Advanced process control has come to be a term synonymous with computer based technologies. Many companies use this process to help them with increasing their profits by improving the product capacity and minimizing expenses. Some companies have reported that they have cut their operating expenses by up to 6% once they started using advanced process control.
The exact meaning of advanced process control depends on what a company uses it for. It could mean cascade control features, a time delay compensator or optimization strategies. In layman’s terms it refers to using computer software to make things work smoothly and efficiently. Modern approaches to this system rely upon a study of system behavior and using process models.
Models of advanced process control
There are four models in advanced process control:
1. Mechanistic model – the structure of the final model that is desired can be either a lumped parameter or a distributed parameter. A lumped parameter uses ordinary differential equations while a differential parameter is used to describe behavior in one dimension and is much more complex. The mechanistic model of advanced process control is not financially feasible for most companies.
2. Black Box Model - this model describes the relationship between the system inputs and outputs. It can track trends in process behavior.
3. Qualitative model – this model is used when the process needs mathematical configuration or when the process is carried out at distinct operating systems.
4. Statistical model – this model describes techniques in terms of statistics. It provides information about the likelihood of something happening so that a solution can be found before a problem occurs. This model does not capture system dynamics. It does play an important role in analysing data so as to assist in higher level decision making.
Using one or more of these models helps companies to see where they can cut down on their expenditures and increase their profit margins.