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 top three most talked about tech topics these days. Carrying the potential promise of the ability to connect every device on earth, it seems, IoT is going to radically transform both our personal and professional lives. Yet LNS Research survey data shows that in manufacturing and asset intensive industries, IoT 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 IoT to the huge market numbers pundits are predicting in the next five years? Fortunately, there are many examples of success stories within Asset Performance Management (APM) leading the way in IoT projects today.
APM: The Bright Spot in the Data
APM has proven largely to be the exception to overall LNS Research data in that there are numerous case studies today that all focus on using IoT sourced data to improve asset performance, business performance, and deliver measurable ROI: all APM centric. At virtually every user group meeting or vendor symposium we've attended over the last six months, end users have delivered compelling case studies on how they are using IoT data to improve asset reliability, lower maintenance costs, and even save energy by leveraging analytics to better understand asset performance.
One such example was presented at the Infor user group meeting by a wastewater utility that used on-machine sensing to detect pump cavitation, a maintenance issue. The eventual solution was to lower the pump in the sump, which not only solved the cavitation issue, but ended up saving considerable energy as well.
At the GE Intelligent Platforms Conference Delta Airlines presented a case study of how it has used IoT sourced data to better manage maintenance on its aircraft engines and avoid downtime, translating immediately into fewer delayed flights and, consequently, to improved revenue, as passengers don’t seek 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.
These stories have become a common and recognizable thread at events, ranging from dairies, to mining companies, to utilities, and all relate to how actual equipment performance data, delivered via IoT, is helping each respective business reduce downtime, improve performance, and ultimately increase profitability. And this is not surprising, considering the foundational role manufacturing/production assets have 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 leveraging extensive data acquisition. And CBM is most effective when driven by data collected from the machinery in real time, rather than hours, days, or even 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:
- Better performance means more on-target quality
- Better performance means less downtime, equating to better capital utilization
- Better performance results in lower maintenance cost, 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 IoT, showing how data collected via the IoT can truly drive ROI, and we expect other areas within manufacturing businesses are taking note, soon to roll out their own use cases to push the frontier of IoT ever forward toward the juggernaut analysts envision.
Categories: Enterprise Asset Management (EAM)