Industry Trends: APM — Poster Child for IIoT ROI

By Dan Miklovic, Principal Analyst, LNS Research

With bold market-size predictions ranging from $20B to $50B by 2020, it’s perhaps not surprising that the Internet of Things (IoT) is one of the most-talked-about technology topics these days. Carrying the potential promise of the ability to connect every device on earth, it seems, the IoT and, by extension, the Industrial Internet (IIoT) will radically transform both our personal and professional lives. Yet LNS Research survey data shows that in manufacturing and asset-intensive industries, the IIoT has not been broadly deployed and future plans are still being discussed.

So how do we get from a situation where businesses are still trying to figure out what to do with IIoT to the huge market numbers pundits are predicting in the next five years? Fortunately, there are many examples of asset-performance management (APM) helping lead the way in successful IIoT projects.

APM has proven largely to be the exception to our overall data in that today there are numerous case studies focusing on the use of IIoT-sourced data to improve asset and business performance and deliver measurable return on investment (ROI)—all of them APM-centric. At virtually every user-group meeting or vendor symposium our analysts have attended over the last six months, end-users have shared compelling accounts of how they are leveraging IIoT data and associated analytics to better understand asset performance and, in turn, improve equipment reliability, lower maintenance costs, and even reduce energy consumption.

One such example was presented at the Infor User Group meeting by a wastewater utility that used on-machine sensing to detect pump cavitation. The eventual solution was to lower the pump in the sump—which, in addition to solving the cavitation problem, saved considerable energy.

At the GE Intelligent Platforms Conference, Delta Airlines presented a case study on how it has used IIoT-sourced data to better manage maintenance on its aircraft engines and avoid downtime. That translated immediately into fewer delayed flights and, accordingly, improved revenue because passengers weren’t seeking alternative carriers due to delays. Passengers are also likely to factor on-time performance into future airline decisions, further demonstrating the positive effects improved data and analytics can deliver as they trickle from immediate performance and efficiency to heightened brand reputation and customer loyalty.

Stories like these have become a common and recognizable thread at various industry events—and all relate to how actual equipment-performance data, delivered via the IIoT, is helping businesses reduce downtime, improve performance, and ultimately increase profitability. This is not surprising, considering the foundational role manufacturing/production assets play in the success of a business.

One of the best ways to improve asset performance is through condition-based maintenance (CBM)—a form of predictive maintenance that leverages extensive data acquisition. As readers of this magazine know, CBM is most effective when driven by data collected from the machinery in real time, rather than hours, days or weeks after the fact from samples taken offline in a batch mode. With the growing power and prevalence of analytic tools, the ability to avoid machine degradation pays back in three ways:

1. More on-target quality
2. Less downtime, equating to better capital utilization
3. Lower maintenance cost (i.e., catching failures before they become catastrophic, thereby reducing repair costs and extending equipment life)

For all of these reasons, APM has become the poster child for the IIoT—one that shows how data collected via the Industrial Internet can truly drive return on investment. We expect other areas within manufacturing enterprises are taking note, and that they will soon roll out their own use cases to push the frontier of the IIoT toward the juggernaut analysts envision. MT

dan.miklovic@lnsresearch.com