NextEra:utilizing machine learning to increase reliability and integrate renewables into the grid
See how Royal Dutch Shell plans to use predictive maintenance to improve profitability.
Offshore wind turbines offer tremendous potential for renewable energy, but are still not as competitive as other low-carbon technologies. Iberdrola, global leader in power generation and one of the largest wind power producers, looks at machine learning solutions to decrease maintenance costs and make offshore wind more affordable.
EasyJet is struggling to keep up its operational performance, and customer satisfaction is decreasing significantly. How can machine learning help?
ThyssenKrupp’s MAX is on the rise
In the backdrop of increasing ridership and almost zero tolerance for breakdown, Singapore’s rail operator, SMRT, is turning to machine learning and predictive maintenance to manage failure.
The US Navy's antiquated maintenance system must evolve into a conditions-based system enhanced by AI.
Exploring how Shell has leveraged machine learning to adapt the era of low oil prices through predictive maintenance, optimization and safety applications
Generally, machine learning is perceived for computer technology-driven firms. This article examines the use of machine learning in an old world industry such as oil and gas.
Rolls-Royce is the current marker leader in the wide-body aircraft segment. The intense competition in the market results in manufacturers willing to sell their products without profit, but capture significant value from the MRO (maintenance, repair and overhaul) business driven by digital data. As a result, digital technologies not only transform Rolls-Royce’s product supply chain from initial concept to aircraft delivery, but also the company’s service offerings and aftermarket supply chain. Now the question is how can Rolls-Royce develop its existing workforce to be more adaptable, change-ready and digitally savvy?