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? We believe sensor expansion will inevitably lead
Viking Analytics was one of the winders of the Ignite Awards 2021. In a ceremony on November 29th, the company received the Ignite B2B Engagement 2021, which recognizes startups that have met more corporations during the year. The startup’s unique AI-based predictive maintenance software has been key to addressing needs from both Swedish and international
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 the machine, Mode Identification can
One of the fundamentals of condition monitoring is being able to trust the data you get from your sensors. Normally, there is a set of checks that an IIoT installation goes through to become fully functional, like connectivity and authentication tests to ensure that the sensor is in the right operational state or, in other
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
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. For example, how can a professional responsible for the maintenance of compressors in a company realize which ones need to go to the top of priorities list?
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,
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, and maintaining models for each machine a challenge. Therefore, it‘s natural that predictive
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
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
