Case study: implementation of Predictive Maintenance strategy for a steam turbine
1 June 2020

Case study: implementation of Predictive Maintenance strategy for a steam turbine

Project: implementation of Predictive Maintenance strategy for a steam turbine

Challenge with the implementation of the Predictive Maintenance strategy for a steam turbine

The phenomenon of rapid increases of vibrations for a steam turbine appeared in the production plant. The causes of this phenomenon were difficult to identify. The turbine was damaged after exceeding a certain level of vibrations (regardless of the operator’s work). This was indicated with the stoppage of the installation and the need to restart the entire process. This situation caused large losses due to high gas consumption and additional costs resulting from production downtime. The objective of the project was to develop predictive models in order to identify causes and predict failures of the turbine.

Solution

ReliaSol consultants have developed and implemented (on the PdM RSIMS platform) predictive models that calculate the probability of failures based on current operating parameters. The solution enables turbine operators to take quick action to prevent the breakdown of the turbine and identify the reason for the turbine’s failure that was previously unknown.  

The prediction value is updated in one-minute cycles with the use of current sensor values. When the alarm level is reached, the system operator is informed about this fact by a voice signal (as well as e-mail and SMS notifications). The alarm signal enables the operator to change settings in advance in order to avoid breakdowns.

implementation of Predictive Maintenance strategy for a steam turbine

Benefits of implementing Predictive Maintenance for a steam turbine

The developed model returns information about the measurements that have the most significant impact on the prediction’s result, while guaranteeing 98% of forecasting accuracy. Moreover, the model enables the identification of causes of the problem. The solution enables the monitoring of the turbine’s operation in real-time, as well as minimization of maintenance costs and production losses due to downtime.

  • Minimization of the turbine’s failure
  • 98% of forecasting accuracy achieved
  • Identification of the failure’s cause
  • Constant monitoring and insight into the operation of turbines
  • Maintenance of a high degree of automation for the production process

The implementation of an innovative predictive maintenance system with the use of artificial intelligence, which forecasts upcoming failures with 98% accuracy, is one of the milestones in the development of our company. RS solutions give unlimited possibilities to control the operation of machines, get insights into their condition and enable rational production planning, which produces a significant increase in the efficiency of the company in all aspects of its functioning. The RSIMS system combined with expert knowledge is a guarantee of the highest quality of services and professional implementation of even the most comprehensive projects.

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Author:

Reliasol

Reliasol

Predictive maintenance is the future of modern industry, and we are building it today at ReliaSol! Check out our solutions based on Artificial Intelligence (AI).
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