AI4EU is a European Union Artificial Intelligence project which aims to bring together the AI community and facilitate knowledge transfer from research to business application. It provides an experiments platform that promotes the sharing and deployment of AI models. In 2021, Viking Analytics has been selected by AI4EU as a…

The Industrial Internet of Things (IIoT) market is in the early stages of a growth curve comparable to the evolution of the mobile telephony, especially when it comes to IIoT vibration sensors. In this scenario, is the current business model of keeping systems closed compatible with the future of IIoT…

Industrial Artificial Intelligence (IAI) has one of the greatest potentials to affect the way companies manage their maintenance practices. Letting Machine Learning (ML) and algorithms take more responsibility can lead to more productive work routine and less unplanned stops and the high costs associated with it. …

Detecting and monitoring operational modes in a machine is a very effective way of getting a precise view of the asset’s health conditions. In a machine, different operational modes can reflect different usages, a production process, an on-off state, or a developing failure. But besides reflecting the overall state of…

Viking Analytics was one of the winners of the 2020 edition of the ABB Electrification Virtual Startup Challenge, that invited startups to compete in a ten-day challenge to create safer, smarter, and more sustainable solutions in the electrical energy sector. In the joint project that followed the competition, Viking Analytics…

One of the fundamentals of condition monitoring is being able to trust the data you get from your sensors. …

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…

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…

By Sergio Martin-del-Campo, Data Scientist at Viking Analytics. Even companies that are playing in the advanced league of the condition monitoring game may face the challenge of knowing which machines need to be prioritized for maintenance. …