Dealing with big data
One of the major challenges within the downstream sector is an almost infinite number of records, documents, drawings, reports, procedures, and schedules. For any single piece or type of equipment at a facility, there can be thousands of associated pieces of critical information – and each facility can host thousands, if not tens of thousands, of pieces of equipment requiring data management for effective operation. That adds up to potentially millions of documents, schedules, records, and more that need to be brought together. Additionally, these have a certain level of ‘health’ that needs to be maintained in order to function within required specifications and remain effective across facility-wide operations.
Kognitwin provides a unified environment where all this data – from docs and drawings to real-time sensor outputs and schedules – can be collected, sorted, and displayed in a way that reduces complexity, allowing users to get the most out of the information that’s available. Data is overlayed in a single digital twin interface that unveils a new level of visualization and spatial awareness. Once data is extracted from the various data sources, it can also be delivered to Machine Learning (ML) models to derive more value and offer maintenance schedules based on real-time operating conditions. Even when a facility has low data maturity or missing data, Kognitwin can handle a variety of data scenarios and optimize these to monitor and predict operational parameters for significant savings.
In an industry that is vulnerable to fluctuating oil prices, production costs, and low margins, the need to reconfigure production for more optimal operations is a constant struggle. The ability to forecast consumption accurately and in trend with changing circumstances is a major component in optimizing everything from processing through to distribution.
Kognitwin’s integrated hybrid ML model makes it easy to monitor equipment/assets at a facility over time to evaluate baseline trends and deviations. Equipment can then be maintained based on actual performance and maintenance needs, and with features like Cumulative Work Visualization, on-site activities can be scheduled in parallel with planned maintenance to eliminate scheduling conflicts. Additionally, Kognitwin can employ data from steady-state and dynamic simulators to not only provide optimization suggestions but also predict performance to increase efficiency and reduce potential downtime.
Kognitwin functionality such as predictive maintenance aids in reducing the carbon footprint linked to operating and transportation and promotes compliance in line with emerging environmental regulations. For many refineries, sources of GHG emissions like stationary combustion units (e.g., process heaters, furnaces, boilers, etc.) can contribute up to two-thirds of all CO2 emissions generated at a facility. Understanding and benchmarking these emissions are clear directives for managing improvements.
Kognitwin’s performance monitoring and predictive maintenance features allow users to get data-driven insights into emissions and visualize the location of both predicted and actual equipment performance and maintenance priorities. The equipment tracking and supply chain automation opportunities unlocked by these features make it possible to reduce the carbon footprint of supply chain/distribution activities for greener operations.
Unplanned downtime can cost operators upwards of 49 million USD per year but with Kognitwin, downstream operators can meet the challenges of turnarounds and shutdowns head-on. Transforming turnarounds becomes easier with Kongsberg Digital’s cutting-edge digital twin solution, helping to optimize resource allocation, streamline planning, and identify risks (and build mitigation measures for these risks).
Major maintenance events like shutdowns and turnarounds pose considerable safety challenges like working in confined spaces where access to equipment is difficult and the potential for exposure to hazardous gas is escalated.
Kognitwin mitigates these risks by enabling immersive visualization online where a user can zoom in to a piece of equipment from any angle, right down to the smallest parts. With the click of a mouse, users can navigate to any linked documentation for a piece of equipment including historical records and maintenance data – all without conducting a physical site visit. Users can also add annotations and share this view to collaborate with colleagues worldwide.
Kognitwin is especially useful in the planning and testing phases of shutdowns and turnaround activities, opening a new world of possibilities for the optimization of these typically resource-intensive operational scenarios. Read more about how Kognitwin can transform your turnarounds.
Another important safety area where Kognitwin is changing the game is the training and onboarding of operators prior to turnarounds. Say for example a large replacement of personnel is required within a short timeframe. Kongitwin’s simulation capabilities can be used for digital and even remote training which helps to reduce training times for new operators. Employees are enabled to do more since roles and work tasks can be consolidated in the twin’s collaborative digital environment, and overall costs are reduced as no overtime or additional resources like extra personnel are required.
Kongsberg Digital’s (KDI) specialized digital twin solution Kognitwin can be deployed for any heavy asset from upstream to downstream. Get in touch to find out how Kognitwin can help you achieve smarter, safer, and greener operations from data through to daily operations.
Learn more about kognitwin
Imagine having access to all real-time data from the oil & gas asset in one place through a simple virtual interface.
We call it Kognitwin®.