The onset of the methodology is to accept input from an existing process
The first step in the methodology is to identify feasible and infeasible options and remove infeasible elements at early stages. A detailed analysis of subsequent steps continuously enables their removal to remain with the most feasible ones. Therefore, the methodology put into use structured knowledge and the principles of process intensification.
The onset of the methodology is to accept input from an existing process. Then the objective function (OF) defines the problem function specific to PI synthesis. This is characterized by two optimization variables, that is X and Y. Y is a binary decision while X is the design factor. In addition to that, the product is defined by the measurements, d as the product parameter and ß as the equipment parametric value.
The basis for identifying and selecting the objective function is based on a variety of associated costs that should be minimized in the process to optimize system outputs. Variables such as cost, volume, complexity, capital, costs, wastes, energy consumption among others are factored in the process.
Each step in the process has measures to identify bottlenecks and requisite principles for PI. Every point that is identified in the problem is directed to sub-problems and compared with PI options. A variety of PI options are evaluated to identify the most feasible option to supplement the identified problem or gap. A superstructure, as illustrated below is developed to address the gap and enable PI based on a generic model of the superstructure as illustrated below.
