Read more about the acquisition in our article.
i4SEE provides you with direct access to a team of experienced professionals, using best-in-class software to analyse and optimize your fleet. We work with you to enable a transition to predictive operations and maintenance.
There is a gap between recommendations derived from data analytics and the actions being carried out on the assets. This gap is between departments within companies, but also between the asset owner, operator and OEM. Adding more tools or reports to the mix has the risk of widening rather than shrinking this gap. We are finely attuned to how our customers are working and how they would like to work better. We provide practical guidance and advice to help our customers minimize this gap whether they have 100 MW or 1 GW.
For owners and operators of renewable energy portfolios wishing to maximise the production of their assets, but faced with the pressures of high costs, risk and workload, i4SEE provides an optimization service that helps to transform existing operational data into increased financial returns.
Unlike many other providers of wind turbine data analytics, we do not create additional effort for your organization by delivering complex tools or lengthy reports. i4SEE provides you with direct access to a team of experienced professionals, using best-in-class software to analyse and optimize your fleet. We work with you to enable a transition to predictive operations and maintenance.
A revolution is now on the horizon. Recent technical innovations provide the framework that is needed for a more complete implementation of predictive maintenance.
Analysis of operational data and service documentation from large numbers of turbines has demonstrated significant potential to increase the power performance of individual turbines, reduce overall downtime and reduce O&M costs through the selective introduction of a range of analytical and predictive methods.
However, this potential is only fully realised if the results of such analysis are properly integrated into operational processes. The main obstacles to achieving the transition to a methodology such as predictive maintenance appear to be of an organisational nature, rather than technical. The wind turbine service market is complex and dynamic, with turbine manufacturers, owners and independent service providers jostling for position. Responsibilities and contractual motivation appear to change faster than technology providers and change management teams can implement new solutions.
Self learning, adaptive models to simulate healthy turbine behaviour and detect faults. Rapid onboarding and learning allows brand new wind farms to be analyzed without long periods of historical data.
Full automation of the entire analytics process from data collection, data validation, analysis and reporting.
Modular software design based on a suite of individual Applications, allowing us to deliver exactly what you need.
Statistics and machine-learning combined with physics and engineering, to produce efficient but transparent models.
“If you are looking for a reliable, accurate and affordable tool for condition monitoring of your wind turbines, you need to check out i4SEE. They took the time to figure out our needs and goals as a company and gave us a few excellent solutions to choose from. We accomplished detecting abnormalities and small damages at the early stages, thanks to i4SEE ‘s modules such as i4SEE Heat and i4SEE GearDrive. Consequently, we are avoiding sudden failures of key components on our fleet. It is a great accomplishment considering the size, variety of turbines’ types and geographic locations of our assets. What we love most about i4SEE is that it can work accurately based on SCADA data thanks to their smart computation model and their knowledge of the wind industry. We cannot end this testimonial without mentioning the courtesy that the i4SEE team has always shown us and the quality of their customer services. We definitely recommend i4SEE to everyone we know.” Read the Case Study.
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