Mariner has been fortunate to collaborate with some good people with interesting business problems. One in particular is ABT Power Management in Greensboro, NC. ABT provides solutions to its customers’ motive power problems. Motive power refers to the very expensive batteries used to power lift trucks, scissor lifts and other material handling vehicles. As it turns out, these batteries can cost more than the vehicles they power and if they’re not properly maintained, can last a fraction of the 5 years for which they’re rated. Two years ago, ABT’s CEO, CIO and COO visited us in our offices in Charlotte where Ken Fearn, CEO, shared his vision to create a technology solution that would give his customers’ batteries a “voice” so they can let us know when they need to be serviced to ensure trouble-free operation and a long life. This is how ABT’s RAAMS (Remote Automatic Asset Monitoring system) project began.
Azure IoT Finds the Signal
Working with Ken and his very bright team of technologists and engineers, Mariner captured the maintenance “rules” and devised a system to collect data from the batteries while they’re being used and while they’re being recharged. Armed with this data, we collaboratively built RAAMS to capture all of the telemetry available using Microsoft’s Azure IoT Services and then sift through the noise to find the signal. Enhanced with additional historical information gathered from the Azure-based RAAMS data warehouse, the battery data flows through Sparkling Logic’s SMARTS decision management solution where the correct decisions are made to ensure optimal battery life and performance. These decisions are communicated to the field service group who ensures the maintenance prescribed is performed.
Machine Learning + Decision Management = Agility
Ken is truly a visionary in his field. No one else has had the foresight to see the value of a predictive maintenance solution in his industry. And that value is enormous. Prior to RAAMS, ABT engineers had to pour through countless pages of data to find information requiring a response. Now Ken and his engineering staff’s proprietary knowledge of battery maintenance is embedded in his decision management engine. As maintenance needs change, he has one place to make those changes. He’s currently using Azure Machine Learning to both validate his decision logic but also to discover new decision logic. And think about this for one minute: If he finds better ways to maintain batteries, he changes the rules and immediately his customers’ batteries will benefit from the knowledge. No memos to a field service team. No training. No following up to ensure maintenance policies are being followed. Now THAT is business at the speed of thought.
Read more about ABT Power Management’s use of the Internet of Things and digital business to achieve strategic advantage in Microsoft’s IoT Blog Post.