predictive maintenance

Improve your plant reliability

You want to :
‣ Move from Curative or Preventive maintenance to Conditional and Predictive maintenance.
‣ Anticipate your process deviation and/or equipment failure due to equipment deterioration and ageing?

A fast track to Conditional Maintenance (CM)

Our Plant BI module, combined with the Contextualisation Engine’s advanced KPI elaboration, enables you to initiate maintenance actions. You can implement conditional maintenance through indicators that give you insight into the condition of your equipment.
‣ Indicators from equipment or IoT (vibration level, condition status, etc.) can be easily integrated with process sensors and IoT devices using OIAnalytics.
‣ Calculated indicators derived from process data (operating time, operating time corrected for ageing factors such as temperature, pressure…)
‣ Health indicators derived from actual measurements, such as equipment fouling, can be combined with physical models, such as an equipment digital twin.
‣ Abnormality indicators comparing actual performance with theoretical performance computed by a physical model to detect abnormal conditions.

Go one step further with Predictive Maintenance (PM)

Predictive maintenance requires good quality data to develop the appropriate anomaly detection models. The Contextualisation Engine simplifies and accelerates the generation of the appropriate data set required to develop a predictive maintenance model. Once you have the right model, you can immediately implement it in the solution using our Python code execution module. The solution’s capabilities can save you up to 80% of the time required to develop and run your predictive maintenance model.

Large scale deployment of Conditional and Predictive Maintenance

The asset context proposed in the Contextualisation Engine can help you deploy your Conditional and Predictive Maintenance using templates built by equipment type. Using these templates, you can quickly deploy your indicators, model and alerts across a large number of assets.

Integration with your CMMS

OIAnalytics can be integrated with your Computerised Maintenance Management System (CMMS). In this way, you can enrich the Contextualisation Engine with data coming from your CMMS, such as intervention events, scheduled maintenance… OIAnalytics can also feed back data to your CMMS, such as the list of equipment requiring maintenance intervention… Such integration can streamline your maintenance operations.

Reduced downtime and process variation

By taking a close look at the condition of your equipments, you can anticipate both equipment failure and process deviation, thus improving the productivity and efficiency of your plant.

Let’s talk about your business challenges