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    • 08
    • Feb

    The top 3 barriers to predictive maintenance

    Predictive maintenance sounds great – maintain your assets, before they show outward signs of failure and cause unplanned downtime (loss of revenue), whilst spending less money than you would for a preventative maintenance program – boosting profitability and throughput. The benefits are quite clear. Why then do relatively few companies have an active predictive maintenance program? 

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    • 23
    • Jan

    Condition Monitoring Techniques, An Overview

    Simple beginnings

    Condition monitoring, whilst now highly technical and adapted for specific industries (with Aerospace & Defence arguably leading the way) had very humble beginnings, essentially listening to a machine and trying to understand if it ‘felt right’ or not. Humans seem to have an inherent talent for this (I’m sure many of us have experience with our cars, feeling that something isn’t quite right or doesn’t sound like it should!) but pure intuition isn’t a good way to scientifically implement predictive maintenance and avoid unplanned downtime. 

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    • 22
    • Nov

    Prognostics means Remaining Useful Life

    Prognostics is the science of forecasting when your assets will stop being able to perform their intended functions. It means that you can properly perform predictive maintenance, with the right information and it is undoubtedly the future of condition monitoring

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    • 10
    • Nov

    Senseye, the Manufacturing Uptime as a Service company closes funding round

    Category: Press Releases

    Senseye, the Manufacturing Uptime as a Service company, today announced the close of a significant seed funding round, led by Breed Reply, alongside IQ Capital. Existing angel investors also participated. The capital will be used to launch Senseye’s revolutionary predictive maintenance software which automates analysis of condition monitoring data and enables advanced prognostics – automatically diagnosing failures as well as forecasting when a machine is likely to fail. 

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    • 31
    • Oct

    Enabling Predictive Maintenance with Prognostics

    Predictive maintenance is clearly superior to prescriptive maintenance and can save upwards of 40% [McKinsey] of maintenance costs. Prognostics, as the science of predicting when machinery will fail is invaluable in an effective predictive maintenance program. 

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    • 04
    • Oct

    Free Prognostics White Paper (blog)

    Uptime as a Service is the core of our offering at Senseye; we’re constantly pushing the boundaries of automated diagnostics, condition monitoring and prognostics to help you to reduce unplanned machine downtime and improve your predictive maintenance program. 

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    • 04
    • Oct

    Free Prognostics White Paper (press)

    Category: Press Releases

    Southampton UK, October 4th 2016: Senseye, the Uptime as a Service company, has published a free white for manufacturers and asset owners about prognostics, the science of predicting when machines will stop being able to perform work. 

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    • 23
    • Sep

    Automated Condition Monitoring – What it means for you

    We’ve covered a short introduction to Condition Monitoring before – it’s great but has some shortcomings in that generally you need to be quite an expert in understanding the raw data to extract value for your predictive maintenance program. 

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    • 07
    • Sep

    4 things to keep in mind when implementing Industry 4.0

    There’s a lot of hype about Industry 4.0, otherwise called the ‘Industrial Internet of Things’. With all that’s on offer, it’s easy to get distracted by the possibilities of the myriad technologies and lose sight of what it should be about – helping you to improve your throughput, quality and uptime. 

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    • 30
    • Aug

    Do diagnostic engineers have a future with the IoT?

    Category: Press Releases

    Senseye, the Uptime as a Service company, will be revealing how it’s making diagnostic engineers a thing of the past at the NMI Future World 2016 “Deep Tech” conference to be held in London, UK over the 15th-16th of September. 

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