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Large Oil Producer Leverages Advanced Analytics Platform - C3 IoT Industrial IoT Case Study
Large Oil Producer Leverages Advanced Analytics Platform
Approximately 17,000 wells in the customer's portfolio have beam pump artificial lift technology. While beam pump technology is relatively inexpensive compared to other artificial lift technology, beam pumps fail frequently, at rates ranging from 66% to 95% per year. Unexpected failures result in weeks of lost production, emergency maintenance expenses, and costly equipment replacements.
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Driving Network Efficiency and Fraud Detection Efforts - C3 IoT Industrial IoT Case Study
Driving Network Efficiency and Fraud Detection Efforts
Baltimore Gas and Electric Company (BGE) wanted to optimize the deployment and ongoing health of its advanced metering infrastructure (AMI) network and identify and reduce unbilled energy usage. BGE wanted a solution to deliver an annual economic benefit of $20 million.
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Predictive Maintenance for Building Equipment  - C3 IoT Industrial IoT Case Study
Predictive Maintenance for Building Equipment
Unexpected failures of building equipment can result in significant problems for facility operators. For example, refrigeration system downtimes result in expensive loss of perishables for retailers, or drugs for pharmacies. HVAC system downtimes drive need for emergency maintenance activities, and result in reduced customer satisfaction.
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Predicting, Diagnosing and Reducing Equipment Failures - C3 IoT Industrial IoT Case Study
Predicting, Diagnosing and Reducing Equipment Failures
One of Europe’s largest integrated electric power companies was looking for analytics solutions to reliably forecast equipment failure and improve condition-based maintenance for its coal-fired power plant. With a diverse array of coal, oil, and gas/CCGT power plants, the utility’s more than 50GW worldwide generating portfolio has been under pressure to streamline global operations and reduce generating costs (both CapEx and operations /maintenance O&M expenses) by 7-10%.
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Reducing Energy Costs Across Pella’s Manufacturing Plants - C3 IoT Industrial IoT Case Study
Reducing Energy Costs Across Pella’s Manufacturing Plants
Pella’s commitment to continually improve its processes for its team members and the environment has led the company to seek innovative technologies that advance overall productivity and the quality of its manufacturing operations.
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Largest Production Deployment of AI and IoT Applications - C3 IoT Industrial IoT Case Study
Largest Production Deployment of AI and IoT Applications
To increase efficiency, develop new services, and spread a digital culture across the organization, Enel is executing an enterprise-wide digitalization strategy. Central to achieving the Fortune 100 company’s goals is the large-scale deployment of the C3 AI Suite and applications. Enel operates the world’s largest enterprise IoT system with 20 million smart meters across Italy and Spain.
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Enterprise Data Analytics Platform and AMI Operations - C3 IoT Industrial IoT Case Study
Enterprise Data Analytics Platform and AMI Operations
In tandem with its 6 year-long smart meter rollout plan, Con Edison sought to implement Advanced Metering Infrastructure (AMI) operations on top of a comprehensive enterprise data analytics platform for improved operational insight and customer service for its base of more than four million customers. In order to improve customer service and operations across its region, one of the largest integrated utilities in the United States has rolled out the C3 AI Suite and C3 AMI Operations application on AWS. Con Edison’s project objectives were to deliver on the utility’s commitments for presenting customer data, establish AMI operations across 5 million smart meters to ensure operational health, and build a federated data image platform for analytic capabilities. The utility’s smart meter deployment will generate between 100 terabytes and 1 petabyte of data per year, so choosing a platform that could scale and continue to perform analytics on an ever-larger data set was vital.
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