Automatic monitoring of your process data

Get all the information out of your process data using your predictive machine maintenance software.

We are immersed in a world where automation has been a reality for some years now. The automatic process data acquisition systems that have been installed in industrial plants provide much more data than we can process, i.e., we record everything, but we do not extract all the useful information from these data. It is therefore necessary to process this data in an automatic way as well.

The analysis of machinery vibrations appeared with the first oscilloscopes, it gained strength when these oscilloscopes developed the function of displaying the amplitude/frequency graph (FFT), but it was implemented as an essential tool when the data collection in programmed routes was automated and the first analysis of these data was also automated through the software developed for predictive maintenance by vibrations. This software was intensively developed and today we have excellent tools that facilitate our work to detect faults in machinery from their first symptoms.

More and more users of predictive software are wondering if the successes achieved from vibration analysis could also be achieved from other data, such as those from oil analysis, ultrasound, electrical parameters... but also temperatures, flow rates, pressures, consumption... The study and analysis of these data serves both to detect the first symptoms of the development of failures and to detect points of the process with a lower efficiency than expected, so we can also apply this analysis to the achievement of results on the plan for the improvement of energy efficiency.

Transferring the data measured by the Distributed Control System (DCS) to the Predictive Maintenance Software (PdM) is not a costly task. Most industrial plants have ^PI* type tools, which allow the export of the data recorded by the DCS to other information analysis systems. In many cases, these data are processed using standard applications, such as ^Excel*, which, although it is flexible to configure calculations from the data recorded in the tables, the analysis process is mainly manual, which means time consumption of qualified personnel. Although no company with a well-implemented vibration-based predictive plan uses the Excel spreadsheet as predictive software, the question arises as to whether it is possible to automate the analysis of process data using the predictive tools developed for vibration predictive maintenance, which already exist in industrial plants.

The treatment of the process data recorded by the DCS by means of a predictive application brings the following benefits:

Increased plant reliability. Because failures are detected at an early stage.

2. Increased energy efficiency. Because the processes where the results are below the established levels are identified.

3. Increased safety. Because dangerous situations are avoided as deviations from normal operation are known from the slightest change.

All these advantages make it advisable to incorporate process data into your predictive software to increase the ability to detect failures, deviations from normal operation and process efficiency drops.

For more information contact Preditec/IRM at info@preditec.com.

^*) PI is an OSIsoft product; Excel is a Microsoft product.