As asset-intensive companies continue to look for ways to differentiate themselves in the market, many are investigating the advantages of intelligent asset management. The basic idea of intelligent asset management is to use intelligent technologies – such as the Internet of Things (IoT), machine learning, and augmented reality – to move from traditional, reactive processes to predictive and prescriptive processes.
One goal is to see what’s coming before it happens – and to take action accordingly. This is the predictive maintenance model – which says that it’s cheaper and less disruptive to do maintenance ahead of time than to do repair work after assets break down.
Another goal is customer understanding and engagement. Companies that can track how customers use their assets are able to pick up signals that make it possible to serve them as trusted business partners engaged in their success. Intelligent asset management can bring companies into closer contact with their customers – and as a result, these companies can deliver better customer experiences.
Expectations for intelligent asset management systems
Making the move to intelligent asset management requires more than the intelligent technologies themselves. What’s needed is an end-to-end intelligent asset management system. Some requirements include the following.
Connectivity – with intelligent sensors
Critical to any system, of course, are the assets themselves. For asset management in the real-time digital economy, these assets need to be connected and intelligent. This means they need sensors capable of delivering real-time maintenance and performance data to home base where it can be acted upon.
Visibility – in real time
Connected assets, in turn, yield real-time visibility and insight into asset conditions, productivity, and efficiency. Only with this visibility into equipment information can organizations gain full situational awareness of assets in the field.
Accountability – a single source of truth
Comprehensive visibility of this sort can only be achieved with a common set of data that spans operations and maintenance. A single source of truth for all relevant asset information can help drive technician productivity in the field.
Accessibility – via mobile devices
Technicians, for example, should be able to access asset data from their mobile devices in real time in order to address issues and prevent asset failure. Real-time alerts, work requests, and work approvals via mobile devices are important, too.
Agility – cloud deployment
Because things constantly change and new opportunities arise, asset management teams need to be agile. This makes cloud deployment for intelligent asset management critical. Running in the cloud, teams can take their eye off of the day-to-day IT infrastructure duties that pull IT people away from higher value tasks. The cloud also delivers the scalability on demand required to ramp up and meet customers’ needs.
Collaboration – an asset intelligence network
More advanced scenarios for intelligent asset management include building a network of intelligent assets. By interconnecting deployed assets in such a network, organizations can collect and track equipment information across asset deployments to pull in a larger set of data from which to drive analysis and insight.
Digitization – digital-twin technology
A digital twin is a live digital representation of a physical asset. Playing a critical role in enabling an asset intelligence network, digital-twin technology acts as a common point of reference for the asset from inception, design, engineering, production, and end-of-life management – allowing teams to collaborate based on a shared understanding of the asset. This can help drive product improvements while enhancing the customer experience with the asset as well.
New whitepaper by Arc Advisory Group
The ARC Advisory Group has recently released a white paper: “Intelligent Asset Management – A Critical Differentiator for Today’s Maintenance and Operations Organizations.”
Written for organizations considering intelligent asset management systems, this paper touches on some of the topics discussed here. For a deeper dive, access the paper here.