VIKING ANALYTICS AB | SÖDRA CELL

Exciting AI-driven vibration monitoring unveiled at Swedish Maintenance Day Event

David Svahn from Södra Cell and Stefan Lagerqvist highlighted the transformative power of AI and smart monitoring technologies in optimizing maintenance strategies
© Cision

David Svahn from Södra Cell and Stefan Lagerqvist highlighted the transformative power of AI and smart monitoring technologies in optimizing maintenance strategies
© Cision
The Maintenance Days, organized by the National Organization for Swedish Maintenance, gathered professionals from diverse sectors, including the engineering, process, mining, and steel industries. The event featured a carefully curated lineup of speakers representing academia, industry, and security firms, focusing on the latest innovations and strategies in maintenance.

Maria Stockefors, CEO of Swedish Maintenance, opened the event with a call to action: “The Maintenance Days are focused on networking. You who have come here have enormous competence, and we have a lot to convey to each other. Together we build a strong industry.”

She emphasized the vital role of maintenance in driving profitability through reliability: “It is important to bring out and talk about and understand the importance of maintenance. With reliability comes increased profitability. We have to see which interventions have the greatest effect, be innovative, and constantly develop skills.”

Among the presentations, one notable case study showcased by David Svahn, a vibration data engineer from Södra Cell, and Stefan Lagerqvist, COO and co-founder of Viking Analytics, highlighted the transformative power of AI and smart monitoring technologies in optimizing maintenance strategies.

 

Transition to wireless sensors

Södra Cell is moving away from traditional hand-held vibration measurement instruments in favor of wireless sensors. Currently, 3000 sensors are installed, with a goal to complete the transition by 2027–2028. These sensors offer continuous monitoring, eliminating the need for manual rounds. Despite the advances, the system generates approximately 1100 alarms weekly, handled by only two engineers. Alarm thresholds are often determined based on intuition and require frequent updates. While existing tools like data filtering offer some relief, the need for more robust solutions is evident.

 

Role of Viking Analytics and AI Tools

Viking Analytics has developed Multiviz, an AI-powered tool aimed at revolutionizing vibration analysis. Currently tested on 5% of Södra Cell’s sensors, the tool analyzes data across thousands of machines without requiring:

·Machine-specific details

·Pre-set manual alarm thresholds

·Machine type classifications

·Initial results reveal a significant reduction in workload, saving engineers 2–3 hours of analysis daily with just 5% coverage. Full-scale implementation could result in even greater time and cost efficiencies

 

Case Study: Predictive Maintenance in Action

David Svahn illustrated the potential of predictive maintenance through a real-world example involving a screw conveyor in a washing press. When vibration data flagged a warning, a manual inspection revealed a damaged belt. The issue was resolved during a scheduled maintenance stop, avoiding an emergency shutdown.

 

The effectiveness of the repair was subsequently validated using both Multiviz and Södra Cell’s traditional tool, CondMaster, showcasing the complementary strengths of advanced and conventional systems.

 

Benefits and Future Prospects

Smart sensors and AI tools like Multiviz allow early identification of issues, minimize manual labor, and significantly improve efficiency. While only 5% of sensors are currently integrated, the potential impact of expanding this to 100% highlights the value of digitalization and AI in industrial maintenance.

These innovations align with Södra Cell’s commitment to sustainability, operational excellence, and industry-leading practices.

www.vikinganalytics.se

Related articles:

Issue 12/2014 HANSFORD SENSORS LTD.

Vibration monitoring to boost efficiency

Introduction Cement manufacturing is one of the most aggressive of all production processes. The chemicals used to produce Portland and Masonry cement – particu­larly silicates, aluminates and...

more
Issue 10/2020 SCHAEFFLER AG

Schaeffler Optime makes condition monitoring cost-effective for all plant assets

For cost reasons, permanently installed continuous condition monitoring is typically used only for production machines that are directly process-critical. In the process manufacturing and automation...

more
Issue 5/2015 MARTIN ENGINEERING

Custom work cell to mold conveyor belt cleaners

In a move designed to deliver global product availability and consistency with the fastest possible response to customer orders, Martin Engineering from Neponset, Illinois/USA has announced the design...

more
Issue 05/2010

Garadagh Cement ensures production uptime using online Condition Monitoring System (CMS)

Garadagh Cement OJSC (Fig. 1), established in 1999 by the Swiss Holcim Group, is the only cement and clinker manufacturing company in Azerbaijan. The company covoers the majority of domestic demand...

more
Issue 7-8/2015 SIEMENS AG

Drive train condition monitoring

1 Introduction An efficient condition monitoring solution such as Siemens’ Drive Train Condition Monitoring (DTCM) is integrated into the automation system and monitors the entire drive train. The...

more