What is predictive maintenance and how to get started with Senseye

You’ve heard the hype and it all sounds very impressive. But what is predictive maintenance and what is it best used for?

For optimal performance, all factory machinery needs to be maintained and companies often have maintenance agreements in place, usually with the original machine manufacturers or their approved service network. Whilst useful, these agreements are largely service-interval schedules, which don’t take into account actual usage and so do little to prevent unplanned downtime. This is the widely-used preventative and reactive maintenance model:

senseye real-world preventative maintenance.png

In contrast, predictive maintenance is more proactive, analysing the huge volumes of available machinery data to give you a better understanding of the ongoing health of your machines and pre-empt failure. This maintenance approach opens up opportunistic possibilities in machinery management, allowing you to adapt and enhance your existing maintenance arrangements. By analysing data to predict when machinery will break down, companies can remove surprise failures and reduce downtime, scheduled maintenance and the routine replacement of parts that may in-fact be perfectly healthy.

predictive maintenance in the factory.png 

Enabling a break from tradition

Revolutionising machinery management, predictive maintenance solution ‘Senseye’ is cloud based and automates data analysis, and the Senseye user interface is set up for operations and maintenance teams, rather than requiring specialist analysts. This approach of automating the analysis and simplifying the reporting of the resulting actions streamlines a complex task, saving time and costs, and allows maintenance teams to multiply their efforts, reacting with increased speed and accuracy.

Another benefit of automated analysis is that Senseye is scalable, so can grow with your requirements. This means that, in addition to critical machines, the wider non-critical population can now be monitored. These subsidiary machines may not be as expensive to replace, but their downtime could still be costly.

Getting started

If you are sold on the opportunities that predictive maintenance can open up, here’s how to get started. 

  1. Book a demo!
    We can discuss your specific requirements and give you a live demonstration of the Senseye software. 
  1. Get the data flowing
    Senseye accepts data in many formats and once you start streaming data, it’s all go! Senseye is data agnostic, so it works with your existing data. We don’t copy your data or need access to your internal network. Senseye doesn’t rely on expensive onsite hardware, it’s just plug and play. 
  1. See meaningful results in just two weeks
    It’s that easy. With Senseye’s automated analysis and machine learning capabilities, actionable results are available in just two weeks. Over time, you will build an understanding of the health of your machinery, so you can make informed, proactive decisions guided by the software and avoid any surprises through advance warnings. 
  1. Feed results into enterprise planning systems
    If you have existing planning and work-order systems, there are opportunities to integrate Senseye analysis, meaning you can bring all the results into one platform and avoid having multiple, disparate systems in house. With a straightforward configuration setup, we have made Senseye to integrate and benefit from. 

The future is opportunistic

To date, the manufacturing sector has benefited minimally from predictive maintenance due to difficulties with the scalability of manual (expensive) analysis. Senseye changes this - cloud based with a clear, concise user interface, Senseye has opened up predictive maintenance to those without deep expertise in data science and condition monitoring techniques.

Get started today! Book a demo here:

Request a demo of Senseye