Energy Industry - Motor
2× Analyst Efficiency: How Mälarenergi Scaled Predictive Maintenance with AI
By cutting through data overload and automating prioritization, Mälarenergi’s team doubled their diagnostic capacity without adding headcount.
By cutting through data overload and automating prioritization, Mälarenergi’s team doubled their diagnostic capacity without adding headcount.
diagnostic capacity, without adding headcount
wireless vibration sensors deployed
machines monitored by 4 analysts
Mälarenergi, a major energy provider in Sweden, has transformed its maintenance approach by deploying over 350 pureMEMS wireless vibration sensors from MLT and pureSignal. With support from Viking Analytics’ AI platform, the team moved from manual checks to real-time, prioritized insights – saving time, reducing risk, and detecting faults earlier. In one case, AI flagged a bearing issue on a nearly new machine before failure. Now exploring technologies like the AI-driven lubrication system pureALUBE, Mälarenergi continues to set the standard for modern, data-driven maintenance.
No visibility between manual checks
pureMEMS wireless sensors (MLT/pureSignal) + Viking Analytics AI
Early bearing fault detected, more efficient workflows, scalable monitoring
One of the biggest benefits is that the technology picks up alerts well in advance. The fact that AI is continuously working, analyzing, and sorting different events to present patterns and trends saves us a lot of time.
Energy Industry - Motor
MLT and pureSignal
Combined heat and power plant, Västerås, Sweden
350+ pureMEMS wireless sensors on 100+ machines
774
Electricity and district heating, Cooling, Water and sewage
One of Mälarenergi's first wins was an early-stage bearing issue on an almost new machine. The PDF breaks down the alert step by step.
The whole story in one PDF: what happened, the technical deep dive with MultiViz screenshots, and the results.
Bring your own use case and we'll walk you through it.
MultiViz - AI powered vibration analysis-conditioning monitoring for smarter predictive maintenance.
