Be a maintenance hero

Remove maintenance chaos and uncertainty; be a maintenance hero with Senseye in your toolkit to drive predictive maintenance

Scalable predictive maintenance

Reduce unplanned downtime and maximize OEE with Senseye, the ultimate cloud-based predictive maintenance application

Get a grip on downtime

Reduce the Total Cost of Ownership of your assets, increasing throughput, saving money and improving profitability with Senseye

Transformational

Industrial condition monitoring analytics at scale, to transform predictive maintenance through Senseye’s unique prognostics engine
Bearing
Bearing
Bearing on the main hydraulic pump will exceed design limits in 32 days, due to excessive vibration levels.
Motor
Motor
The motor ES2 on production line AC6 will fail in 40 days. Trends in vibration condition indicators have been detected.
Pump
Pump
Performance of pump 2 indicates damage to the impellor. Rectification action is recommended to avoid any secondary damage.
Actuator
Actuator
The electrical actuator ACT023 has entered a failure pattern and now has 8 days of Remaining Useful Life.
Conveyor
Conveyor
Analysis shows that the conveyor on production line G has 72 hours of operation remaining.
Gearbox
Gearbox
A misalignment of the input shaft to gearbox MGB2 has been identified.
Other
Other
As long as data is available, Senseye can monitor any machine that you have!

SENSEYE, SCALABLE PREDICTIVE MAINTENANCE

Driven by Industry 4.0 / the Industrial Internet of Things, industrial operations are increasingly autonomous. Sensors all over the factory provide real-time data on the status of production and machinery to optimize operations. Welcome to the fourth Industrial Revolution.

Senseye is the only product to offer simple predictive maintenance; using machine-learning to perform condition monitoring and prognostics analysis at scale and without requiring deep pockets or a team of expert data analysts. Senseye is your key to reducing unplanned machine downtime and increasing Overall Equipment Effectiveness (OEE).

Key Benefits

Time to value

Instant deployment and actionable results within two weeks.

ANY MACHINE

Senseye isn’t restricted to any machine type as it learns about your machinery and builds health models automatically.

Know-How

Over 40 years of predictive maintenance, condition monitoring and prognostics expertise, combined with the latest advances in machine learning and semantic technology.

Scalable

From one machine to thousands, Senseye delivers Uptime as a Service as a scalable product to drive your maintenance strategy.

Download the Senseye flyer to learn more

UPTIME AS A SERVICE

Be a maintenance hero

Senseye eliminates the chaos and uncertainty from conventional predictive maintenance, helping you to become a maintenance hero. Its advanced machine-learning works like an experienced team of condition-monitoring engineers in the cloud, getting the right information to you ahead of time, multiplying your efforts.

Fact: 45-55% increased productivity of maintenance staff

Scalable predictive maintenance

Senseye enables simple predictive maintenance, reducing unplanned downtime and maximizing OEE; it’s the ultimate cloud-based machine health application for time-starved production and operations managers. Our proprietary machine learning technology infused with over 40 years of machine failure expertise gives you fast, accurate Remaining Useful Life (RUL) information without upfront costs.

Fact: 30-50% reduction in machine downtime

 

WARNING YOU ABOUT UNPLANNED DOWNTIME BEFORE IT IMPACTS YOUR PROFITABILITY

Minimize unplanned downtime

Senseye helps you to reduce the Total Cost of Ownership of your assets, increasing throughput, saving money and improving profitability.

It’s the ultimate cloud-based uptime application to let you know what’s happening now and in the future, in a really simple way and at any scale.

Fact: 10-40% reduction in maintenance costs

Transformational

Leveraging industrial trends like the Industrial Internet of Things and condition monitoring analytics at scale with our unique prognostics engine, Senseye delivers a transformational predictive maintenance capability. As the only product to offer scalable condition monitoring, Senseye is leading predictive maintenance.

Fact: 85% increase in downtime forecasting accuracy

How it works

Senseye connects to your sensor, maintenance and operational data stored in a factory historian, database or IoT middleware solution. There is no need to add any hardware or install any software on-site.

  • Vibration

  • Temperature

  • Acoustics

  • Current

Operational data

Machine specs

Historic performance

Any other data

Don't worry about these,
Senseye uses them
all automatically!

Senseye
clever stuff

Semantic Annotation Machine Learning & statistics Fleet clustering Dynamic time warping Machine ontologies

Easy and simple to use,
Senseye automatically calculates machine health.

  • Bearing failure in 200 hours
  • Pressing machine is binding
  • Belt will fail in 10 days
  • Check driveshaft for excessive play

Senseye will
help you to

  • Reduce unplanned machine downtime by 30-50%
  • Increase productivity of maintenance staff by 45-55%
  • Lower your maintenance costs by 10-40%
  • Add predictability to your operations through an 85% improvement in forecasting accuracy
  • Reduce manual inspections and spares
  • Detect abnormalities and understand remaining useful life
  • Operate a successful predictive maintenance program
More Information

COntact Us

Get in touch and start saving money

Are you ready to take control? Start getting ahead of downtime by using Senseye to guide your decisions.

Get in contact to share your requirements and discover how much Senseye could improve your operations.

NEWS blog

6 tips on choosing the correct data for successful predictive maintenance

Time and again we encounter excited maintenance managers who possess terabytes of data; eager to kick-off their predictive maintenance project and avoid machine downtime. It never stops being painful when we take a look at the data and find that much of it us unusable for predictive maintenance purposes. 

Read More
Read More
  • 19
    July

Senseye celebrates prognostics at scale milestone of over 1,000 machines under automated predictive maintenance analysis

Senseye, the Uptime as a Service leader today announced that it has reached a significant prognostics-at-scale milestone of automatically monitoring over 1,000 machines at a single customer site for early signs of mechanical damage and failure; using machine learning to help the client to avoid unplanned downtime, without relying on expensive consultants. 

Read More