Industry 4.0

Predictive
Maintenance

Today’s maintenance teams are leveraging INDUSTRY 4.0 driven PdM to bring digital transformation to their maintenance practice.

What is predictive maintenance?

Predictive maintenance (PdM) is maintenance that measures the performance and condition of equipment of in-service equipment during normal operation to identify any faults developing. It provides cost savings and better reliability over routine or time-based preventive maintenance.

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Where should i use it?

Planned
(PM)

For assets whose failures modes increases with time or use and can be prevented with regular maintenance e.g. valves

Predictive
(PdM)

For assets whose failures modes increases with the condition of operation and can be prevented with monitoring/measurements e.g. rotating and reciprocating

Reliability Centered
(RCM)

For assets whose failures modes are identifiable and controllable e.g. aircraft engines , large turbines.

Where does it fit in your maintenance strategy?

Off

Common PdM Tools

 

  • Vibration analysis
  • Acoustic or ultrasound analysis
  • Electrical signature analysis
  • Oil analysis
  • Infrared thermography
  • Insulation analysis
  • Laser alignment
  • Dissolved gas analysis

Root Cause Analysis (RCA) makes PdM even more powerful

The goal of predictive maintenance is to measure equipment condition and then predict its failure, followed by a root cause analysis and then preventing the failure through corrective maintenance.

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Want to get started with ioEYE Predict?

Now is the right time to change how we sense, predict and troubleshoot machine failures

IIoT sensor technology has made it possible to measure machine condition parameters like vibration, ultrasound, temperature, etc affordably and without human intervention. Machine-learning models can increase the accuracy of the predictions and make it easy for the maintenance team to run the program across a large number of equipment with minimal knowledge of condition monitoring techniques.

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Cheaper Hardware

Affordable sensor and microcontroller technologies.

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Reliable Connectivity

IoT is making sensor connectivity easier, secure and more reliable.

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Smarter Algorithms

Machine Learning(ML), Artiicial Intelligence(AI) and Bi Data are making predictions possible.

Benefits of IoT and ML driven digital transformation in maintenance

  • Reduce unexpected failure by up to 55%
  • Reduce unexpected failure by up to 55%
  • Reduce inventory carrying costs for spares by up to 28%
  • Reduced overall maintenance costs by up to 30%
  • Reduce maintenance interval without compromising on equipment reliability
  • The maintenance team can make data-driven decisions
  • Improved HSE compliance
  • Establish clear correlation between events that led to the breakdown. Data driven root cause analysis can improve plant reliability.

Choose a new and better way to maintenance

ioEYE Predict makes PdM affordable and even more powerful

IOT Sensor

Acquire contineous machine health data

ML & AI

Predict faults accurately
  • App
  • App
Autonomous

Now collect asset predictive maintenance data without human intervention and error, 24 x 7. Free up the time your team spends on data collection via an handheld.

Anywhere

Now access your machine's health and diagnostic data from anywhere using a mobile phone. Digital transformation for your maintenance team.

Advance

ioEYE Predicts assist you in identifying machines that need attention. The area where they need attention. The advance analytical tools can help you do a root cause analysis and support your decisions.

Affordable

We have used the latest technology while striking a balance between affordability and features. It is designed to get the work done cost effectively.