Skip to main content

Caterpillar Marine receives type approval DNV GL certification for Cat Asset Intelligence analytics and monitoring solution

Published by
Oilfield Technology,

Caterpillar Marine has received Type Approval certification from DNV GL for Cat® Asset Intelligence (Cat AI) software, demonstrating Caterpillar’s commitment to quality and customer focus. Caterpillar provides Cat AI advanced predictive analytics and expert advisory services to ship owners and operators, with onboard and shore based modules, which can be configured for a single vessel or an entire fleet. Cat AI is focused on increasing uptime, by predicting and avoiding failures and better maintenance planning, and decreasing operating costs, through fuel efficiency and reduced maintenance expense. With over 40 million hours of equipment analytics experience, Cat Asset Intelligence turns data into actionable information, for Cat and non-Cat equipment including diesel engines as well as non-diesel engine auxiliary equipment.

Driven by the purpose of safeguarding life, property and the environment, DNV GL enables organisations to advance the safety and sustainability of their business. A certification from DNV GL documents Caterpillar’s commitment to quality, consistency, continual improvement and customer satisfaction. Type Approval of Cat AI provides vital assurance to clients that Cat AI exceeds industry standards and guidelines.

Caterpillar Marine Asset Intelligence Technology Manager, Ken Krooner, said, "We are pleased to announce the Type Approval Certification of our software after working closely with the experts at DNV GL. DNV GL Type Approval validates Caterpillar’s commitment to quality and to our customers. The Type Approval gives further comfort to our customers of the quality of our technology and the robustness of our development and engineering processes.”

Read the article online at:

You might also like


Embed article link: (copy the HTML code below):


This article has been tagged under the following:

Oil & gas news