2021 – Viking Analytics

Maintenance companies and the next wave of industrial digitalization

With IIoT democratizing asset and process information for remote condition monitoring, the next grand battle in the PdM market will be between OEMs and maintenance companies.  The maintenance field has been greatly impacted by digitalization. As data collection and analysis capacities increased, companies were able to move from reactively performing maintenance in their equipment to

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Science Behind Industry 4.0: The Origins of Bayesian Statistics

Bayesian methods have become widely used in machine learning and pattern recognition. Talking simplistically, traditional – or ‘frequentist’, statistics see probability as the limit of relative frequencies of events as the number of trials increases, assuming a fixed set of distribution parameters. Bayesian statistics, on the other hand, is more concerned with adapting a model’s

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Science behind Industry 4.0: Array programming with NumPy

As part of predictive maintenance techniques, condition monitoring is used to detect anomalies and predict machinery’s health in real-time. Sensor data is used to verify whether a component failure is likely. Some failure occurs gradually and can be prevented by routine inspections and examinations. In contrast, other types of failures are more complicated to forecast. 

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Using Machine Learning to identify operational modes in rotating equipment

Vibration monitoring is key to performing condition monitoring-based maintenance in rotating equipment such as engines, compressors, turbines, pumps, generators, blowers, and gearboxes. However, periodic route-based vibration monitoring programs are not enough to prevent breakdowns, as they normally offer a narrower view of the machines’ conditions. Adding Machine Learning algorithms to this process makes it scalable,

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Times they are a-changin’ in predictive maintenance

Predictive maintenance, despite its measurable results and successes, has been suffering from lack of scalability. Models designed and trained for a given machine with a particular set of sensors often had to be retrained before being used with other similar machines. In addition, the quantity and variety of machines in a factory makes developing, training,

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Viking Analytics enters frame agreement with ABB

Viking Analytics, a Swedish startup in the field of advanced analytics for predictive operations, has signed a frame agreement with ABB. The scope of the agreement is the development of data-powered monitoring of strategic assets and marks a new stage in the collaboration between the companies following the ABB Electrification Virtual Startup Challenge 2020. In

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Viking Analytics and pour-tech AB sign contract to provide AI operators to iron foundries

Viking Analytics, a Swedish startup in advanced analytics solutions for predictive operations, and pour-tech AB, specialized in automatic pouring systems, announced a partnership to offer AI operators to iron foundries. The solution, named EASYpour, uses data analytics and machine learning algorithms developed by Viking Analytics to automatically adjust the pouring process, improving product quality, enabling

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