Predictive Maintenance and the US Army
Predictive Maintenance and the US Army
Let's take a look at the role IoT and predictive maintenance play in US Army operations and the lessons that can be gleaned for IIoT.
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When the government saves money, we all win. Over the last four years, the U.S. Army has avoided about $15 million per year in operational costs by paying only for the cloud services it actually consumes. Working with IBM since September of 2012, this partnership has enabled the Army to create significant operational efficiencies across its vast logistics system, Logistics Support Activity (LOGSA). When embarking on this mission back in 2012, the hope was that the cloud would provide improved coordination and efficiency of operations. It has done that and much more. But now the time has come to take another leap forward.
It was announced recently that the U.S. Army’s LOGSA awarded IBM a contract to continue providing cloud services, and also improve cybersecurity efforts and incorporate advanced analytics to better predict fleet maintenance needs.
As part of this new contract, IBM will help the Army predict vehicle maintenance failures from more than 5 billion data points of on-board IoT sensors. In addition, the Army is adopting Watson IoT services and a new Watson IoT Equipment Advisor solution that analyzes unstructured, structured and sensor data directly from military assets. Using these services, LOGSA can better understand the health of its vehicles and predict mission-critical failures. By halting failures before they happen, the Army will realize significant savings and increase efficiency.
Why Is LOGSA Critical to Operations?
LOGSA is one of the federal government’s biggest logistics systems, providing support of Army operations worldwide. It impacts every soldier, every day. LOGSA provides key intelligence around logistics, asset life cycle support, technical advice, assistance to soldiers, and provides asset visibility for timely and proactive decision-making. They are the leader when it comes to the U.S. Army’s top priority – readiness. Home to the Logistics Information Warehouse (LIW), the Army’s official storehouse for collecting, storing, organizing and delivering logistics data, it utilizes analytics tools and business intelligence solutions to acquire, manage, equip and sustain the Army’s material needs.
“Over the past four and a half years, LOGSA has benefited from the business and technical advantages of the cloud,” said LOGSA Commander Col. John D. Kuenzli. “Now, we’re moving beyond infrastructure-as-a-service and embracing both platform and software-as-a service, adopting commercial cloud capabilities to further enhance Army readiness.”
Preventing Critical Failure of Vehicles
The U.S. Army has been utilizing IBM cloud to process upward of 40 million transactions per day – more than the New York Stock Exchange. This new 33-month, $135 million contract will take that analysis up a notch. The Army will have the ability to monitor, analyze, and report on information gathered from devices and equipment and recommend maintenance procedures.
Using predictive maintenance, they will have the ability to:
- Monitor and analyze vehicle health data – both historical and real-time
- Intervene at the right time, before failure occurs
- Prioritize and optimize resources
This provides the potential to eliminate nearly 70 percent of breakdowns and reduce downtime by up to 50 percent. Having vehicles in optimal condition is critical to effective military operations and readiness.
Use Cognitive Intelligence to Understand What the Best Play Is
In addition to moving toward predictive maintenance models, the Army is taking advantage of cognitive and machine learning capabilities to provide faster insights into recommended fixes.
The IBM IoT Equipment Advisor applies cognitive methods to a wide range of unstructured data to identify data points such as equipment details (model, version, configuration, controller), equipment status/conditions, service technician notes, tests and test results, hypothesized failure, prescribed repair procedures, repair resolution, operational procedures, tooling, expertise, and evidence. It then applies this insight to provide probability-ranked guidance regarding diagnostic and resolution options or next best action recommendations to help preempt or resolve correlated failures. See Figure 1.
Figure 1. IoT Equipment Advisor pulls in data from unstructured sources to provide recommended solutions.
IBM recently completed a proof of concept that demonstrated the effectiveness of Watson cognitive computing for 10 percent of the Army’s Stryker vehicle fleet. Under this new contract, LOGSA will increase its ability to provide that predictive and prescriptive maintenance information to the Army.
March Toward the Future
Technology is ever-changing and every organization across every industry must strive to keep up the pace. To stay ahead of the competition, one must always stay one step ahead. “When Gen. Perna took command of the Army Materiel Command, he said we cannot conduct tomorrow’s operations using yesterday’s processes and procedures,” said LOGSA Commander Col. John D. Kuenzli. This has never been more true, and the U.S. Army is marching forward to the technology of the future, which revolves around predictive analytics, cognitive intelligence, and the cloud.
Published at DZone with permission of Chris O'Connor , DZone MVB. See the original article here.
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