News Analysis

AI and Asset Intelligence

Imagine a marine company saving almost a half-million dollars in fuel per vessel annually by leveraging AI (artificial intelligence); consider the effect a savings of $1.5 million per ship could have on a cruise line operator thanks to reduced fuel consumption, and ponder the impact data and AI-enabled decisionmaking could have on a tugboat operator looking to catch engine, fuel pump, and other equipment issues before they affect performance. Two companies will integrate their IoT (Internet of Things) offerings to enable more success stories like these early, real-life wins.

According to OSIsoft, a provider of operational intelligence, shipping companies need access to data more than ever before, because they must optimize their operations in order to stay afloat and keep up with the competition and the changing times. Since fuel costs can make up 70% of a vessel’s lifetime cost, the company says reducing consumption by just a few percentage points can equal an annual savings of millions of dollars. In addition, changing regulations focused on safety and protecting the environment will require shipping and port operations to pay close attention to the content of fuel and other emissions. These sorts of operational “fine tunings” can be accomplished with the help of IoT and data-analytics technologies that offer decision-enhancing information and operational visibility.

OSIsoft, along with Caterpillar Marine Asset Intelligence, a provider of digital services and solutions, recently announced Caterpillar has integrated OSIsoft’s data-management system into its Cat Asset Intelligence platform, a suite of subscription-based AI services for analyzing vessel fuel consumption, equipment health, safety and environmental regulations, and other critical operations in realtime. OSIsoft’s Connected Services comprise of a selected set of cloud-based services that enable hardware manufacturers, software developers, and service providers to integrate the company’s PI System into their offerings. The PI System transforms data streams into realtime insights that can be used to improve efficiencies or benefit organizations in a host of different ways.

David Shannon, business development manager, Caterpillar Marine Asset Intelligence says, “We needed a partner to scale at quality and to feed data into analytics and that’s OSIsoft.”

He adds that from a mathematical standpoint and understanding parametric relationships OSIsoft provides the skillset and coupled with CAT’s subject-matter expertise it now has the ability to see something moving out of machine state and act on these prognostics instead of reactive situations.

AI is a fast-growing facet of the IoT and the IIoT (industrial IoT), and the OSIsoft/Caterpillar integration is just one example of how it can be leveraged to impact the bottomline of asset-intensive businesses. Matt Miller, transportation industry principal at OSIsoft, says the company is supporting many AI partners, each with their own unique approach. “With such a broad array of tools, techniques, and approaches, there doesn’t seem to be one solution that fits a vast majority of use cases,” Miller says. “The best ones are applicable to many asset types and cases, which necessitates they be unbound to the data sets, which the customer wants to own anyway. To protect their IP, they are moving to cloud services running on data sets in either public or private cloud environments. As more OEMs (original-equipment manufacturers) get in the game, it will make this even more complex, as they will have the design and manufacturing and operating model understanding to add to the AI mix.”

OSIsoft in particular is focused on delivering quality, contextual data and capturing AI predictive analytics so that operations can use them to build knowledge and achieve higher performance across all their assets. As the market matures, Miller says the space can expect to see some consolidation in the market, along with a split of tools designed for data scientists and those designed for other types of knowledge workers.

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By |2018-09-25T13:40:46+00:009/25/2018|

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