Recap: Succeeding in Predictive maintenance with Wärtsilä and Silo.AI

We hosted a breakfast seminar on predictive maintenance, where we had the pleasure to hear out Wärtsilä's journey in building predictive maintenance for their operations. We wanted to bring out concrete showcases from the industry and tell our experience in applying machine learning to predictive maintenance. This post is a recap of the key learnings from the event.

We were happy to have Robert Wendelin, Director Digital Portfolio Management and Patrik Strand, Senior Digital Product Manager, Digital Development Asset Management from Wärtsilä explain us their way of thinking. Wärtsilä is a global leader in smart technologies and complete lifecycle solutions for the marine and energy markets, with operations in more than 80 countries around the world. 

From Silo.AI, our Lead AI Architect Niko Vuokko talked about how to apply machine learning into predictive maintenance and what aspects make you succeed in predictive maintenance.

Robert Wendelin started off by explaining how Wärtsilä has shifted their focus from product to the entire ecosystem over the years. He highlighted the importance of making predictive maintenance part of the business model: “Predictive maintenance is all about the business model, business process optimization and especially the development of service business.” 

Wärtsilä has been building their digital journey towards machine learning based predictive maintenance for two decades.

Patrik Strand continued by talking about Wärtsilä’s new services, powered by AI, that intend to enhance safety, reliability and efficiency of the equipment Wärtsilä offers.

“Our analytics is based on the latest machine learning technologies. This allows continuous processing of a large amount of data points. We leverage computer power to be able to see even the smallest anomalies, allowing our experts to support you proactively”, Patrik explained.

Niko Vuokko from Silo.AI highlighted that switching to predictive maintenance is a company-wide disruption, so it should be treated as such. As the audience had already seen from Wärtsilä’s presentation, this change can create major customer value. However, it requires transforming not only the business model, but also how services are run and how customer relationships are built and managed.

Niko outlined in his talk four steps for this company-wide transformation:

  1. Incubate in a separate business unit with top-level support.
  2. Train people not only on activities, but on mindsets.
  3. Get partners with dedication, also as customers.
  4. Roadmap: what happens once you develop or acquire new product portfolios?

“You should build up momentum internally and with customers by using tech demos that show a clear value potential. And don’t forget to have compelling roadmap and execution to hold on to the early momentum”, Niko comments.

Silo.AI has worked on predictive maintenance solutions that leverage machine learning to estimate failure probability from patterns in data.

Thank you all for joining our breakfast seminar! We will be organizing more of these in the future, get in touch if you’re interested to join. 

Pauliina Alanen
Former Head of Brand
Silo AI
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Pauliina Alanen

Former Head of Brand

Silo AI

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