Spiro PID

Opportunity

Identifying improperly tuned PID control loops and instrumentation issues is critical to optimizing plant performance. A typical process plant has thousands of PID control loops. Monitoring each PID control loop to ensure best performance is an onerous task requiring process control expertise and process knowledge.

Solution

Spiro PID is a powerful application that delivers continuous measurement and visulatisation of PID control loop performance, valve/actuator anomalies, and sensor performance. By understanding the cause of poorly performing control loops, users can make significant improvements to process efficiency.

Expected project benefits

• 1% Production improvement
• Reduce loops running in manual to less than 15%
• 2% reduction in energy cost through oscillation reduction
• 20% reduction in off-spec product
• Full return on investment (ROI) within months

Spiro PID

 summary display

Table showing metric values for all PID loops being monitored. Each column can be sorted, and users can search and filter rows (e.g. filter to only show temperature loops).

Individual Loop analysis summary

For each PID loop a user can drill down to a more detailed visual display to better understand loop performance. A set of scaled bar graphs show the real-time value of each performance metric on a range of 0-1, where values closer to 1 indicate desirable performance. Parameters can be assigned a threshold target value to be highlighted when surpassed.

PID Loop data plot

Plot of PID components: PV, SP, OP. Highlight data where loop is in manual or has diverged from normal mode.

PID Output analysis

This can be used as a visual indication of process non-linearity, and to display control valve issues such as basklash, hysterisis, dead band, and stiction. Users are able to time shift X or Y values to account for delays.

PID Impulse response

The plot provides a direct measure of how well the PID is performing in rejecting disturbances or tracking set point changes. The plot shows characteristics such as overshoot, damping ratio, settling time, and oscillations.

PID Closed Loop Bode Plot

Shows the closed loop frequency response as an alternative way to evaluate how well the PID loop is performing in rejecting disturbances or tracking SP changes.

PID Error Autocorrelation function (ACF) Plot

An ACF plot provides an approximation of how close the controller is to ideal, minimum variance. If the controller is close to minimum variance, then the auto-correlation plot should decay quickly to zero after the process deadtime

PID Closed Loop Frequency Plot

A companion plot to the ACF plot, showing the range of frequencies over which the controller is deviating significantly from minimum variance.