Crystal ball 4.0 – how predictive maintenance benefits from engineering

Unplanned downtime and repair works during plant operations cost time and money.  ‘Predictive maintenance’ (PdM) of plants is intended to prevent disruptions to operation and reduce maintenance, service and downtime costs to a minimum. Its ‘predictions’ have little to do with the questionable practices of fortune tellers, but are based on high-accuracy IT-based processes. Analytical tools no longer simply measure actual status figures, but also use minimal changes in the measurements to identify trends that could lead to outages in the medium term. To achieve this, vast quantities of data must be constantly captured and analysed. Find out how engineering helps modern systems to cope with this task here.

Predictive Maintenance

Feeding big data with engineering data

So far, only Aucotec’s Engineering Base (EB) system platform is able to network engineering intelligently with a PdM tool. This is made possible by its special multi-tier architecture and central data depository. The system can be closely linked to high-performance analytical applications for predictive maintenance, and is capable of imaging abstract objects that could not be modelled by other systems.

‘Single source of truth’

These ‘interpretations’ – e.g. types of pressure measurements for a supply line that have been classified under a particular sensor – are mapped in a database. In this way, EB functions as the unique source of all technical data on a plant, including all values approaching or already at critical levels, dimensions and measurement units, and transfer characteristics. Since these specifications can be used simultaneously by both the control system and PdM configuration, predictive maintenance can interpret the live data from the control system without any additional effort. In other words, the Engineering Base modelling of the plant becomes the ‘single source of truth’ for the PdM process.

Intelligent workflow

After determining all the data in the engineering system, the platform transfers the bulk specification data to the PdM system – e.g. dimensions and units for possible signals. The control system also receives corresponding configuration data from Engineering Base. The control system feeds the live operational data to the predictive maintenance system, where it is processed for the evaluation logic. With the aid of this logic, the PdM system interprets the plant data on the basis of the engineering data defined by EB, so that it can subsequently carry out its analysis. A further application informs the user whether, and where, a need for maintenance might possibly arise.

Controlled data transfer

The engineering data is transferred to the PdM system either ‘on demand’ or by a time-controlled system. The transfer proceeds via Engineering Base’s advanced web communication server, which means it can take place at any time – even if the applications are not open. In this way, it is possible to guarantee that the data is always absolutely up-to-date.

This link-up between the engineering system and the PdM is fully up to the challenges of big data. It saves the huge expenditures that would be necessary if the PdM could not consistently connect the live data from the plant with the data processed in the engineering system.

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