Predictive Monitoring in Continuous Processes

PROBLEM STATEMENT

Continuous processes maximizes production and operate at a considerably lower cost compared to other process method. However, this process method is asset intensive and an unexpected breakdown would cause high production loss. The process is automatically controlled and monitored with the help of control systems such as DCS, PLC, SCADA and etc. in order to keep the process online. In predicting unexpected equipment breakdown, the control system has limitations as it can only alert the operators only a few hours or once problem arises. Is it possible to expect the unexpected?

Figure 1: Control System in a Plant

DESCRIPTION

The process dashboard is a software application first developed as an easy tool for managers to monitor the plant performance and more specifically their KPI. The software connects to the data historian and automatically translate the hundreds or not thousands of data from transmitters to easy to read summary. The process parameters and operating points are also plotted over time and compared to its safe operating range. While developing the app, it was discovered that the app can also be a tool for predictive monitoring.

For the solution to be effective, the event or breakdown must be predicted days or even weeks ahead. This can be done by continuously monitoring the equipment performance throughout its service. The parameters extracted from the data historian is used to determine the current efficiency of the equipment with pre-installed back calculations  and utilising the design curve or design rating from vendor as basis. By monitoring the trend of the equipment efficiency, any kind of abnormality can quickly be found ahead of time.

More specifically, the performance scale (of which it is considered to be in good condition or not) can be pre-set to the app and the current condition of the equipment will be shown based on the setting as shown in Figure 2. Then based on the performance trend, the app will be able to predict the days for the equipment to go off spec. With this information, user can easily make decisions of whether to perform a check on the equipment immediately or wait for the next scheduled maintenance.

Figure 2 : Screenshot from Process Dashboard, KPI page for Equipment Performance

On top of that, the equipment efficiency is also illustrated in a way users can observe how fast the equipment is deteriorating and falling out of its design performance. Equipment such as compressors and pumps has their design curve thus the equipment current performance can be plotted on the design curve as shown in Figure 3. Besides that, the equipment performance can also be determined by computing the energy loss such as the case for heat exchangers.

Figure 3 : Screenshot from Process Dashboard, Compressor Performance

KEY FEATURES

The Process Dashboard application not only can monitor and predict equipment failure, the app key features includes;

  1. Monitor real time KPI
  2. Monitor plant performance on and off site
  3. User friendly interface
  4. Predict equipment failure
  5. Reduce time to compile and analyse plant data and performance
  6. Users/managers can make fast and informed decisions
  7. Secure one way connection, user can only monitor performance without being able to control the plant.
  8. Tailor made for each plant

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