best use data to drive business value. Forty years
ago, they began upgrading plant control systems from analogue to digital, helping facilitate the capture of data from sensors located across these plants. When stored, this data enabled the development of higher-level applications like advanced process control and optimisation, which benefitted engineers by enabling them to drive plants closer to their operating limit. Times have changed, however. Today,
engineers have found ways to achieve even greater benefits from the data capture and management process. It is now easier and more cost-effective for them to generate large
‘‘ 30
volumes of relevant data; gain access to it and then apply it to deliver operational gains across every aspect of their work – from design to troubleshooting. So, why is this? On the one hand, the
price of instrumentation is falling and the cost of connectivity to that instrumentation is coming down. On the other, the advance of technologies like edge computing and fog computing is making more data available to engineers – and the increasing ubiquity of the cloud is enabling companies to consolidate multiple silos of information and prepare it for analysis. So, engineering companies have easier
access to larger volumes of data than ever before. That, in itself, has brought them gains,
Extending warnings from hours or days
to weeks - or even months - is creating an opportunity to revolutionise how a whole organisation responds to events...
’’
allowing senior operatives to ‘get their hands dirty’ in plant data and use it both to improve working processes and drive operational, environmental and health and safety benefits. What has really changed the game, though, are the latest advances in artificial intelligence, machine learning and data science. Together, these technologies enable a new approach known as prescriptive analytics which pinpoints signatures and patterns in the data that warn the operating company of an impending outage or plant breakdown, enabling it to take remedial action in advance. The value key is the weeks or months early warning. The success of prescriptive analytics in
providing weeks of accurate warning of asset failures is enabling a new set of collaborative workflows to plan around those failures. Extending the warnings from hours or days to weeks - or even months - is creating an opportunity to revolutionise how the whole organisation responds to the event. Maintenance, operations, scheduling, supply chain and maybe even sales can all get involved to mitigate the impact. These technologies are fuelling a revolution in asset maintenance that no operating company or plant operator can afford to ignore.
October 2019 Instrumentation Monthly
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