GE Intelligent Platforms (NYSE: GE) announced an Equipment Insight solution, from GE PredictivityTM that enables OEMs to securely collect data from connected machines, analyze that data, and get actionable information to people to deliver better service levels and optimize equipment performance, leading to new revenue streams and improved customer satisfaction. Powered by GEs Proficy® software and rugged RXi IPCs, the solution also allows OEMs to gain a better understanding of how customers use their machines, while helping them to optimize processes, asset performance and profitability.
GEs Equipment Insight solution takes full advantage of the Real-time Operational Intelligence (RtOI) paradigm. It combines an on-premise or private cloud server architecture with rugged Field Agents to create the first integrated solution that monitors asset health, leveraging ever-expanding industrial data sets to predict equipment failures.
Todays OEMs are being pressed to deliver higher levels of service to customers without increasing cost, said Steve Pavlosky, Solutions Ecosystem Leader for GE Intelligent Platforms. Most are looking to monitor their equipment and share asset information with their end users, but many dont have the resources to do it effectively. For some, this solution can provide a new business model that can bring them closer to their customers by providing a service the customer needs on a machine they know.
With functionality provided by GEs proven Proficy software, the Equipment Insight server collects and manages long-term fleet performance data and alarms, as well as administers user access. Based on this historical data, the Equipment Insight solution performs trend analysis of a single machine or an entire fleet. It then delivers role-specific alarms and trends to either the end user or OEM personnel via mobile device applications or a web browser. All of this is guided by an equipment asset model created by the OEM.
For TempuTech, the Equipment Insight solution is paying off quickly. By deploying the solution at one of our customers grain facilities, we are able to access and provide actionable information about the health of their system and deliver it to them in real-time so they can avoid downtime and quality issues, said Tom Herrera Sr. owner of TempuTech, Inc. Virtually centralizing unlike applications, devices and sensors via a web-based remote monitoring & diagnostic solution is improving our ability to service this account, enhancing our value to them a vendor, and reducing our overall costs-to-serve, said Adrian Merrill, Vice President of Operations of TempuTech, Inc.
The solution quickly and cost effectively transforms raw data into actionable information, maximizing operational efficiency, productivity and profitability. Alarms and overall equipment effectiveness and Key Performance Indicator (KPI) data is viewed in a single, accessible screen on your mobile device. And a customized risk index provides advanced analytics and predictive detection, allowing OEMs to contact customers before their process goes down. Costs are reduced by leveraging a small number of experts to monitor and troubleshoot an entire fleet of assets.
The Field Agent collects equipment data from nearly any brand of intelligent control device. The data is buffered to protect against network outages, encrypted and transmitted to and verified by the Equipment Insight server. An optional 3G interface provides access where end user networks or public infrastructure arent available. Setup of the solution is fast and easy, with little or no impact on customer IT functions. Configuration of several machines is also simple an equipment data model is all that is needed.
As one of the worlds largest OEMs, said Pavlosky, GE has the experience and vast installed base to harness the power of todays technological transformation elastic computing power, ubiquitous connectivity and cloud computing — and make it work for companies of any size.
Filed Under: TECHNOLOGIES + PRODUCTS, ALL INDUSTRIES, Factory automation, Industrial computers, Software
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