Making wind a reliable source of energy depends greatly on the placement of the wind turbines used to produce electricity. Turbulence is a significant factor as it strains turbine components, making them more likely to fail. Vestas wanted to pinpoint the optimal location for wind turbines to maximize power generation and reduce energy costs.

To achieve its goal of doubling production capacity while keeping tight control of costs, major shoe manufacturer PT Chang Shin Indonesia set out to unlock greater efficiencies in its operations.

Among the many challenges that Day Kimball Hospital faced included difficulties in performing maintenance on their applications, system hardware and completing backups within an acceptable backup window. It was a challenge to find the downtime necessary to upgrade their firmware.

On a daily basis, millions of data records are generated on visitor exhibit and special event preferences and participation in conservation initiatives. Significant visitor feedback is also generated on social channels, such as Facebook, which reveal visitor likes and dislikes and other feedback on overall zoo operations. The zoo needed a lens to focus on the actionable insights that emerge from this massive amount of information.

Increasingly sophisticated malware attacks can leave healthcare providers in a vulnerable position as they confront the critical need to improve security while also keeping IT costs under control. Concord Hospital has worked hard to cultivate a reputation for clinical and patient service excellence.As an example of its progressive approach to automating health service delivery, Hospitals & Health Networks magazine has named Concord one of the United States’ “Most Wired Hospitals” for several consecutive years. In order to maintain this level of operational excellence, Concord Hospital needed a solution to save time and resources while also improving results for software licensing, patch management, asset inventory and security configuration.

Sharing secure and transparent critical network data across shareholder networks is difficult using traditional system. Furthermore, private SMEs lack access to public stock exchange networks or formalized credit structures.

Seeking to add value beyond pump efficiency, Armstrong wanted to help customers address the issue of predictive maintenance through continuous learning to improve efficiency and by sharing best practices across industries and buildings.

Mining companies have a lot of data at their disposal. Sensors are seemingly everywhere in their underground operations. But thus far it has been very hard for mining companies to capitalize on all their data because of the difficulty in making sense of it all.So what’s the most important data for mining companies? The short answer: assets. Mining is one of the most asset-intensive businesses there is. At every point in the extraction chain— drilling, cutting, crushing, screening and removing ore-bearing rock—heavy equipment is critical. And it takes a beating. When equipment breaks down, requiring unscheduled maintenance, production takes a hit, costs rise and a critical measure of capital efficiency in mining—overall equipment effectiveness (OEE)—goes down.

Daimler AG was looking for a way to maximize the number of flawlessly produced cylinder-heads at its Stuttgart factory by making targeted process adjustments. The company also wanted to increase productivity and shorten the ramp-up phase of its complex manufacturing process.

KONE already provided traditional maintenance services for its more than 400,000 building owner and facilities management customers, but it sought cloud-based analytics technology to capture and use the vast amount of data generated by its elevator and escalator equipment worldwide to transform its service offerings. “We knew that digitalization was changing the industry, and we wanted to become a forerunner, not a follower in this development,” says Markus Huuskonen, the Director of Maintenance Processes and Connected Services at KONE.

The challenge was to harvest and sift through this data, recognize the patterns that indicate a high likelihood of asset failure, identify the most urgent issues, and get the right information to its engineers with enough lead time for them to take effective action.“Before, we only used between 10 and 12 percent of the operational data we collected, which is the industry average,” comments Benn. “By the time we had searched for, collated and forwarded the right information to the right people, we might respond too late to avoid impact to operations, or have to make last-minute changes to our maintenance schedule, which reduces efficiency. Our challenge was to provide right-time, actionable, effective information proactively, rather than in a reactive or look-back assessment.”“What we wanted was a way to identify patterns in that sensor data that would give us an early warning of asset failure. We saw an opportunity to use analytics technology to extract greater value from the systems and data we already possessed, which would help us to, for example, avoid preventable failures and potentially save millions of dollars.

Simplifying maintenanceHana Financial Group had recently consolidated the infrastructure and resources of 11 of its affiliates at a local IBM data centre. However, the business was left with more than 100 service and maintenance contracts that needed to be reviewed and renewed periodically. These contracts also involved 100 separate bills that Hana Financial Group had to manage. Managing such a large volume of bills was cumbersome and sometimes resulted in late payments. The group wanted to improve efficiency and eliminate the overhead involved with managing these contracts by consolidating its heterogeneous IT systems and data storage systems under more consistent processes.