Organizations frequently implement a maintenance strategy for their fleets of vehicles using a combination of time and usage based maintenance schedules. While effective as a whole, time and usage based schedules do not take into account driving patterns, environmental factors, and sensors currently deployed within the vehicle measuring crank voltage, ignition voltage, and acceleration, all of which have a significant influence on the overall health of the vehicle.In a typical fleet, a large percentage of road calls are related to electrical failure, with battery failure being a common cause. Battery failures result in unmet service agreement levels and costly re-adjustment of scheduled to provide replacement vehicles. To reduce the impact of unplanned maintenance, the transportation logistics company was interested in a trial of C3 Vehicle Fleet Analytics.

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.

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.

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.

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%.

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.

To understand their complex global energy consumption and emissions footprint, Cisco needed a software solution to help them manage disparate energy- and emissions-related data inputs across their enterprise, integrate and analyze their sustainability and energy metrics, embark upon energy and emissions mitigation projects, and report results publicly. Cisco also needed to perform detailed interval analysis of their high energy-usage facilities.

Global energy leader ENGIE is implementing an ambitious digital transformation strategy that is vital to the Fortune Global 500 company’s plan to confront the major challenges posed by climate change and promote people’s access to reliable, innovative, socially responsible, low carbon, and decentralized energy. To do this, ENGIE plans to invest €1.5 billion in new businesses and digital over the next three years.

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.

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.

One of Europe’s largest manufacturing companies recognized the need for asset digital twins to improve service-level agreements (SLAs) for its installed base. However, maintaining accurate digital bills of materials (BOMs) in systems-of-record was a challenging task.

The building systems division of a Fortune 500 manufacturer conducted chiller maintenance reactively, leading to business disruptions and costly emergency repairs.

A large manufacturer of high-performance semiconductors was experiencing lower than expected overall yield in some of its most complex products.

Load and cluster sensor data for use in a predictive modelTrain a machine learning model to predict chiller failureDemonstrate speed of development and deployment by completing project in < 1 week

To improve the management of a diverse portfolio of more than 500 facilities worldwide, from typical office buildings to very energy intensive labs and data centers, this Fortune 100 technology company implemented the C3 AI Energy Management application on Amazon Web Services. With such a disparate portfolio, the company needed a software solution to manage energy and greenhouse gas (GHG) emissions, integrate and analyze sustainability and energy metrics, and report results from energy and emissions mitigation projects for its annual sustainability report and the Carbon Disclosure Project.

One of the largest banks across Asia, Africa, and the Middle East manages a complex commercial lending process that requires assessing the credit worthiness of thousands of businesses spread across multiple countries and sectors. The average time-to-decision is measured in weeks.

A global agribusiness and food manufacturer faced challenges with highly variable demand from their only customer, resulting in gaps in their weekly demand forecast. They struggled to modify demand forecasts and production schedules in a timely manner when sales orders deviated from the forecast.

The global HealthTech company faces challenges in obtaining critical business insights due to a complex IT landscape with supply chain data stored across disparate ERP systems. This hampers their ability to prioritize product lines, identify inventory issues, and optimize inventory allocation.

ENGIE, the largest power producer in the world, wanted to undergo a digital transformation and implement a platform for enterprise-wide digital transformation and IoT excellence.

A global manufacturer of aircraft engines, avionics, and other aviation products maintains a complex supply chain with significant costs of maintaining inventory.

Centrifuge failures causing production delays and lost revenue