WASHINGTON, Sept. 18, 2017 /PRNewswire/ -- ANALYTICS EXPERIENCE -- Asset-intensive industries like manufacturing, energy, and transportation rely on safe and efficient operation of their equipment to generate healthy profits. For example, rail companies lose a lot of money when trains operate inconsistently and outside their optimum fuel efficiency range. GE Transportation is doing something about it by integrating SAS to decipher locomotive Internet of Things (IoT) data and uncover use patterns that keep trains on track.
"GE Transportation's locomotives are equipped with edge devices that manage hundreds of data elements per second to optimize locomotive operation," said Garret Fitzgerald, General Manager of Transport Intelligence at GE Transportation. "We use SAS® Event Stream Processing in our Predix-based EdgeLINC offering to enable our customers with analytical insights on their data in real time. Although we're in the integration phase of this project, the software has been easy to implement and use."
GE Transportation leverages SAS® Event Stream Processing powered by the SAS Platform and its SAS® Viya™ capabilities. The SAS software will be integrated with Predix Machine and Predix Edge Manager, deployed on equipment and in back offices. The combined solution helps enterprises gain real-time insights and drive improved outcomes by harnessing the power of streaming edge analytics running on board connected locomotives. SAS Event Stream Processing can be scaled, embedded and deployed across an enterprise, from small, constrained devices that sit at the network's edge, to cloud data centers. Its performance and ease of adoption provide organizations the flexibility to adapt to evolving challenges. GE Transportation leads the way in this industry with an initial rollout plan of more than 1,000 North American locomotives.
"In the IoT era, data is the fuel and analytics is the engine that drives value and tangible outcomes," said Randy Guard, SAS Executive Vice President and Chief Marketing Officer. "GE Transportation sought to develop an intelligent network to increase the value of its investment in connected IoT assets. They understand the need for analytics close to the edge, directly on the locomotives. With SAS Event Stream Processing, GE Transportation will benefit from a unified analytics environment and the ability for data scientists to code in the programming language they prefer to drive valuable customer outcomes faster."
Garret Fitzgerald will discuss GE Transportation's use of SAS in more detail with Randy Guard during an Analytics Experience session on Wednesday, Sept. 20, from 9:00 to 9:30 a.m. Eastern Time.
Today's announcement was made at the Analytics Experience conference in Washington, DC, a business technology conference presented by SAS that brings together more than 10,000 attendees on-site and online to share ideas on critical business issues.
About GE Transportation
At GE Transportation, we are in the business of realizing potential. We are a global technology leader and supplier of equipment, services and solutions to the rail, mining, marine, stationary power and drilling industries. Our innovations help customers deliver goods and services with greater speed and savings using our advanced manufacturing techniques and connected machines. Our digital solutions, which provide data-driven insights to improve efficiency, utilize Predix – GE's cloud-based operating system for the Industrial Internet. EdgeLINC is GE Transportation's Predix-based software solution for Industrial IoT device management and data optimization.
About SAS
SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 83,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®.
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2017 SAS Institute Inc. All rights reserved.
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