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A predictive maintenance strategy doesn't have to be complex

Looking to improve your machine uptime? Get a flying start to predictive maintenance with IXON Cloud. Combine condition monitoring with alarms and integrations, and you have a basic predictive maintenance strategy in place. 

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Ixon Predictive Maintenance Main

Get started with remote machine inspections

You may not have thought about it this way, but an engineer performing visual inspections is basically predicting maintenance. In fact, many experienced service engineers can determine if the machine is going to fail just by listening to the machine operating.

But this can be done more efficiently. With a condition-based maintenance strategy you don't have to rely as heavily on having experienced service engineers in the field. New technologies like augmented reality and remote camera inspection make it easier than ever before to combine the right insights, domain knowledge and data science. Leading the way to predictive maintenance.

Building a predictive maintenance strategy

Industrial predictive maintenance is associated with a lot of data. Before you can build a predictive maintenance strategy, you have to collect data from PLCs and peripherals for a long period of time. Include and rule out different variables and factors, so you can test the strategy with historical data and see if the results produced prove a hypothesis. Historical data from your machines can be logged, visualised and analysed in IXON Cloud without the need for coding.

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Real-time condition monitoring & alarms

Predictive maintenance is the pinnacle of condition monitoring. To start predicting future asset failure, you need a solid condition monitoring strategy and the ability to send out alarms. Delve into historical data to find data correlating to a specific failure to recognise patterns. Then combine real-time equipment monitoring with alarming to allow for just-in-time maintenance planning. Resulting in:

  • Higher uptime
  • Cost reduction
  • Premium service offering

Correlation and causality in existing data

A more advanced stage of predictive maintenance is finding correlations and causality in data. It’s a substantially more complex project to set up an automated analysis and machine learning system. IXON engineers are available to advise, help and collaborate with machine builders during this process of finding the best solution to fit their needs, such as what data and tools are necessary.

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How IXON supports you

Data analysis

Collect and store data in the IXON Cloud platform, visualise them in custom dashboards, and get clear insights into what happens in your machines.

Alarms & notifications

Set alarms and receive alerts via email, smartphone or tablet wherever you are so you can take immediate action to prevent downtime. 

Expert advice

We work together with you to find the best predictive maintenance solution, including collaboration with external partners and integrations.

Custom integrations

Use our API to integrate with 3rd party solutions like BI or machine learning tools, so you can build an advanced predictive maintenance solution.

Discover the platform

Want to know more about what IXON Cloud offers to help with predictive maintenance? View all features

Get access to IXON Cloud

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