The aim of the process area optimization survey is to reduce or even eliminate process variability that is compromising operational efficiency and product quality. There are hundreds of reasons for process variability including process design flaws, inadequate control strategies, loop health problems and poor controller tuning.   

 The optimization survey improves process performance through increased operational efficiency, reduced raw material costs, and improved product quality. 

Product Quality will be improved through reduced variability in the key process loops. 

The initial task is to collect process data in normal operating mode. The data is analyzed using time series analysis techniques such as the power spectrum and cross correlation. These are powerful techniques for determining the degree and nature of the process variability.  Control loops are retuned where appropriate using the Lambda tuning method. This tuning method yields predictable and stable loop performance. 

Additional tests will be conducted to identify the sources of process variability and develop corrective action. These tests include the following.

• Auto/Manual tests to identify if the variability is control-induced.
• Open loop bump tests to identify process dynamics and control loop ‘health’ problems such as valve backlash and stiction
• Setpoint bump tests to evaluate the control loop performance 
• Coupling bump tests to evaluate interaction between process variables and to understand the disturbance handling capability of the process. 

A report is prepared with concise recommendations for further improvement. These recommendations will typically include control valve repair/replacement, control strategy modifications, process design modifications (such as pump/valve sizing, sensor positioning, piping design) and operating strategy modifications.