US conglomerate GE has scooped the Manufacturing Leadership Award with its cloud-based supply chain platform for the energy sector.
Elastic Cloud – a system allowing real-time management of oil and gas materials, equipment and services – was recognised during a ceremony held earlier this month at the tenth annual Manufacturing Leadership Summit in Palm Beach, Florida.
Developed by GE’s technology arm Global Research and its oil and gas division, it is designed to monitor, manage, and optimize the sourcing, production, flow and inventory of complex oil and gas raw materials, components and final products for installation and servicing at customer sites.
“With this software platform we’ll be able to maximize, in real-time, the service level we provide to our customers, while minimizing the total delivered cost of GE products and services,” said Jody Markopoulos, vice-president of sourcing at GE Oil & Gas.
“We have heard from our customers they want better software tools to help navigate the complexities of today’s global manufacturing supply chain environment. GE’s Elastic Cloud technology delivers on this need.”
How it works:
GE’s Elastic Cloud Supply Chain Platform consists of several analytic modules to extract meaningful information from the data collected:
– One module provides end users with a “control tower” view of current inventory positions and enables users to pinpoint specific opportunities for inventory reduction.
– A second module provides materials managers and the commercial team with the ability to identify similar finished goods that are well positioned for customer replenishment by automatically identifying attributes (e.g. horsepower, voltage, etc.). This enables the commercial team to quickly find local inventory, reducing manufacturing and transportation costs.
– A third module enables end users to monitor, manage and optimize inventory relative to contractual agreements with large customers by pooling inventory by product attributes.
– A fourth module enables regional material managers to receive real-time decision support for determining the proper policy for replenishment and re-stocking of spare parts.
The outputs from these analytic modules are presented in web-based user interfaces and integrated into a cloud-enabled and secure software platform accessible to artificial lift users.