This blog originally appeared in Industrial IoT/Industrie 4.0 Viewpoints
Core to the Industrial Internet of Things (IIoT) is enhanced connectivity of smart devices (machines, assets, products, things, physical entities, or pieces of equipment) coupled with advanced analytics. The expectation is that by applying these potentially transformative technologies, significant business transformations can be achieved.
One of the most promising areas for substantial change is asset performance management (APM).
Early results suggest that we are indeed making progress toward that end, but there’s still a long way to go. A recent ARC survey asked the question: ”In terms of IIoT, at what maturity stage would you rate your company’s asset performance management (APM) program?” Respondents could select one of the following:
- Conventional: Not smart or connected
- Instrumented: Connectable, can share data externally
- Software defined: Embedded intelligence, software tunable, enhanced data feeds
- Smart: Enhanced intelligence, actively monitored, self-optimized, used in ecosystem
- Autonomous: Real-time analytics utilized, onboard execution models, performance guarantees
In total, software defined, smart, and autonomous devices – those most suitable for IIoT implementation – accounted for more than a third of total devices.
Slightly more than 27 per cent of devices are capable of sharing data externally. According to respondents, the majority of devices are neither smart nor capable of external connectivity. I believe that for industrial operations, IIoT represents the opportunity to optimize maintenance particularly from the practice of predictive maintenance (PdM). In principle, PdM requires continuous or periodic monitoring and diagnostic capabilities to determine device health to detect device degradation with sufficient advanced warning to avoid significant deterioration of the device.
Ideally, IIoT will be an enabler of holistic asset performance management, where all devices are continuously monitored and APM becomes integrated into the fabric of the business. Realistically not all devices are obvious candidates for monitoring and/or predictive maintenance solutions.
It’s essential for owner/operators to identify the most critical devices to determine the cost of failure and root causes of device downtime.
When the cost of downtime is high, it can be easier to justify the cost of IIoT-enabled monitoring even for a relatively low-cost device. IIoT provides a compelling value proposition to help maintain production and decrease unplanned downtime. The reduction in the cost of downtime and the assurance of increased uptime in the future can be used to justify IIoT enablement for lower cost devices that have been traditionally labeled as expendable or easily replaceable.
What’s your opinion – if one third of industrial APM programs are already dealing with assets that are ‘smart’, ‘software-defined’, or ‘autonomous’, is that more or less that you would have guessed? Is it dependent on the industrial segment?