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Beyond the Visual

Aside from a virtual replica of energy facilities, Kognitwin Energy offers easy access to dynamic monitoring, simulation, and high-quality predictions in real time.

Based on over 35 years of physics based models expertise, Kongsberg delivers the innovative Hybrid ML technology to the market, combining data science with advanced knowledge about the physical world. As a result, operators take advantage of fast, accurate, and explainable predictions for production optimization, automation, and condition monitoring.

A portfolio of services to address your needs

When the subject of Digital Twin comes up, the first image that may come to your mind is a 3D replica or a virtual model of components and assets. However, visualization tools represent just a limited part of a wider range of functionalities that Kognitwin Energy can provide.

Kognitwin Energy, Kongsberg’s Dynamic Digital Twin, offers a complete portfolio of services that can be customized according to the customer needs, going beyond the visuals to represent the true behavior of your asset.

From visualization to autonomous operations, Kognitwin Energy enables you to unlock value in different levels:

Actual State

  • Asset data and transactional data: Offering a digital twin for information and documentation.
  • Real time data: Enabling the measurement and observation of the current status of the asset.

Modelled State

  • Simulated data: Allowing for accurate hypothetical scenarios as well as unlimited training data for machine learning models.
  • Physical and mathematical models: Enabling a digital twin for planning, operation, and maintenance through the lenses of models.

Predicted State

  • Data driven ML (Machine Learning) models: Adding real time optimization capabilities verified by accurate physical models and presented to the end-users out in the field. Thereby, facilitating improved efficiency across processes.
  • Automation Systems: Enabling higher levels of autonomy and closing the loop.

The combination of these three dimensions is powerful and supports a range of use cases with high business value.

This is Kognitwin Energy

Beyond being a virtual replica of your industrial facility, Kognitwin Energy, our dynamic digital twin delivers a rich framework for advanced digitalization and analytics, including a range of solutions that can be customized to attend your needs.

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Data science and advanced knowledge about the physical world combined into Hybrid ML

Analytics and physic simulators have been used for many years in the O&G (Oil & Gas) industry providing robust and accurate results, however, the downside  of these solutions are that they used to struggle with long processing times, especially, for dynamic applications.

Given the limitation, a shift in the methods towards data-driven algorithms started taking place.

While data-driven modeling presents some clear advantages, being quick to develop and run, it also has drawbacks on the proof of accuracy, data quality, and interpretation sides, which make them difficult to adopt in the asset-heavy industry.

We now see possibilities to use digital solutions more efficiently within the industrial market.

Hybrid ML (Machine Learning) answers this challenge, combining the strengths of both physical and data-driven models in one solution.

As a category of machine learning, Hybrid ML is defined as an approach to data-driven models enhanced & constrained using knowledge about the physical world through high fidelity simulators.

With Kognitwin you can configure, orchestrate and run Hybrid ML models that use data-driven analytics like neural networks combined with physical models to provide fast and accurate predictions for production optimization, predictive maintenance, and situational awareness.

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  • Artificial Intelligence

    Artificial Intelligence (AI) refers to computer systems that are designed to think and perform actions like humans. The application areas for AI is broad and can range from simple game bots, following some predefined rules (such as the ghosts in Pacman), to more advanced language translation models (such as google translate).

  • Machine Learining

    Machine learning (ML) is an application of AI and a category of algorithms that allow models to become more accurate in predicting outcomes without being explicitly programmed. By finding statistical relationships in the data, the models can find good predictors despite the programmer not knowing in advance what these will be.  

  • Deep Learning

    Deep Learning is a part of a broader family of machine learning methods. These are often used for modern image and text analysis as the relationships in the underlying data are extremely hard to define upfront. By using a vast amount of data and computing resources, these relationships can be learned.  

Combining the best of both worlds with Hybrid ML

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Test What-if scenarios and always be one step ahead

In industrial operations, decisions with various levels of complexity need to be taken every day.  Outcomes of these decisions can result in a negative impact for the business, that in many cases are known just after the action is executed. And that is too late.

The teams working on onshore and offshore assets might wonder:        

  • What if I change the parameters of this equipment?
  • What if I schedule this maintenance for next week instead of today?
  • What if I adjust the pressure?

What if you could test scenarios before performing?

The combination of simulators, physical, and data-driven models offers the opportunity to test different hypothetical scenarios, predict their impact, compare options, and make accurate decisions. It means improved performance and productivity, increased safety, and energy savings for energy operations.

  • USE CASE: The O&G industry aims to reduce its large consumption of energy and reduce carbon emissions. Combining simulators and Hybrid ML, Kognitwin Energy can help you to test configurations before executing actions, thereby, avoiding risks and ensuring production optimization.  LEARN MORE

  • USE CASE: Shutdowns and equipment deterioration are costly for the business. With simulators and Hybrid ML, Kognitwin Energy can help you to predict issues in advance and operate more efficiently.  LEARN MORE

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Why choose Kongsberg Digital

With 200 years of determination, KONGSBERG has a long and proud history. Through our foresight and ability to adapt, we have survived through changing times, always boosting innovation and pushing new technologies to better serve the market.

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